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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/1 - Introduction - lang_en.srt
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Hi, everybody, and welcome to the first lesson
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of the Software Engineering Course. In this introductory lesson
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I will first provide an overview of the
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whole course and then try to answer two important
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questions about software engineering, which are, what is
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software engineering and why do we need it? And
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to spice up the content a bit I
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will also interview several experts in the software engineering
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field from both academia and industry and ask them these
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very questions. So without any further ado, let's begin the lesson.

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/10 - Software Development - lang_en.srt
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Now that we saw how software engineering was born and we
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saw some of the problems that led to the birth of software
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engineering. Let's see how we can do better. How can we
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preform software development in a smarter, in a better way, a more
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successful way? So what I'm going to show here is the
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way I see software development. To
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me software development is fundementally going
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from an abstract idea in somebody's head, for example, the customer's head,
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to a concrete system that actually implements that idea and hopefully it
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does it in the right way. And this is a very
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complex process. It can be overwhelming. So, unless we are talking about
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the trivial system, it's very complex for us to keep in mind
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all the different aspects of the systems, and to do all the
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different steps required to build this system, automatically. So that's when
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software processes come to the rescue. So what is a software process?
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A software process is nothing else but a way of breaking down
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this otherwise unmanageable task into smaller steps. In smaller steps that we
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can handle. And that can be tackled individually. So having a
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software process is of fundamental importance for several reasons. First of
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all, for non-trivial systems, you can't just do it by getting
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it, by just sitting down and developing. What you have to
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do instead is to break down the complexity in a systematic
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way. So software processes are normally systematic. And you need to
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break down this complexity, in a more or less formal way.
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So software processes are also a formal, or semiformal, way of
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discussing, or describing, how software should be developed.
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So what are the steps involved in developing software?

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/11 - Software Process - lang_en.srt
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One thing you need to know right away about software processes
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is that there's not just one single process, but there are multiple,
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possible processes, depending on your context, depending on the kind of
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applications that you are developing. In this course, we are going to try
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to cover the spectrum of the possible processes, as much as
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possible, by focusing on four main software processes. The first one is
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what we call normally the waterfall process. And, we call it waterfall
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because in the process we go from one phase to the other
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in the same way in which water follows the flow
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in a waterfall. The second process that we consider is what
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we call evolutionary prototyping, and in this case, instead of
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following this set of rigid steps, all we're trying to do
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is to start with an initial prototype and evolve it
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based on the feedback from the customer. We will then move
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towards a slightly more formal process, which is the rational unified
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process or the unified software process. And this is a kind
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of project heavily based on the use of UML, so we
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will also cover UML when discussing this kind of project. Finally,
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the fourth kind of process we will consider is the family
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of agile software processes. And these are processes in which we
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sacrifice the discipline a little bi,t in order to be more
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flexible and be more able to account for changes and in
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particular for changes in requirements. We are going to cover each
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one of these four processes extensively in the rest of the class.

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/12 - Preliminary Questions - lang_en.srt
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So, now before we actually jump to the
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discussion of software processes I want to ask you
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a couple of preliminary questions. The first one is,
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what is the largest software system on which you
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had worked? And you should enter here the size.
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And the second question I'm going to ask is how
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many LOC or how many lines of code per
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day you were producing when working on this system?

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/13 - Preliminary Questions Solution - lang_en.srt
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We're going to go back to these two questions
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and to your answers later. But I wanted to
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gather this information beforehand, so that your answers are
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not biased, they're not influenced by this subsequent discussion.

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/14 - Preliminary Questions - lang_en.srt
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So now I want to ask you one additional question, which is how many lines
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of code a day do you think professional
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software engineers produce? Do you think they produce
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25 lines of code? Between 25 and 50? Between 50 and 100? Between 100 and 1000?
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Or more than 1000 a day? And remember
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that here we're talking about professional software engineers.

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/15 - Preliminary Questions Solution - lang_en.srt
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Studies has shown that, on average, developers produce between
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50 and 100 lines of code a day. And that
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might not seem much. Why, why only 50 to
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100 lines of code in a whole day? And the
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answer is because coding is not everything. When you
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develop a system writing code is not the only thing
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you have to do. It's not the only activity that
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you have to perform. And that's a very important point.

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In fact, software processes are normally characterized by several phases, what
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we call the software phases, and only one of these phases is
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mainly focused on coding. The other phases are meant to support
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other parts of software development. The first of these phases is called
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requirements engineering and that's the phase in which we talk to
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the customer, to the stakeholders, whoever we are building the software for.
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And we try to understand what kind of system we need
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to build. Then we use this information to define our design and
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the design is the high-level structure, that then can become more
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and more detailed, of our software system. Once we've defined our
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design we can actually move to the next phase, which is
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the implementation, in which we write code that implements the design which
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we just defined. After implementing the code, we need to verify
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and validate the code. We need to make sure that the code
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behaves as intended. And finally, we need to maintain the code.
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And maintenance involves several activities like,
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for example, adding new functionality or
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eliminating bugs from the code or responding to problems that
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were reported from the field after we released the software.
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We will look at all of these activities and of
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the software development process in detail, in the rest of the
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class. And for each activity, we will look at the
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fundamental principles and how it is done currently. And in
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some cases, we will also look at some advance ways
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to do it. For example, more research approaches for that activity.

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We will also look at how tools can improve software phases,
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the software activities, and can support software development tasks in general.
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And this is something that I will repeat over and over
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in the class, tools and automation are fundamental, in software engineering.
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And they're fundamental for improving productivity, not only efficiency but also
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effectiveness of our activities in the software development process. So let
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me go back to one of the diagrams that I showed
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you before. If you remember we had this qualititive diagram in which
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we were showing that one of the issues that led to the
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software crisis was the fact that developers' productivity was not able to
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keep up with the software size and complexity, with the growth in
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the importance and the complexity of software. What tools can help us
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to do is to change this and basically move this curve from
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this original position up here. So that it gets closer and closer
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to what we need to develop the software that we need to
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build. So let me discuss examples on how tools can improve productivity.
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For example, if we are talking about development, think about
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what kind of improvement it was to go from punch
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cards to modern IDEs. If we're talking about languages, think
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about of how much more productive developers became when going from
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writing machine code to writing code in high-level languages. And
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finally, if we talk about debugging, which is a very important
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and expensive activity, moving from the use of print lines
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to the use of symbolic debuggers dramatically improve the effectiveness and
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efficiency of development. And these are just some of the
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tools that we will discuss in the rest of the class
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and notice that we will also use the tools in practice.
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So we will use the tools before projects and also during
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the lessons and for assignments. In particular, we will use
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three main kinds of tools. The first type is IDE's. And
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I'm pretty sure you're familiar with IDE's. These are integrated development
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environments. So, advanced editors in which you can write, compile, run,
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and debug and even test your code. We'll also use a
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version control system, systems that allow you to save, and restore, and
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check the differences between different versions of the code, in particular
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we will be working with git. We will also be looking at
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other kinds of tools like coverage and verification tools. These are
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tools that can help you during testing and I'm a big fan
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of these tools, so I'm really going to stress the usefulness
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of these tools and how you should use them in your development.

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usth/ICT2.7/P1L1 Introduction and Overview Subtitles/2 - Importance of Software Engineering - lang_en.srt
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First, let me start by asking a couple of very
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natural questions that you might have when considering whether to take
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this course. The first one is what is software engineering.
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And the second, very related one, is why do we need
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it? So what I did was actually to go out
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and ask some of the main experts in the field, both
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in academia and industry, these very questions and let's see what
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they said. What is software engineering and why is it important?
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>> Okay, can I start with another question?
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>> Of course.
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>> Okay, first what is a computer? It's a programmable device. So the essence
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of computing is programming. So program development
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is basically the most essential use of the
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computer. So software engineering is the discipline
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that investigates program development. So, how can it
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been done more efficiently? What's the best
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way of doing program development? And how can
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you develop reliable programs? So that's how I would define
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it. But I consider any
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software development activity software engineering activity
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>> Software engineering is the systematic application of methods to build
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software in a rigorous way. And I think one of the
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aspects that I like to bring into the notion of software
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engineering is that it's something that involves not only kind of
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technically building the system but understanding the
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requirements, working with stake holders. Trying to
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find a solution that balances all of the stakeholder needs in order to deliver
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the software thats tested and its rigorous to meet the needs of a stakeholder.
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Well, software engineering is the whole process
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of creation of software using engineering principles.
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>> My view is kind of a holistic
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view and I think about it from the perspective
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of how is software engineering different from programming.
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So, I think that research about programming is all
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about the create part of software. And that
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software engineering is about the entire life cycle. So,
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that's one aspect. And the other aspect of the
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definition is it's about quality, the quality of software.
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Software engineering even considers things long after you ship which we all know
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is one of the, it is the largest economic piece of software development.
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>> So, improve, software engineering process
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for better software productivity and quality.
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>> The set of activities that one engages in when building software
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systems or software products. It's fundamentally a venue-creating
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activity. It involves social processes.
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>> Software engineering is the act
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of many people working together and putting
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together many versions of large and complex
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systems. And our world depends on software,
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software is immensely complex and we need
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many, many smart people to build these things.
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>> Well, engineering I think is the activity of envisioning and
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realizing valuable new functions with sufficient
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and justifiable confidence that the resulting
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system will have all of the critical quality attributes that are necessary
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for the system to be a success. And software engineering is the
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activity of doing this not only for
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the software components of engineering systems but
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for the system overall, given that it's
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so heavily reliant on it's underlying software technologies.
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>> So, I would say software engineering is the
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kind of art and practice of building software systems.
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>> Software engineering, in a nutshell, is a set of
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methods and principles and techniques that we have developed to enable us to
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engineer, or build, large software systems that
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outstrip or outpace one engineer's or even a small
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team of engineer's ability or abilities to understand
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and construct and maintain
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over time. So it requires a lot of people, it requires a long,
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term investment by an organization or a number of organizations, and often times
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it requires support for systems that that are intended for one purpose but end
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up getting used for many additional purposes in addition to the original one.
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>> Software engineering is about building and constructing very large-scale
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high-quality systems, so the high quality is the big issue.
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>> Software engineering is engineering discipline of developing
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software-based systems, usually embedded into larger systems composed of
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hardware and and humans [LAUGH] and business
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processes and processes in general. And why is that important?
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Well, because software is pervasive in all industry sectors
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and therefore systems must be reliable, safe and secure.
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>> Why can't we just get that by sitting down and writing software?
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>> Well, you could if software was small and
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simple enough to be developed by one or two
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people together in a room. But software development now
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is distributed, involves teams of people with different backgrounds
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who have to communicate with each other. It also involves customers,
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clients, users. Software engineers have to work with
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hardware engineers, with domain experts and therefore,
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well, no, we can't simply sit down and start coding.
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>> Software engineering is mostly being able
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to program. And you need to be able to put big
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systems together so that they actually work. That's my simple definition.
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>> And if you don't use software engineering practices,
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you're not going to be able to put them together?
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>> Well, you're not going to be able to reliably
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put them together. So basically, you could maybe hack something up,
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but it's not going to necessarily stand the test of time.
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If somebody wants to change it it's probably going to break.
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>> It's important
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because if you don't think about how you're building this system and
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how you're trading off different aspects,
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like performance and scalability and reliability, then
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it's going to end up breaking or not lasting very long or not,
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not doing everything that you want it to do, or being really expensive.
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>> If it's not done in a principled way it will
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be bad and every user will suffer. That's why we need
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software engineering.
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>> Why is it important? Because, I mean these two goal, productivity, faster,
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in developing software. And higher quality
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would be apparently important. Software is everywhere.
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>> It's important because we use software in everyday life. Everything's
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built on software systems. And these are ubiquitous across our society.
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>> It's
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important because software is everywhere around us and the way we build it,
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and the way we maintain it, is something that determines almost a basic
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quality of life nowadays. And getting that software right can make a difference,
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oftentimes, between a really fun product and one that you won't like to use
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a reasonably successful company, or one that fails. And in
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more extreme cases even the difference between life and death,
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if you think about the software that runs in the
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airplane on which many of you fly on a regular basis.
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>> There are programs out there that if they screw up we are all screwed.
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>> Software engineering is crucially
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important because it's the engineering discipline
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that is uniquely capable of carrying out
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the engineering mission for software reliant systems.
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>> In the U.S we've all seen an unfortunate example with
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a system that went badly wrong in healthcare.gov and that system wasn't
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engineered correctly. And I think if we look at the reasons for
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that, they stem back to somewhere at the intersection between requirements and
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architecture and politics and project management, and all of these things are
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important concepts that have to go into the software engineering mix.
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>> It would end up in lots and lots of chaos because people
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wouldn't know how to organize themselves and
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wouldn't know how to organize software. Many
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of software engineering has very simple rules that you need to apply properly in
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order to get things done. And people who look at these rules and think,
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these rules are so super simple. This is totally obvious. But once
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you try to apply them, you'll find out they're not obvious at all.
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>> Now that we've heard these experts, let me show you an
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example that illustrates what can happen
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when software engineering practices are not suitably
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applied. [NOISE].

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Now that you watched this small video, I like
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to ask you, what is this? Do you think
3
00:00:03,660 --> 00:00:06,330
it's fireworks for the 4th of July celebration, or
4
00:00:06,330 --> 00:00:08,280
maybe it was a flare gun in action, or
5
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maybe again it was the explosion of the Ariane
6
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five rocket due to a software error. What do
7
00:00:12,280 --> 00:00:14,190
you think? And in case it helps, I'm also
8
00:00:14,190 --> 00:00:16,450
going to show you an actual picture of this event.

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As you probably guessed, these are not fireworks for the 4th of
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July but, rather, the explosion of the Ariane 5, which happened 30 seconds
3
00:00:06,670 --> 00:00:09,250
or so after takeoff due to a software error. And this is
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just an example of what can go wrong when we don't build software
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and we don't test and verify and perform quality assurance of software
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in the right way, and quite an expensive one. In fact, to develop
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00:00:18,540 --> 00:00:21,250
and to build the Ariane 5 it took 10 years. The cost
8
00:00:21,250 --> 00:00:25,240
was around $7 billion and there were $500 million of cargo on board.
9
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Luckily, at least there were no humans on the
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00:00:27,280 --> 00:00:29,400
rocket. And you can find more details in case
11
00:00:29,400 --> 00:00:31,610
you're interested about the Ariane 5 accident in the
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00:00:31,610 --> 00:00:33,230
lesson notes. I put a couple of links there.

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And even if we don't go to these extreme examples, I'm
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sure that you have all experienced
3
00:00:04,380 --> 00:00:06,540
software problems, typically manifested in what
4
00:00:06,540 --> 00:00:09,630
we call a crash. And that crash might happen while you're
5
00:00:09,630 --> 00:00:13,230
finishing your homework or that three-page long email that you were preparing
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00:00:13,230 --> 00:00:15,900
for the last two hours. But why's it so difficult to
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build software, or better, why's it so difficult to build good software?
8
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And how can we do it? This is exactly the topic
9
00:00:22,200 --> 00:00:25,190
of this class. And the reason why software engineering is a fundamental
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discipline in computer science. To motivate that, in this class, we
11
00:00:28,330 --> 00:00:32,259
will study a set of methodologies, techniques, and tools, that will help
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00:00:32,259 --> 00:00:35,150
us build high quality software that does what it's supposed to
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00:00:35,150 --> 00:00:38,540
do. And therefore, makes our customers happy. And that does it within
14
00:00:38,540 --> 00:00:42,375
the given time and money constraints. So within the budget that
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is allocated for the software. Before
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jumping into today's software engineering techniques
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though, let me take a step back and look at how
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we got here, as I believe it is very important to have
19
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some historical perspective on how this discipline was
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00:00:52,690 --> 00:00:54,840
born and how it was developed over the years.

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To do that we'll have to go back in time to
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the late 60s. So what was happening in the 60s? Well for
3
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example the first man landed on the moon. That was also
4
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time when Woodstock took place and also the time when the first
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60 second picture from Polaroid was created. Concurrently to these events,
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which you probably didn't witness in first person, that was also the
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time when people started to realize that they were not able
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to build the software they needed. This happened for several reasons and
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resulted in what we call the software crisis. So let's
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look at some of the most important reasons behind this
11
00:00:31,820 --> 00:00:35,760
crisis. The first cause was the rising demand for software.
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Now you're used to see software everywhere: in your phone,
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in your car, even your washing machine. Before the 60s,
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00:00:41,530 --> 00:00:44,590
however, the size and complexity of software was very limited
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and hardware components were really dominating the scene. Then things
16
00:00:47,580 --> 00:00:51,490
started to change and software started to be increasingly prevalent.
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So we move from a situation where everything was mostly
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hardware to a situation in which software became more and more
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important. To give an example, I'm going to show you the growth
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in the software demand at NASA along those years. And in
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particular, from the 1950s to more or less 2000. And this
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is just a qualitative plot but that's more or less the
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ways things went. So the demand for software in NASA grow
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exponentially. And the same happened in a lot of other companies.
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For example, just to cite one, for Boeing. So the
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amount of software on airplanes became larger and larger. The
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second cause for the software crisis was the increasing amount
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of development effort needed due to the increase of product complexity.
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Unfortunately, software complexity does not increase linearly with size. It
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is not the same thing to write software for a
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class exercise or a small project, or a temp project,
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than it is to build a software for a word processor,
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an operating system, a distributed system, or even more complex and larger
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system. And what I'm giving here is just an indicative size for
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the software so the class exercise might be 100 lines of code,
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the small project might be 1000 lines of code, in the other thousand
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lines of code, and so on and so forth. For the former,
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the heroic effort of an individual developer can get the job done.
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So that's what we call a programming effort. If you're a good
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00:02:03,850 --> 00:02:07,340
programmer, you can go sit down and do it, right. For the latter,
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this is not possible. This is what we called the
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software engineering effort. In fact, no matter how much programming languages,
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development environments, and software tools improve, developers could not keep
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up with increasing software size and complexity. Which leads us to
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the third problem that I want to mention and the
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third reason for the software crisis. And this cause is the
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slow developer's productivity growth. So let me show this again
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with a qualitative diagram. And this is taken from the IEEE
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Software Magazine. And what I'm showing here is the growth in
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software size and complexity over time, and how the developers' productivity
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really couldn't keep up with this additional software complexity, which resulted
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in this gap between what was needed and what was actually available.

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So now let's take a quick break and have a recap
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of what we just discussed. I want you to think about what
3
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are the major causes of the software crisis. I'm going to provide you
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a set of possibilities and I would like for you to mark
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all that apply. Was that increasing costs of computers? Was it increasing
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product complexity, or maybe the lack of programmers? Or was it, instead,
7
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this slow programmers productivity growth? The
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lack of funding for software engineering
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research? The rise in demand for software? And finally, was it maybe
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the lack of caffeine in software
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development organizations? Again, mark all that apply.

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So, if you think about what we just discussed. Definitely one
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of the causes was the increasing product complexity. Products were becoming more
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and more complex and software was replacing more and more, what
4
00:00:09,510 --> 00:00:11,860
was before, provided by hardware components.
5
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Slow productivity growth was another problem,
6
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because programmers could not keep up with the additional complexity of
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the software that they had to develop. I would like to say
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there was lack of funding for software engineering research because I'm
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a software engineering researcher, but that was not one of the reasons
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for the software crisis. Instead, it was
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the rising demand for software. Again, more
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and more software was being required and
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more and more software was replacing hardware.

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After recapping the three major issues that characterize a software crisis
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let's see what was the evidence that there was indeed a
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crisis. So what I want to discuss now is the result
4
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of a study performed by Davis in 1990s. So in even
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more recent times than the 60s and the 70s. And the
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study was performed on nine software projects that were totaling a
7
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cost around $7 million and I'm going to show you how this
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projects went using this representation, this pi representation, in which I'm
9
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going to discuss what each of the segment of the
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pi represent. So let's start looking at the first one.
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This is a software that was usable as delivered. Other
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software was delivered, and usable, either after some changes or
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after some major modifications, so within additional costs involved.
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But the striking piece of information here is that the
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vast majority of the software, so these two slices, were
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software that was either delivered but never successfully used or
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software that was not even delivered. And this corresponded
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to five over the seven total million dollars for
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all the projects. So clearly, this shows a pretty
20
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grim picture for software development and its success. In short,
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there was clear evidence the software was becoming to
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difficult too build and that the software industry was facing
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a crisis. And this is what led to the
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NATO Software Engineering Conference that was held in January 1969,
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which is what we can consider the birth of software engineering. And what
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I'm showing here is a drawing of the proceedings for that conference. And if
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00:01:23,080 --> 00:01:26,020
you look at the class notes you can see a link to the actual
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proceedings, in case you are interested in
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looking at the issues that were discussed.

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Hi, in the last lesson we provided an overview of the course and motivated the
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need for software engineering. In this lesson,
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we will present and start discussing several traditional
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software engineering life cycle models. We will
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talk about their main advantages, and also about
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their shortcomings. We will also talk about
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classic mistakes in software engineering that is well
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known ineffective development practices, that when
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followed, tend to lead to better results. And
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00:00:32,590 --> 00:00:35,120
covering those, will hopefully help us to avoid
11
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them in the future. And because in this
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lesson, I will discuss some fundamental aspects of
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software engineering, to suitably introduce these topics, I
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went to the University of Southern California, to
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interview one of the fathers of software engineering;
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Professor Barry Boehm.
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>> A well, a software life cycle is a sequence of, of decisions that you
18
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make, and it's fundamentally those decisions are
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going to be part of the history of the
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software that. You are going to build that other people are going to use, and
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the process model is basically answering the question of what do I do next and
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how long shall I do it for. And again, because there are a lot of different ways
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you can make that decision, you need to
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figure out which models are good for which particular
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situations. So, for example, we've, written a book
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that's called Balancing Agility and Discipline. It says under
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what conditions should you use agile methods, under
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which conditions should you invest more time in analyzing
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the situation and planning what you're going to do and the like. And so,
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typically if the project is, is small where it's three to ten
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people, agile works pretty well. If it's 300
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people, then I think we don't want to go that way. If the affect of
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the defect is loss of comfort or limited funds, then agile is fine,
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but if it is a loss of life, then you don't. On the other hand if, if
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you have a situation where you have lot
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of unpredictable change, you really don't want to spend
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a lot of time writing plans and lots of documents. In some cases you may have a
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project where you want to do waterfall in
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some parts and agile in others. So, these are
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the kind of things that, that make the choice of life cycle process
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model very important and very interesting as a subject of research.

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At this point, you know the possible activities, the
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possible phases performed during the software development process. But there
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this something that we still haven't discussed, which is
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very important. And that is how should we put these
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activities together to develop software? And this all comes
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down to the concept of software process model. Also called
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software lifecycle model. And what this is, is a
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prescriptive model of what should happen from the very beginning
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to the very end. Of a software development process. The
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main function of the life cycle model is to determine
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the order of the different activities so that we know
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which activities should come first and which ones should follow. Another
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important function of the life cycle model is to determine
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the transition criteria between activities. So, when we can go from
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one phase to the subsequent one. In other words, what
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the model should describe is what should we do next and
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how long should we continue to do it for each activity
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in the model. Now lets see a few traditional software process
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models. I will discuss them here at the high level and
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then revisit some of these models in the different mini courses.

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The first model we want to discuss is the grandfather of
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all life cycle models. And it is the waterfall model. In
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the waterfall model the project progresses to an orderly sequence of
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steps. From the initial software concept, down until the final phase.
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Which is system testing. And at the end of each phase
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there will be a review to determine whether the project is
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ready to advance to the next phase. The pure waterfall model
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performs well for softer products in which there is a stable
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product definition. The domain is well known and the technologies
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involved are well understood. In these kind of domains, the
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waterfall model helps you to find errors in the early,
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local stages of the projects. If you remember what we discussed,
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this is the place where we want to find errors,
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not down here because finding them here will reduce the cost
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of our overall software development. The main advantage of the
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waterfall model is that it allows you to find errors early.
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However, the main disadvantages of the waterfall model arise
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from the fact that it is not flexible. Normally,
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it is difficult to fully specify requirements at the
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beginning of a project. And this lack of flexibility is
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far from ideal when dealing with project in which
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requirements change, the developers are not domain experts or
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the technology used are new and evolving, that is
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it is less than ideal for most real world projects.

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The next model that we will discuss is the spiral
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model, which was first described by Barry Boehm, which is
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the professor that we interviewed at the beginning of this
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lesson. In his paper from 1986 that was entitled A Spiral
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Model of Software Development and Enhancement. And one of the
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main characteristics of that paper is that it was describing the
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spiral model using a diagram, which is the one that
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I'm showing you here, and this diagram has become very very
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popular, and you probably saw it either in this
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form or one of the many variations of the
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diagram. So I'm not going to discuss all of
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the details of the spiral model, but I just want to
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give you an idea of its main characteristics. The
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spiral model is an incremental risk-oriented lifecycle model that has
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four main phases listed here: determine objectives, identify and
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resolve risks, development and tests, and plan the next iteration.
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A software project will go through these four phases in
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an iterative way. In the first phase, the requirements will
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be gathered. In the second phase, the risks and the
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alternate solutions will be identified, and a prototype will be produced.
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Software and tests for the software are produced in the
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development and test phase, which is the third step of the
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process. Finally, in the fourth phase, the output of the
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project, so far, is evaluated, and the next iteration is planned.
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So basically, what the spiral process prescribes is a
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way of developing software by going through these phases in
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an iterative way, in which we learn more and more
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of the software, we identify more and more, and account
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for, more and more risks and we go more
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and more towards our final solution, our final release. There
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are several advantages of using a spiral model. The first
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one is that the extensive risk analysis does reduce the
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chances of the project to fail. So there is a
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risk reduction advantage. The second advantage is that functionality can be
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added at a later phase because of the iterative nature of
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the process. And finally, software is produced early in the software
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lifecycle. So, at any iteration, we have something to show
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for our development. We don't wait until the end before producing
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something. And then of course there's also the advantage that we
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can get early feedback from the customer about what we produced.
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The main disadvantages on the other hand of
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the spiral model, are that the risk analysis requires
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a highly specific expertise. And unfortunately, the whole success
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of the process is highly dependent on risk analysis.
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So risk analysis has to be done right.
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And finally the spiral model is way more complex
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than other models, like for example, the water fall
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model. And therefore it can be costly to implement.

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The next process model I want to discuss is evolutionary
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prototyping, which works in four main phases. We start
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from an initial concept, then we design and implement
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a prototype based on this initial concept, refine the prototype
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until it is acceptable, and finally we complete and
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release the prototype. Therefore, when developing a system using
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evolutionary prototyping, the system is continually refined and rebuilt.
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So it is an ideal process when not all requirements
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are well understood. Which is a very common situation. So, looking
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at this in a little more details, what happens is that
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developers start by developing the parts of the system that they
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understand, instead of working on developing a whole system, including parts
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that might not be very clear at that stage. The partial
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system is then shown to the customer and the customer feedback
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is used to drive the next iteration, in which either changes
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are made to the current features or new features are added.
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So, either the current prototype is improved or the
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prototype is extended. And finally, when the customer agrees that
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the prototype is good enough, the developers will complete all
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the remaining work on the system and release the prototype
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as the final product. So let's discuss as we did
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for the previous process models, what are the main advantages
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and disadvantages of evolutionary prototyping. In this case, the main
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advantage is the immediate feedback. Developers get feedback immediately as
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soon as they produce a prototype and they show it to
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the customer and therefore, the risk of implementing the wrong system is
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minimized. The main negative is the fact that it's difficult to plan.
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When using evolutionary prototype it is difficult to plan in advance how
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long the development is going to take, because we don't know how
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many iterations will be needed. And another drawback is that it can
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easily become an excuse to do kind of do cut and fix
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kind of approaches in which we hack something together, fix the main
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issues when the customer gives us feedback, and then continue this
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way, until the final product is something that is kind of
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working, but it's not really a product of high quality. Something
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else I want to point out before we move to the next
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software process model is that there are many different kinds of
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prototyping, so evolutionary prototyping is just
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one of them. For example, throwaway
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prototyping is another kind of prototyping in which the prototype is
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just used to gather requirements, but is thrown away at the end
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of the requirements gathering, instead of being evolved as it happens here.

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O próximo modelo que eu quero discutir é prototipagem
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evolutiva, que funciona em quatro fases principais. Nós começamos
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por um conceito inicial, então nós desenhamos e criamos
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um protótipo baseado neste conceito inicial, refinamos o protótipo
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até que ele se torne aceitável e finalmente nós completamos e
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liberamos o protótipo. Desta maneira, quando desenvolvemos um sistema usando
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prototipagem evolutiva, o sistema é constantemente refinado e refeito.
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Então este é o processo ideal quando nem todos os requisitos
9
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estão bem compreendidos. O que é uma situação bastante usual. Então, olhando
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para isso um pouco mais detalhadamente, o que ocorre é que
11
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os desenvolvedores começam no desenvolvimento das partes do sistema que eles
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compreendem, ao invés de trabalhar no desenvolvimento do sistema com um tido, incluindo as
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parte que não estão ainda muito claras. O sistema
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parcial é então mostrado ao cliente e a opinião do cliente
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é usada para guiar a próxima iteração, na qual tanto modificações
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são feitas nas atuais feições, como novas feições são adicionadas.
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Assim, ou o protótipo atual é melhorado ou o
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protótipo é aumentado. E finalmente, quando o cliente concorda de
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que o protótipo está suficientemente bom, os desenvolvedores irão completar todo
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o trabalho faltante no sistema e liberar o protótipo
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como o produto final. Então vamos discutir como fizemos
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para os modelos de processos anteriores, quais são as principais vantagens
23
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e desvantagens de prototipagem evolutiva. Neste caso, a principal
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vantagem é apreciação imediada. Os desenvolvedores recebem a opinião imediatamente,
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tão logo eles produziram o protótipo e o mostraram para o
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cliente e desta maneira, o risco de implementar erradamente o sistema é
27
00:01:21,050 --> 00:01:25,150
minimizado. O principal ponto negativo é que isso é difícil de planejar.
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Quando é usada a prototipagem evolutiva é difícil de antecipar por
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quanto tempo o desenvolvimento irá levar, porquê nós não sabemos quantas
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iterações serão necessárias. E outro inconveniente é que isso pode facilmente
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se tornar uma desculpa para começar a fazer aquele tipo de abordagem de
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"corte-e-correção" na qual nós começamos a enjambrar as coisas, corrigir os
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principais defeitos quando o cliente nos dá sua opinião e então continuamos desta
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maneira, até que o produto final se torne tipo algo que
35
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funciona, mas que não é de fato um produto de alta qualidade. Outra coisa
36
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que eu quero apontar antes de irmos ao próximo
37
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modelo de criação de software é que existem diversas maneiras de
38
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prototipagem, então a prototipagem evolutiva é apenas
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uma delas. Por exemplo, prototipagem
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descartável é outra maneira de prototipagem na qual o protótipo é
41
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usado apenas para coletar requisitos, mas é descartado ao final
42
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da coleta de requisitos, ao invés de ser evoluído, como ocorre aqui.

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There are two more software process models that I want to cover, so
2
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bear with me. The first one is the Rational Unified software Process
3
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or IUP, which is s a very popular one based on UML.
4
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RUP works in an iterative way, which means it that it performs different
5
00:00:12,620 --> 00:00:16,360
iterations. And at each iteration, it performs four phases. So what I'm
6
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showing you here, is a high level view of the process. And I
7
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don't want you to focus on all the different details, because we
8
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will discuss these details later on, in a lesson that is actually dedicated
9
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to RUP. What I want to give you now, is just the
10
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gist of how this works. So, in each one of these four
11
00:00:31,020 --> 00:00:34,680
phases, which I'm going to describe in a second. We perform standard software
12
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engineering activities, the ones that we just discussed. And we do them
13
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to different extent, based on the phase in which we are.
14
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In particular, in the inception phase the work is mostly to sculpt
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the system. So basically figuring out what is the scope of the
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work, what is the scope of the project, what is the domain.
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So that we can be able to perform initial cost
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and budget estimates. The operational phase is the phase in which
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we focus on the domain analysis and define the basic architecture
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for the system. So this is a phase in which analysis
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and design are particularly paramount. Then there is a construction phase,
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which is where the bulk of the development actually occurs. And
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as you can see here, is where most of the implementation
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happens. And finally, the transition phase is the phase in which
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the system goes from development into production, so that
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it becomes available to users. And of course, this is
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the phase in which the other activities in software
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development become less relevant and deployment becomes the main one.

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Existem ainda dois outros processos de modelagem de software que eu gostaria de tratar, então
2
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me acompanhem. O primeiro é o Processo Unificado Racional
3
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ou RUP que é um dos mais populares baseados em UML.
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RUP opera de uma maneira iterativa, o que significa que ocorrem diversas
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iterações. E em cada iteração, são desenvolvidas quatro fases. Então o que eu
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estou lhe mostrando aqui, é uma vista panorâmica do processo. E eu
7
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não quero que você foque em todos os detalhes, porquê nós
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iremos discutir estes detalhes mais tarde, numa lição que é de fato dedicada
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ao RUP. O que eu quero lhe dar agora, é apenas a
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essência de como isso funciona. Então, em cada um dessas quatro
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fases, que eu irei descrever em breve... Nós desenvolvemos atividades
12
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de engenharia de software padrões, as que nós já discutimos. E nós as fazemos
13
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para diferentes amplitudes, baseadas na fase em que nos encontramos.
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Em particular, na fase de Concepção (Iniciação) o trabalho será sobretudo de esculpir
15
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o sistema. E basicamente ilustrando o escopo do
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trabalho, qual será o escopo do projeto, qual é o domínio.
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E então nós seremos capazes de saber o custo inicial
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e fazer um orçamento. A fase de Elaboração é a fase na qual
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nós focamos na análise de domínio e definimos a arquitetura de base
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do sistema. Então esta é a fase na qual a análise
21
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e o projeto se tornam proeminentes. E então ocorre a fase de Construção,
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na qual o desenvolvimento massivo de fato ocorre. E
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como você pode ver aqui, é onde a maior parte da implementação
24
00:01:11,640 --> 00:01:15,280
ocorre. E finalmente, a fase de Transição é a fase na qual
25
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o sistema passa do desenvolvimento para a produção, e então
26
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ele se torna disponível aos usuários. E é claro, esta é
27
00:01:20,380 --> 00:01:22,480
a fase na qual as outras atividades em desenvolvimento de
28
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software se tornam menos relevantes e a entrega se torna a principal.

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The next type of software process models that I
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want to discuss are Agile Software Development Processes. And this
3
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is a group of software development methods that are
4
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based on highly iterative and incremental development. And in particular,
5
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I'm going to discuss Test Driven Development or TDD. The
6
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space on the iteration of three main phases. In
7
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the first one that we mark as red, we
8
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write test cases that encode our requirements, and for which
9
00:00:25,350 --> 00:00:29,180
we haven't written code yet. And therefore, they will fail, obviously.
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So we're in this sort of red or fail phase. From
11
00:00:31,800 --> 00:00:34,830
this phase, we move to this phase, in which after we
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write the just enough code to make the test cases pass.
13
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We have a set of test cases that are all passing.
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And therefore, we can consider this as the green phase. We
15
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had enough code to make the test cases pass because the
16
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test cases encode our requirements. We have just written enough code to
17
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satisfy our requirements. When we do this over time though,
18
00:00:53,940 --> 00:00:57,080
what happens is that the structure of the code deteriorates, because
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we keep adding pieces. So that's why we have the
20
00:00:59,100 --> 00:01:02,540
first step, which is refactoring. In this step, we modify the
21
00:01:02,540 --> 00:01:05,724
code, and we will talk about refactoring extensively. We'll devote
22
00:01:05,724 --> 00:01:08,190
one lesson to it. We modify the code to make it
23
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more readable, more maintainable. In general, we modify to improve the
24
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design of the code. And after this phase, we will go
25
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back to writing more test cases for
26
00:01:17,670 --> 00:01:19,730
new requirements, write code that makes these
27
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test cases pass, and so on. So we'll continue to iterate among these phases. And
28
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also, in this case, we will talk
29
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about Agile Software Processes. And in particular,
30
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about extreme programming, or XP, and Scrum
31
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in more details, in minor course number four.

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O próximo tipo de modelos de processo para software que eu
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gostaria de discutir são os Processos Ágil de Desenvolvimento de Software. E este
3
00:00:06,300 --> 00:00:08,470
é um grupo de métodos de desenvolvimento de software que são
4
00:00:08,470 --> 00:00:12,620
baseados em desenvolvimento incremental e altamente iterativo. E em particular,
5
00:00:12,620 --> 00:00:16,000
eu irei discutir é o Desenvolvimento Orientado a Testes, ou TDD. O
6
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espaço na interação de três fases principais. Na
7
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primeira delas que iremos marcar em vermelho, nós
8
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escrevemos casos de teste que codificam nossos requisitos, e para os quais
9
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nós ainda não escrevemos o código. E obviamente, em seguida eles irão falhar.
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E então nós iremos cair neste tipo de fase vermelha, ou de falha. Desta
11
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fase, nós passamos para esta outra fase, a qual ocorre depois de nós
12
00:00:34,830 --> 00:00:37,970
escrevermos código suficiente para que os casos de teste aprovem.
13
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Nós temos um conjunto de casos de testes em que todos aprovaram.
14
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E em segunda, nós podemos considerar isso como a fase verde. Nós
15
00:00:43,810 --> 00:00:46,930
temos código suficiente para fazer os casos de teste aprovarem porquê os
16
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casos de teste codificam nossos requisitos. Nós escrevemos código suficiente para
17
00:00:50,520 --> 00:00:53,940
satisfazer nossos requisitos. Quando nós seguimos com isso ao longo do tempo,
18
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o que ocorre é que a estrutura do código deteriora, porquê
19
00:00:57,080 --> 00:00:59,100
nós continuamos adicionando partes! E esta é a razão de nós termos o
20
00:00:59,100 --> 00:01:02,540
primeiro passo, que é a Refatoração. Neste passo, nós modificamos o
21
00:01:02,540 --> 00:01:05,724
código, e nós iremos falar extensamente sobre refatoração. Nós iremos dedicar
22
00:01:05,724 --> 00:01:08,190
uma aula para isso. Nós modificamos o código para o tornar mais
23
00:01:08,190 --> 00:01:12,650
legível, mais fácil de dar manutenção. Em geral, nós modificamos para aprimorar a
24
00:01:12,650 --> 00:01:15,560
concepção do código. E depois desta fase, nós iremos tornar a
25
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escrever mais casos de teste para
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novos requisitos... escrever código que faz com que
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esses casos de teste aprovem e assim em diante. E então nós iremos continuar a iterar ao entre essas fases. E
28
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também, neste caso, nós iremos falar
29
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sobre Processos Ágil de Desenvolvimento de Software. E em particular, em
30
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Programação Extrema, ou XP e SCRUM
31
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mais detalhadamente, no subcurso número quatro.

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We just saw several software process models, and there
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are many, many more. And because these process models define
3
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the master plan for our project, the specific process
4
00:00:09,330 --> 00:00:12,220
model that we choose has as much influence over a
5
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project's success as any other major planning decision that
6
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we make. Therefore, it is very important that we pick
7
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the appropriate model for our development process. Picking an appropriate
8
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model can ensure the success of a project. On the
9
00:00:25,100 --> 00:00:27,830
contrary, if we choose the wrong model, that can be a
10
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constant source of problems and ultimately, it can make the project
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fail. So how can we choose the right model for a
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project? To be able to do so, we have to take into
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consideration many factors. In particular, we need to be aware of
14
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what level of understanding we have of the requirements. Do we understand
15
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all the requirements? Are we going to be able to collect all
16
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the requirements in advance, or collecting requirements is going to be hard and
17
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therefore, we might want to follow a process that is more flexible
18
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with that respect. Another important point is the expected lifetime of the
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project. Is this a quick project that we are putting together for
20
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a specific purpose or something that's going to last for for a number
21
00:01:03,100 --> 00:01:05,910
of years and that we're going to maintain over all those years?
22
00:01:05,910 --> 00:01:08,380
That's going to make a difference in the way we decide to develop
23
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that project. Also, what is the level of risk involved? Do we
24
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know the domain very well? Do we know exactly the technologies involved?
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Well, if so, we might go with a more traditional process. Otherwise,
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we might want to be more agile, more flexible. It is also
27
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very important to know the schedule constraints. How much time, how many
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resources do we have for this project? What is the expected interaction
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00:01:28,640 --> 00:01:31,870
with the management and the customer? In particular for this ladder, there
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are many processes that rely on the fact that there can be
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a continuous interaction with the customer. If that interaction is not there,
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there's no way we are going to be able to use these processes.
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Conversely, there are processes that don't require the presence of the customer
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at all, except for the initial phase and maybe some checking points and
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so if the customer is very inaccessible, we might want to follow
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one of those processes, instead of one of the more demanding ones in
37
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terms of customer's time. Finally, it is important to take into account
38
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the level of the expertise of the people involved. Do we have people
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that know the technologies that we're using? Do we know people that
40
00:02:02,730 --> 00:02:04,590
know a specific kind of process?
41
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Some processes require some specific expertise and
42
00:02:06,930 --> 00:02:09,320
we're not going to be able to follow that process if we don't
43
00:02:09,320 --> 00:02:12,410
have the right expertise. So we need to take into account all of
44
00:02:12,410 --> 00:02:15,570
these aspects, and sometimes more, in order to be able to make
45
00:02:15,570 --> 00:02:19,560
the right decision and pick the right software process model for our project.

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Now before we move to the last part of the lesson, let's
2
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have a quick quiz on software process models to make sure that
3
00:00:04,939 --> 00:00:06,640
we are all on the same page. So I am going to
4
00:00:06,640 --> 00:00:10,320
ask you two questions. The first question is which of the following models
5
00:00:10,320 --> 00:00:14,330
is most suitable to develop a software control system? And when you
6
00:00:14,330 --> 00:00:17,700
think about the software control system, you can think about for example
7
00:00:17,700 --> 00:00:21,150
the control system for the software in an airplane. Would you rather
8
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use a pure waterfall model? Test
9
00:00:22,860 --> 00:00:25,840
driven development? Or an evolutionary prototyping approach?

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This is the context in which, typically, a pure
2
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waterfall process will work well. Why? Well, because it's a
3
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context in which requirements are usually well understood. The
4
00:00:10,160 --> 00:00:13,020
domain is well understood, so that kind of system has
5
00:00:13,020 --> 00:00:15,900
been built many times before. And also, it's a
6
00:00:15,900 --> 00:00:19,510
system in which we don't expect requirements to change dramatically
7
00:00:19,510 --> 00:00:23,180
over time. Therefore, a waterfall model, in which we collect
8
00:00:23,180 --> 00:00:25,140
all the requirements at the beginning and then we move
9
00:00:25,140 --> 00:00:28,280
to the subsequent phases might be the most appropriate one. Probably
10
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we don't want to do evolutionary prototyping in the case of
11
00:00:30,800 --> 00:00:34,130
the control system for an airplane. Same thing holds for TDD,
12
00:00:34,130 --> 00:00:36,460
so we want to be a little more rigorous in those cases.

11
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The second question I want to ask you is which model is the most suitable if you
2
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expect mid-course corrections? Would you rather use a
3
00:00:06,660 --> 00:00:10,430
pure waterfall model, a spiral model, or evolutionary prototyping?

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As we just heard from Professor Bohem, software
2
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engineering is an important and critical discipline, concerned
3
00:00:05,970 --> 00:00:09,100
with cost effective software development. We also heard
4
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that this is based on a systematic approach
5
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that uses appropriate tools and techniques, operates under
6
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specific development constraints. And most importantly, follows a
7
00:00:18,130 --> 00:00:20,890
process. As we discussed in the previous lesson,
8
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the software development process contains fundamental activities, or phases.
9
00:00:25,770 --> 00:00:28,480
Since we will discuss several processes, I'm going to remind
10
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you what these phases are. We start with requirements
11
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engineering, followed by design,
12
00:00:33,630 --> 00:00:36,980
implementation, verification and validation, and
13
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finally maintenance. Note that we will revisit each of
14
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these phases and devote an entire lesson or more
15
00:00:43,940 --> 00:00:46,160
to each phase. So what I want to do next
16
00:00:46,160 --> 00:00:48,210
is simply to give you a quick overview of
17
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what these phases are. Note also that for now
18
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I will follow a very traditional take on these topics. Later on in the
19
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class we will see how things can change and did change over the years.

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In this case, I think about the spiral model,
2
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and evolutionary prototyping model will work. Definitely you don't want to
3
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have a pure water from water. Why? Well because it
4
00:00:09,110 --> 00:00:11,940
is very expensive with a pure waterfall model to make
5
00:00:11,940 --> 00:00:15,460
changes during the course of the project, especially changes
6
00:00:15,460 --> 00:00:17,860
that involve requirements. Why? Because we saw that it can
7
00:00:17,860 --> 00:00:20,440
be very expensive. Whereas with the spiral model, we saw
8
00:00:20,440 --> 00:00:25,220
that being iterative, we can actually make correction throughout development.
9
00:00:25,220 --> 00:00:28,840
Similarly, with evolutionary prototyping, we keep evolving our system
10
00:00:28,840 --> 00:00:32,170
based on the customer feedback. And therefore, if something changes,
11
00:00:32,170 --> 00:00:33,810
we will get feedback right away, and we will
12
00:00:33,810 --> 00:00:36,230
be able to adapt. So the key thing here is
13
00:00:36,230 --> 00:00:39,060
that anything that is iterative works better in the
14
00:00:39,060 --> 00:00:43,400
case of changing environments. So, situations in which your requirements,
15
00:00:43,400 --> 00:00:46,720
the situation, the project might change. Whereas waterfall is
16
00:00:46,720 --> 00:00:50,410
more appropriate for situations in which the requirements are stable,
17
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we know the domain, and possibly we also know the technologies involved.

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Now that we discussed softer process models, there is
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another important point I want to cover, because it's going to
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be useful for your projects. Documenting the activities carried out
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during the different phases of the softer lifecycle, is a
5
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very important task. The documents that we produce are used
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for different purposes, such as communicative details of the software
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systems. To difference the colors, ensure the correct implementation of
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the system, facilitate maintenance, and so on. There are standardized
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document that are provided by IEEE that you can use
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for this purpose. However, they're kind of heavyweight. So for the
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project in this class, when we will need them, I will
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rather use this lightweight documents. That we created by modifying the
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original ones, and make them a little simpler. In this,
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our documents are actually used, while teaching this class in the
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past. So they're well tested and work well for the kind
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of projects that we will perform. I provide information on how
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to access these documents in the class notes.

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Now we get to the final part of the lesson.
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And in this part I want to talk about well known,
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ineffective development practices. These practices, when followed, tend to lead
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to predictably bad results. So let's look at some examples of
5
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these classic mistakes. And we're going to start with mistakes
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involving people. And notice that there is a long list. So
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I'm going to discuss just a few of those mistakes.
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And I'm going to point you to more information on this
9
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topic in the class notes. And some of these mistakes are
10
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actually kind of entertaining. So I'll recommend that you look at
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the class notes and go in more depth in this list.
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So the first people mistake I want to mention is the
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one that I define, heroics. And this refers to too much
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emphasis on can do attitudes, so this idea that one person
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00:00:43,480 --> 00:00:46,330
by himself or by herself can do everything and can make
16
00:00:46,330 --> 00:00:50,422
the difference in the whole project. And unfortunately, this encourages extreme
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risk taking and discourages cooperation, which is plain bad for
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00:00:53,950 --> 00:00:56,610
the project. For example, it might force people not to
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00:00:56,610 --> 00:00:59,600
report schedule slips. It might force people to take on
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00:00:59,600 --> 00:01:02,210
on too much responsibility. And normally, and I saw it
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00:01:02,210 --> 00:01:05,600
happen many times, the final result is a failure. So
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what you want when you're developing a larger project, is
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actually to apply soft engineering principles. Have teams, have team
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work, and have cooperation among the different team members, without pointing
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too much on single individuals. Another classic mistake
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is to not create the right working environment. We
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all like to work in nice environments. And there
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is strong evidence that the working environments can play
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a big role in productivity. There is evidence
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that productivity increases when the workplace is nice, quiet,
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warm, and welcoming. Finally, some of the most important
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people relating mistakes are due to poor people management.
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For example, lack of leaderships, or leadership that is
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exercised using the wrong means in the wrong way, which
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can lead to very unhappy personnel and therefore, low
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productivity, or even people leaving teams. Another classic example of
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poor management is adding people to a project that
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is behind schedule, which never works. Why it doesn't work?
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Because these new people need to be brought up to
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speed, and that causes further delays rather than improving the
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00:02:06,520 --> 00:02:08,280
situation with the project schedule.

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Another type of classic mistakes are process-related mistakes. And also
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in this case, these kind of mistakes can be due
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to many reasons. And they are of many types. One
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typical example are scheduling issues, which are due to the fact
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of being unable to come up with a realistic schedule.
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So to have an overly optimistic schedule. And this can be
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because we underestimate the effort involved in different parts of
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the project. Because we overestimate the ability of the people involved.
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Because we overestimate the importance, for example, of the use
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of tools. But no matter what the reason is, the
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00:00:29,640 --> 00:00:32,840
result is typically that the projects end up being late,
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which is a very common situation. So this is somehow
13
00:00:35,580 --> 00:00:39,020
related to planning. And in general, planning is a fundamental
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00:00:39,020 --> 00:00:42,720
factor in software processes and in software development. Mistakes in
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00:00:42,720 --> 00:00:46,120
planning, such as insufficient planning or abandoning planning due to
16
00:00:46,120 --> 00:00:50,190
pressure, usually lead inexorably to failure. And speaking of failures,
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often there are unforeseen failures. Such as
18
00:00:53,040 --> 00:00:55,410
failures on the constructor's end, for example,
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that might lead to low quality or
20
00:00:56,920 --> 00:01:00,580
late deliverables, which ultimately affects the downstream activities.

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The third category of mistakes that I want to
2
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mention is product-related mistakes. A
3
00:00:04,970 --> 00:00:07,360
typical example of product-related mistake
4
00:00:07,360 --> 00:00:11,010
is gold plating of requirements. And what that means is
5
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basically is that it's very common for projects to have
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more requirements than they actually need. For example, marketing might
7
00:00:17,230 --> 00:00:19,090
want to add more features than the ones that are
8
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actually needed by the users. And of course having more
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requirements lengthens the project's schedule in a totally unnecessary way.
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Feature creep is another common mistake and consists in
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adding more and more features to a product that were
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not initially planned and are not really needed in most
13
00:00:34,650 --> 00:00:38,360
cases. And here there is evidence that the average project
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00:00:38,360 --> 00:00:41,180
experiences about a 25% growth in the number of
15
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features over its lifetime which can clearly highly effect The
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project schedule. Finally, if you're working on a project that
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strains the limits of computer science. For example, because you
18
00:00:50,760 --> 00:00:53,350
need to develop new algorithms for the project, or you have
19
00:00:53,350 --> 00:00:56,670
to use new techniques. Then that project might be more research than
20
00:00:56,670 --> 00:00:58,450
actual development. And therefore, it
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00:00:58,450 --> 00:01:00,600
should be managed accordingly. For example,
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by taking into account that you will have a highly unpredictable schedule.

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The final type of classic mistakes that I want
2
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to mention are technology related mistakes. One typical mistake
3
00:00:06,470 --> 00:00:09,990
in this context is the silver-bullet syndrome. What does
4
00:00:09,990 --> 00:00:13,340
that mean? Well, the silver-bullet syndrome refers to situations
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00:00:13,340 --> 00:00:15,900
in which there is too much reliance on the
6
00:00:15,900 --> 00:00:19,950
advertised benefits of some previously unused technology. For example,
7
00:00:19,950 --> 00:00:21,980
a new technology. And the problem here is that
8
00:00:21,980 --> 00:00:25,140
we cannot expect technology alone to solve our software
9
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development issues. So we should not rely too
10
00:00:27,810 --> 00:00:31,020
much on technology alone. Another typical mistake is to
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00:00:31,020 --> 00:00:33,700
switch or add tools in the middle of
12
00:00:33,700 --> 00:00:36,010
a project. And sometimes it can make sense to
13
00:00:36,010 --> 00:00:38,620
upgrade a tool, but introducing new tools, which
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00:00:38,620 --> 00:00:41,650
can have a steep learning curve, has almost always
15
00:00:41,650 --> 00:00:46,290
negative effects. Finally, a common unforgivable mistake is
16
00:00:46,290 --> 00:00:50,230
the lack of an automated version control system for
17
00:00:50,230 --> 00:00:53,480
your code and for your various artifacts. Manual and
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00:00:53,480 --> 00:00:56,700
ad hoc solutions are just not an option. It is
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00:00:56,700 --> 00:00:59,270
way too easy to make mistakes, use out of
20
00:00:59,270 --> 00:01:02,600
date versions, be unable to find a previous working version,
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and so on. I saw that happening many times,
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and it always results in a disaster. So be warned,
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00:01:08,640 --> 00:01:11,650
use a version control system and an automated one. And
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actually we will use version control systems in our projects.

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To conclude this lesson, I'm going to have a
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simple quiz and what I'm going to ask you
3
00:00:03,650 --> 00:00:07,950
is, which kind of mistake adding people to a late project is? And you can pick
4
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between a people mistake, a product mistake, a
5
00:00:10,540 --> 00:00:12,830
technology mistake, or maybe this is not a
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00:00:12,830 --> 00:00:16,800
mistake at all, it is actually okay to add people to a project that is late.

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You probably got this one right. The right answer is that
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this is a people mistake. And despite the fact that this is
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00:00:05,330 --> 00:00:07,550
an easy answer, I just want to make sure to stress
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once more. Because this is a very classic mistake. And one that
5
00:00:10,800 --> 00:00:14,070
can have dire consequences. You should never add people, to a
6
00:00:14,070 --> 00:00:18,430
late project. Because in 99.9% of the cases, that's only going to make
7
00:00:18,430 --> 00:00:21,390
things worse. Why? Because these people have to be brought up to
8
00:00:21,390 --> 00:00:25,590
speed, and also because having more also makes the communication more difficult,
9
00:00:25,590 --> 00:00:27,690
the meetings more difficult and so on. So in
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short, do not add people to a late project.

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So, let's start with requirements engineering, which is the
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field within software engineering that deals with establishing the
3
00:00:06,560 --> 00:00:09,400
needs of stakeholders that are to be solved by
4
00:00:09,400 --> 00:00:13,480
the software. So why is this phase so important?
5
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In general, the cost of correcting an error depends
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on the number of subsequent decisions that are based
7
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on it. Therefore, errors made in understanding requirements have
8
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the potential for greatest cost because many other design decisions
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00:00:25,670 --> 00:00:29,020
depend on them and many other follow up decisions depend on them.
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In fact, if we look at this diagram, which is again a
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qualitative diagram, where we have the cost of error correction over the
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00:00:35,210 --> 00:00:38,780
phase in which the error is discovered. We can see that if we
13
00:00:38,780 --> 00:00:42,420
discover an error in requirements it's going to cost us one. If
14
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we find it in in design it's going to cost us five and
15
00:00:45,020 --> 00:00:47,410
so on and so forth. And the cost grows dramatically as we
16
00:00:47,410 --> 00:00:50,960
go from the requirements phase to the maintenance phase. Why? Because of course
17
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if we discover a problem here we're left to undo a
18
00:00:53,092 --> 00:00:55,536
lot of the decision that we had made before to correct the
19
00:00:55,536 --> 00:00:58,019
error. Whereas if we find an error here we can correct it
20
00:00:58,019 --> 00:01:01,380
right away and we don't affect the subsequent phases. So how can
21
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we collect the right requirements. Traditional
22
00:01:03,540 --> 00:01:05,310
requirements in engineering does so through
23
00:01:05,310 --> 00:01:08,930
a set of steps. The first step is elicitation which is the
24
00:01:08,930 --> 00:01:12,840
collection of requirements from stake holders and other sources and can be
25
00:01:12,840 --> 00:01:15,890
done in a variety of ways, we will discuss some of them.
26
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The second is requirement analysis which involved the study and
27
00:01:19,280 --> 00:01:23,200
deeper understanding of the collective requirements. The third step is this
28
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specification of requirements, in which the collective requirements are suitably
29
00:01:26,760 --> 00:01:30,730
represented, organized and save so that they can be shared. Also
30
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in his case, there are many ways to do this,
31
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and we will see some of this ways when we talk
32
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about the requirements engineering in the dedicated lesson. Once the
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requirements have been specified, they can be validated to make sure
34
00:01:40,970 --> 00:01:44,420
that they're complete, consistent, no redundant and so on. So
35
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that they've satisfied a set of importance properties, for requirements.
36
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Finally, the fifth step is requirements management which accounts for
37
00:01:52,410 --> 00:01:56,100
changes to requirements during the lifetime of the project. And here
38
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I talked about steps, kind of giving the impression that
39
00:01:58,330 --> 00:02:01,310
we're just going from the first step to the fifth one
40
00:02:01,310 --> 00:02:03,300
and that this is sort of a linear process. In
41
00:02:03,300 --> 00:02:05,990
reality, as we will see, this is more of an iterative
42
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process in which will go and cover the different phases in an
43
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iterative fashion. We will discuss extensively
44
00:02:12,560 --> 00:02:15,453
requirements engineering in our second mini-course.

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Now let's discuss the next phase of software development,
2
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which is software design. Software design is the phase
3
00:00:06,080 --> 00:00:09,030
where software requirements are analyzed in order to produce
4
00:00:09,030 --> 00:00:11,500
a description of the internal structure and organization of
5
00:00:11,500 --> 00:00:13,900
the system. And this description will serve as the
6
00:00:13,900 --> 00:00:17,550
basis for the construction of the actual system. Traditionally,
7
00:00:17,550 --> 00:00:20,020
the software design phase consists of a series of
8
00:00:20,020 --> 00:00:25,360
design activities. Which normally consists of the architectural design phase,
9
00:00:25,360 --> 00:00:27,880
the abstract specification, interface design,
10
00:00:27,880 --> 00:00:30,010
component design, data structure and
11
00:00:30,010 --> 00:00:33,230
algorithm design. And notice that this is just a possible list
12
00:00:33,230 --> 00:00:35,820
of activities. But you can also characterize design activities in
13
00:00:35,820 --> 00:00:38,550
many different ways. And if you're looking at different books, and
14
00:00:38,550 --> 00:00:41,800
different sources, you might find different activities described. But the
15
00:00:41,800 --> 00:00:44,500
core idea, the important point is that we go from sort
16
00:00:44,500 --> 00:00:46,940
of a high-level view of the system, which is the
17
00:00:46,940 --> 00:00:50,770
architectural design, to a low-level view, which is the algorithm design.
18
00:00:50,770 --> 00:00:53,100
And these activities result in a set of design
19
00:00:53,100 --> 00:00:56,810
products, which describe various characteristics of the system. For
20
00:00:56,810 --> 00:00:59,770
example, they describe the architecture of the system, so
21
00:00:59,770 --> 00:01:02,890
how the system is decomposed and organized into components, the
22
00:01:02,890 --> 00:01:06,630
interfaces between these components. They also describe these components
23
00:01:06,630 --> 00:01:09,030
into a level of details that is suitable for
24
00:01:09,030 --> 00:01:12,470
allowing their construction. We will discuss the details of
25
00:01:12,470 --> 00:01:16,130
software design and talk extensively about these different actives and
26
00:01:16,130 --> 00:01:19,200
these different products in the third mini course of this class.

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After we have designed our system we can implement
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it. In the implementation phase what we do is basically
3
00:00:05,900 --> 00:00:08,410
taking care of realizing the design of the system
4
00:00:08,410 --> 00:00:11,920
that we just created and create an actual software system.
5
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There are four fundamental principles, four pillars that can
6
00:00:15,530 --> 00:00:18,470
affect the way in which software is constructed. The first
7
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one is the reduction of complexity. This aims to build
8
00:00:21,900 --> 00:00:25,160
software that is easier to understand and use. The second
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pillar is the anticipation of diversity. Which takes into
10
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account that software construction might change in various way over
11
00:00:31,720 --> 00:00:35,220
time. That is that software evolves. In many cases,
12
00:00:35,220 --> 00:00:38,270
it evolves in unexpected ways. And therefore, we have to
13
00:00:38,270 --> 00:00:41,680
be able to anticipate some of these changes. The
14
00:00:41,680 --> 00:00:45,390
third pillar is the structuring for validation. Also called design
15
00:00:45,390 --> 00:00:47,550
for testability. And what this means is that we
16
00:00:47,550 --> 00:00:50,760
want to build software so that it is easily testable
17
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during the subsequent validation and verification activities. Finally, and
18
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this is especially true within specific organizations and or
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domains. It is important that the software conforms to
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a set of internal or external standards. And some examples
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of this might be, for example, for internal standards,
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coding standards within an organization, or naming standards within an
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organization. As for external standards, if for example you
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are developing some medical software. There are some regulations and
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some standards that you have to adhere to in
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order for your software to be valid in that domain.

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After we have built our system, verification and validation
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is that phase of software development that aims to
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check that the software system meets its specification and
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00:00:09,000 --> 00:00:12,800
fulfills its intended purpose. More precisely, we can look
5
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at verification and validation independently. And validation is the
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activity that answers the question did we build the
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right system. Did we build the system that the
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customer wants? That will make the customer happy. Whereas verification
9
00:00:26,030 --> 00:00:28,730
answers a different question which is did we build the system
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right. So given a description of the system that is the one
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that we derived from the customer through the collection of requirements
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00:00:34,280 --> 00:00:37,130
and then design and so on, did we build a system that
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actually implements the specification that we defined? And when we look
14
00:00:41,150 --> 00:00:44,600
at verification there's many, many ways of doing verification and in fact
15
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in the mini course number four we will cover verification extensively. The
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00:00:48,430 --> 00:00:51,100
only thing I want to mention here is the fact that verification
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00:00:51,100 --> 00:00:54,110
can be performed at different levels. In particular, it can be
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performed at the unit level in which we test that the individual
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units work as a expected. Can be performed in the integration level
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in which what we test is the interaction between the different units.
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So we want to make sure that the different modules talk
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to each other in the right way. And finally, there is system
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testing in which we test the system as a whole and we
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want to make sure that all the system, all the different pieces
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of the system work together in the right
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way. And this is also the level at which
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then we will apply validation and some other
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testing techniques like stress testing or robustness testing and
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so on. And as I said I'm not going to say anything more on this topic because
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we will cover verification, and validation, and testing in
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particular in great details in mini course number four.

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As we discussed before software development efforts normally result
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in the delivery of a software product that satisfies
3
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the user requirements. So normally our software development organization
4
00:00:09,879 --> 00:00:13,127
will release this application to its final users, however, once
5
00:00:13,127 --> 00:00:16,090
the software is in operation many things can happen.
6
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So, for example, the environment might change. There might be
7
00:00:18,950 --> 00:00:21,940
new libraries. There might be new systems in which
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00:00:21,940 --> 00:00:25,070
our software has to operate. Or they may be future
9
00:00:25,070 --> 00:00:27,950
requests, so the users may find out that, guess what,
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00:00:27,950 --> 00:00:30,370
they want to do something different with the problem that
11
00:00:30,370 --> 00:00:32,835
we gave them. Or, again, and this is one of
12
00:00:32,835 --> 00:00:35,970
the most common occurrences, users might find problems with the
13
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software and may file bug reports and send the bug
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00:00:38,307 --> 00:00:42,090
reports back to the software developer. These are the reasons
15
00:00:42,090 --> 00:00:46,420
why software maintenance is a necessary phase in software development.
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Software maintenance is the activity that sustains the software product
17
00:00:50,190 --> 00:00:53,780
as it evolves throughout its life cycle, specifically
18
00:00:53,780 --> 00:00:57,350
in response to bug reports, feature requests and
19
00:00:57,350 --> 00:01:00,890
environment changes. Development organisations perform three kinds of
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maintenance activities: corrective maintenance to eliminate problems with the
21
00:01:04,450 --> 00:01:07,740
code, perfective maintenance to accommodate feature request, and
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00:01:07,740 --> 00:01:09,730
in some cases just to improve the software, for
23
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example, to make it more efficient, and finally,
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adaptive maintenance, to take care of the environment changes.
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00:01:15,650 --> 00:01:18,470
And after this activities have been performed, the software developer
26
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will produce a new version of the application, will release it
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and the cycle will continue through out the lifetime of
28
00:01:24,150 --> 00:01:27,440
the software. That's why maintenance is a fundamental activity and a
29
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very expensive one. And one of the reasons why maintenance
30
00:01:30,420 --> 00:01:34,080
is expensive, that I want to mention now, is regression testing.
31
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During maintenance every time you modify your application you have
32
00:01:37,180 --> 00:01:41,120
to regression test the application, where regression testing is the activity
33
00:01:41,120 --> 00:01:44,010
of retesting software after it has been modified to make sure
34
00:01:44,010 --> 00:01:47,320
that the changes you perform to the software work as expected,
35
00:01:47,320 --> 00:01:51,540
and that your changes did not introduce any unforseen effect. I'm
36
00:01:51,540 --> 00:01:53,630
pretty sure that you're familiar with the case of a new
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version of the software being released and just a couple of
38
00:01:56,000 --> 00:01:59,260
days later another version being released to fix some problems that
39
00:01:59,260 --> 00:02:02,000
occor with the new version. These problems is what we call
40
00:02:02,000 --> 00:02:04,640
regression errors and they're what regression
41
00:02:04,640 --> 00:02:06,560
testing targets and tries to eliminate
42
00:02:06,560 --> 00:02:09,240
before the new version of the software is released into the world.

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Okay. Now before we jump into the next
2
00:00:02,590 --> 00:00:04,780
topic, I just want to take a very quick and
3
00:00:04,780 --> 00:00:06,630
simple quiz just to make sure that you
4
00:00:06,630 --> 00:00:09,236
guys paid attention to what I just discussed. So
5
00:00:09,236 --> 00:00:10,820
I want to ask you what are the traditional
6
00:00:10,820 --> 00:00:13,200
software phases. Requirements engineering,
7
00:00:13,200 --> 00:00:16,079
design, abstraction, implementation, verification and
8
00:00:16,079 --> 00:00:18,020
validation. Or maybe design,
9
00:00:18,020 --> 00:00:20,830
optimization, implementation verification and validation
10
00:00:20,830 --> 00:00:22,448
and maintenance. Or requirements
11
00:00:22,448 --> 00:00:24,892
engineering, design, implementation, verification and
12
00:00:24,892 --> 00:00:26,290
validation, and maintenance.

15
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1
00:00:00,190 --> 00:00:04,000
And the answer is the third one. The traditional software phases which are the
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ones that we just discussed are requirements
3
00:00:05,960 --> 00:00:08,820
engineering, design, implementation, verification
4
00:00:08,820 --> 00:00:10,630
and validation, and maintenance.

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1
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Hi, and welcome to the first of several lessons on tools of the trade. I'm
2
00:00:07,470 --> 00:00:12,200
very excited about these lessons, because I believe that tools are a cornerstone
3
00:00:12,200 --> 00:00:14,390
of the software engineering discipline, and it
4
00:00:14,390 --> 00:00:17,570
is of paramount importance to know and
5
00:00:17,570 --> 00:00:20,330
use them. In this lesson, we will
6
00:00:20,330 --> 00:00:25,530
talk about integrated development environments, normally called IDEs.
7
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And these are software applications that support developers in many of their
8
00:00:29,780 --> 00:00:36,870
everyday tasks, such as writing, compiling, and debugging code. And to make the
9
00:00:36,870 --> 00:00:42,470
discussion more concrete we will focus on a specific IDE, Eclipse. We will
10
00:00:42,470 --> 00:00:47,250
first present Eclipse, and then get some hands-on experience through a demo.

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1
00:00:00,160 --> 00:00:02,750
As I just told you, tools are fundamental in
2
00:00:02,750 --> 00:00:06,050
software engineering. And I will stress this concept over and
3
00:00:06,050 --> 00:00:08,240
over, throughout the class. And today we're going to talk
4
00:00:08,240 --> 00:00:11,310
about a tool that is especially important, which is integrated
5
00:00:11,310 --> 00:00:15,060
development environments, or IDEs. And you're probably familiar with
6
00:00:15,060 --> 00:00:18,060
IDEs. So IDEs are environments that give you support for
7
00:00:18,060 --> 00:00:21,580
your development activities. For example, for writing code, editing code,
8
00:00:21,580 --> 00:00:25,320
compiling code, and so on. And we will focus specifically
9
00:00:25,320 --> 00:00:28,890
on one particular IDE, which is called Eclipse. And
10
00:00:28,890 --> 00:00:31,450
what I'm showing here is the two splash screens for
11
00:00:31,450 --> 00:00:35,350
two versions of eclipse, Helios and Kepler. Eclipse is an
12
00:00:35,350 --> 00:00:39,200
open, extensible development environment that was initially created by IBM
13
00:00:39,200 --> 00:00:41,510
and is now managed by the Eclipse Foundation. And of
14
00:00:41,510 --> 00:00:43,840
course, there are many other great IDEs such as for
15
00:00:43,840 --> 00:00:47,310
example, Microsoft Visual Studio or Netbeans. We will be using
16
00:00:47,310 --> 00:00:50,830
Eclipse because it is open and because it is multi-platform,
17
00:00:50,830 --> 00:00:52,390
which means that you can use Eclipse
18
00:00:52,390 --> 00:00:55,140
no matter what operating system we're using.
19
00:00:55,140 --> 00:00:59,030
So if we consider the most commonly used operating system, such as Mac
20
00:00:59,030 --> 00:01:02,780
OS, Windows, Linux, Eclipse runs on any
21
00:01:02,780 --> 00:01:04,769
of these environments. Therefore, no matter what
22
00:01:04,769 --> 00:01:06,490
you're using, you'll be able to install
23
00:01:06,490 --> 00:01:08,560
Eclipse, run Eclipse, and follow the class.

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So, now let's look in a little more detail to what is an IDE. An IDE is a
2
00:00:05,680 --> 00:00:09,790
software application that supports software developers in many of
3
00:00:09,790 --> 00:00:13,840
their everyday tasks. It has many useful features. Most IDEs
4
00:00:13,840 --> 00:00:16,790
provide views that can be used to navigate, project
5
00:00:16,790 --> 00:00:20,140
resources from different perspectives. For example, you might want to
6
00:00:20,140 --> 00:00:22,390
look at your code differently when you're writing code,
7
00:00:22,390 --> 00:00:25,950
and when you're debugging. They also normally provide an intelligent
8
00:00:25,950 --> 00:00:29,380
source code editor. For example, an editor that will allow you
9
00:00:29,380 --> 00:00:32,110
to browse the documentation when you're writing a code that
10
00:00:32,110 --> 00:00:35,780
uses a specific method, or that will give you autocompletion when
11
00:00:35,780 --> 00:00:37,990
you start writing the name of an object and you want to
12
00:00:37,990 --> 00:00:40,820
get the methods for that object. And all of these things
13
00:00:40,820 --> 00:00:43,420
can be very useful while you're developing and can save you a
14
00:00:43,420 --> 00:00:47,750
lot of time. Modern IDE's will also normally give you support for
15
00:00:47,750 --> 00:00:49,540
version control systems that then you
16
00:00:49,540 --> 00:00:52,490
can use for softer configuration management.
17
00:00:52,490 --> 00:00:55,720
And we're going to discuss in detail version control systems in
18
00:00:55,720 --> 00:00:58,380
the next tools of the trade lesson, and we're also
19
00:00:58,380 --> 00:01:01,135
going to see how it can be integrated within an IDE.
20
00:01:01,135 --> 00:01:04,730
IDEs also give you builders so they give you build automation
21
00:01:04,730 --> 00:01:08,070
tools, they give you runtime support. So that you can
22
00:01:08,070 --> 00:01:10,960
run your projects from within the IDE and, for example,
23
00:01:10,960 --> 00:01:14,550
observe some aspects of the execution. In addition to giving
24
00:01:14,550 --> 00:01:17,562
you support for the runtime, they give you support for testing.
25
00:01:17,562 --> 00:01:21,267
Many IDEs allow you to run tests from within
26
00:01:21,267 --> 00:01:23,520
the IDE and to check the results of the tests
27
00:01:23,520 --> 00:01:26,300
from within the IDE. Not only that. Normally, after you
28
00:01:26,300 --> 00:01:28,210
run your tests, if there are some test cases that
29
00:01:28,210 --> 00:01:31,500
fail, you can also use your IDEs to do debugging.
30
00:01:31,500 --> 00:01:35,620
Many IDEs include graphical debuggers. Debuggers will allow you to
31
00:01:35,620 --> 00:01:39,400
navigate through the code, set which points, stop and restart
32
00:01:39,400 --> 00:01:43,160
the execution. Inspect variables, and do all of the activities
33
00:01:43,160 --> 00:01:46,320
that help debugging. And, to help you be more efficient
34
00:01:46,320 --> 00:01:49,440
and more effective when you do debugging. And into addition to
35
00:01:49,440 --> 00:01:52,760
all these features that are listed here IDEs can normally provide
36
00:01:52,760 --> 00:01:56,650
you even more features through a mechanishm that is called plugins.

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In fact most IDEs are extensible through the use of
2
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plug-ins. And by the way, note that plug-ins might be
3
00:00:06,158 --> 00:00:09,326
called differently on different platforms. For example, if you're using
4
00:00:09,326 --> 00:00:12,970
a Microsoft Visual Studio, plug-ins are normally called add-ins, but
5
00:00:12,970 --> 00:00:15,598
the concept is more or less the same. So, what
6
00:00:15,598 --> 00:00:18,555
is a plug-in? Well, let's imagine our IDE to be
7
00:00:18,555 --> 00:00:22,320
this box. A plug-in is additional functionality that you can
8
00:00:22,320 --> 00:00:25,430
actually plug into this box so that this box starts
9
00:00:25,430 --> 00:00:28,830
offering more features to the user. For example, you
10
00:00:28,830 --> 00:00:32,850
can add to Eclipse the Checkstyle plug-in. Which, paraphrasing the
11
00:00:32,850 --> 00:00:35,950
Checkstyle website, helps you ensure that your Java code
12
00:00:35,950 --> 00:00:38,890
complies with a set of coding standards by inspecting the
13
00:00:38,890 --> 00:00:41,690
code and pointing out items that deviate from a
14
00:00:41,690 --> 00:00:44,870
defined set of coding rules. Again, this is a functionality
15
00:00:44,870 --> 00:00:47,330
the core of Eclipse doesn't have. You can add
16
00:00:47,330 --> 00:00:50,600
the Checkstyle plug-in, and this functionality will become available in
17
00:00:50,600 --> 00:00:54,840
the IDE. Another example of plug-in is the EGit plug-in which
18
00:00:54,840 --> 00:00:58,660
adds support for the Git version control system in Eclipse. And
19
00:00:58,660 --> 00:01:01,290
actually this is something that we'll cover in detail, we'll have
20
00:01:01,290 --> 00:01:04,150
a demo, and we will actually use it throughout the class, so
21
00:01:04,150 --> 00:01:07,018
I'm not going to say anything more about the EGit plug-in for
22
00:01:07,018 --> 00:01:09,300
now. But again, what the plug-in will do is to add
23
00:01:09,300 --> 00:01:13,220
the Git functionality to Eclipse. A functionality that is not in
24
00:01:13,220 --> 00:01:16,110
the core of Eclipse and that is available to the user after
25
00:01:16,110 --> 00:01:17,181
you add the plug-in.

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In the rest of this lesson we're going to look at eclipse and
2
00:00:02,550 --> 00:00:05,290
try to get more familiar with eclipse in a hands on manner
3
00:00:05,290 --> 00:00:07,550
through a demo. In the demo we will cover some of the
4
00:00:07,550 --> 00:00:11,040
basic aspects of eclipse like how to run eclipse, how to select
5
00:00:11,040 --> 00:00:14,400
their workspace, how to create a project, how to create the class
6
00:00:14,400 --> 00:00:18,240
within the project and so on. I'll also cover some more advanced
7
00:00:18,240 --> 00:00:21,610
aspects, like how to create builders, run your project within Eclipse, and
8
00:00:21,610 --> 00:00:25,800
how to use their Eclipse debugger. So let's get to the demo.
9
00:00:25,800 --> 00:00:28,220
So let's start Eclipse. Eclipse is going to ask me
10
00:00:28,220 --> 00:00:31,600
for the location of my workspace and in this
11
00:00:31,600 --> 00:00:34,530
case, I selected a suitable directory and you can
12
00:00:34,530 --> 00:00:38,480
also use that checkbox on the left to avoid Eclipse
13
00:00:38,480 --> 00:00:40,640
for asking you again about where to put the
14
00:00:40,640 --> 00:00:43,860
workspace. And the workspace is basically the place the
15
00:00:43,860 --> 00:00:48,310
directory. Where, Eclipse will place all of your projects.
16
00:00:48,310 --> 00:00:50,830
So, now when you start Eclipse, if it's the first
17
00:00:50,830 --> 00:00:53,480
time you might get this Welcome screen. It's not going to happen
18
00:00:53,480 --> 00:00:57,500
again on subsequent executions, but I just wanted to make sure
19
00:00:57,500 --> 00:01:00,210
that I covered all the bases. And so, whatcha want to
20
00:01:00,210 --> 00:01:03,360
do here is to basically go to the java perspective
21
00:01:03,360 --> 00:01:06,760
which you can do by clicking over there or you can
22
00:01:06,760 --> 00:01:09,240
also use the menus. So in this case we will have
23
00:01:09,240 --> 00:01:12,810
to go to Window, open Perspective, and if the Perspective is
24
00:01:12,810 --> 00:01:15,660
not here, you'll have to click on Other. And at this point,
25
00:01:15,660 --> 00:01:18,030
that you can click on Java Perspective, then you
26
00:01:18,030 --> 00:01:21,680
click okay. And the perspective is basically, the visual work
27
00:01:21,680 --> 00:01:24,810
space where you will be operating. So, after we selected
28
00:01:24,810 --> 00:01:29,350
perspective, we can actually close the welcome screen. And here,
29
00:01:29,350 --> 00:01:32,000
you see that you have this different areas and on
30
00:01:32,000 --> 00:01:34,930
the left You have the package explorer. This is the
31
00:01:34,930 --> 00:01:37,650
area where your packages will be, you've got a task list,
32
00:01:37,650 --> 00:01:41,280
and an outline on the right which we'll cover later.
33
00:01:41,280 --> 00:01:44,870
And then you have underneath, the bottom, a problems, java
34
00:01:44,870 --> 00:01:48,330
doc and declaration views and we will see some of
35
00:01:48,330 --> 00:01:51,320
these views in actions later. And here in the center
36
00:01:51,320 --> 00:01:54,290
you have the area. Which is called a code editor,
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which is where you'll be writing, editing, and modifying, basically,
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your code. This is where most of the action takes
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place. So let's start by creating a Java project. And
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00:02:03,140 --> 00:02:06,950
to do that we can use either the context menu, or
41
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you can just use the menu, select new Java project.
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00:02:09,560 --> 00:02:12,390
You'll be greeted by this, wizard, and. And at this
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00:02:12,390 --> 00:02:15,500
point in the wizard, you can select the name of
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your project. I'm just going to call it a very simple way
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my project. And I going to use the default location for
46
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the project, as you can see it will be placed
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00:02:24,070 --> 00:02:27,440
in the work space that I selected before. I'm going to
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also use the default. Java Runtime Environment, which is Java 1.7
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00:02:32,080 --> 00:02:36,250
in this case. I'm going to keep the selected default layout
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00:02:36,250 --> 00:02:39,120
and the, then I'm going to go to the next step. Here,
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we're first presented with the location of the source code for
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our project. The default is a directory SRC in my project
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and for the output file, the directory bin. So repeat, we're now
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00:02:49,320 --> 00:02:52,410
going to change that. Here in case you need other projects to
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build your own, then you can specify them here. Here we
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00:02:55,240 --> 00:02:57,570
are building a simple project, so there's no need for that.
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00:02:57,570 --> 00:03:00,890
And here we can specify which libraries our project requires. As
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you can see, the Java library's already specified. And you can
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also add other jars, which can even be External jars. And
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finally this is the tab that allows you to specify which
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part of you project. So how your project will be exported,
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so lets not worry about that for now. Lets click finish.
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00:03:16,760 --> 00:03:19,300
And as you can see here on the package explorer, my
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project appeared. So now we can open the project by clicking
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on the triangle right next to it, and as you can
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see there is the SRC directory, where my source code will go,
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and there's also an indication that we're using the JRE, so that's
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the Java system directory within our project. And this is just for people
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who are interested in what happens you know, under the hood. So
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if you don't care about that, you can just skip this part. So
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basically here I'm showing you how we can go to the directory
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where the project was created. We can see the bin and src directories.
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And there's also some other files here that you can
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see these 'dot' files that you will not normally, see. And
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those are kind of bookkeeping files. So these are files that
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contain information about your project and that are created automatically by
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Eclipse. And, for example, will have various indication about the
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configuration of the project, some settings and the class path for
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the project. And, as I said, you don't have to worry
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about this if you just want to go Eclipse as you're never
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going to mess with the command line.

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So now that we know, we saw what happens under
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the hood, and as I said, don't worry about it if
3
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you don't care about that part. Now we can go back
4
00:00:06,689 --> 00:00:09,850
to Eclipse, and we can start creating a package. A package
5
00:00:09,850 --> 00:00:13,125
is basically a way of organizing your classes into a
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hierarchy. In this case, I'm going to specify the package name as
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edu.gatech, which means that I'm creating really two packages, a package
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gatech inside package edu. And I can start creating classes inside
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00:00:25,480 --> 00:00:28,770
my packages. So here, I can use the contextual menu, select
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00:00:28,770 --> 00:00:32,055
New>Class, and I'll get another wizard that will allow me to
11
00:00:32,055 --> 00:00:35,160
specify the name of the class. I'm not very creative here,
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so I'm just going to call it Hello World. There's many other parameters
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you can set, and in particular, you can define whether you
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00:00:41,710 --> 00:00:45,450
want a main method in your class. Where having a main
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00:00:45,450 --> 00:00:48,460
method means that your class can be the main class in
16
00:00:48,460 --> 00:00:50,850
your project, can be the one that is run when you run
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00:00:50,850 --> 00:00:54,340
your project. After we click the button, the Finish button, we,
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00:00:54,340 --> 00:00:56,859
we get the class. So we also get template code for the
19
00:00:56,859 --> 00:00:59,604
class, as you can see here, so we go to the editor
20
00:00:59,604 --> 00:01:02,120
function, you can see that there is a to do. Where you
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00:01:02,120 --> 00:01:05,019
have to put your code, and here we are simply, basically printing,
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00:01:05,019 --> 00:01:08,370
you know, the typical first program. We just going to print Hello World
23
00:01:08,370 --> 00:01:11,180
in Java. And something you can note is that as we are
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typing, Eclipse gives us a auto complete suggestions, which is very helpful.
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For example, in case you don't remember the exact syntax,
26
00:01:19,650 --> 00:01:22,190
or the method, or you don't remember the parameters of the
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method. Which is, you know, often the case especially where you
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work with large libraries. So having that feature can really, really
29
00:01:27,590 --> 00:01:30,050
help you. So now if we want to run our code
30
00:01:30,050 --> 00:01:33,380
we can either click on the button up here, or we
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00:01:33,380 --> 00:01:37,960
can right-click in the Call window and select Run As Java
32
00:01:37,960 --> 00:01:41,370
Application. And if we do that, Eclipse will run our tool,
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and it will create, as you can see here, a console view that basically contains
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the textual output of my program. And as expected, the output is Hello World.

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So now that we have run our program, let's see what
2
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happens exactly when you run a program within Eclipse. And to
3
00:00:05,660 --> 00:00:08,410
do that I'm going to use the menu over here which is
4
00:00:08,410 --> 00:00:12,500
the Run menu and I'm going to select Run Configurations, and this
5
00:00:12,500 --> 00:00:15,190
brings up a window where you can change or run configurations.
6
00:00:15,190 --> 00:00:17,200
Well first of all, you can see that here on the
7
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left under Java application. Eclipse automatically created a Hello World run
8
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configuration for our program. And this is where you can configure
9
00:00:25,300 --> 00:00:28,370
the different parameters for your execution. For example,
10
00:00:28,370 --> 00:00:30,520
you can select the main class. So here
11
00:00:30,520 --> 00:00:34,745
it's, obviously, edu.gatech.HelloWorld. You can define different program
12
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arguments. We don't have any for now. You can
13
00:00:36,920 --> 00:00:39,480
also pass arguments to the virtual machine. You
14
00:00:39,480 --> 00:00:41,960
can define which Java runtime environment you want to
15
00:00:41,960 --> 00:00:47,720
use, Classpath and other environmental options. So let's
16
00:00:47,720 --> 00:00:50,650
now try to pass some arguments to our program.
17
00:00:50,650 --> 00:00:54,390
So for example here, I am just going to write George as
18
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a possible parameter. I say Apply so that modify the configuration and
19
00:00:58,450 --> 00:01:01,510
if i run the program of course, the output is not changing
20
00:01:01,510 --> 00:01:04,440
because my program does not use the argument. But, let's see if
21
00:01:04,440 --> 00:01:07,060
we do use the argument, what happens. So I'm going to slightly
22
00:01:07,060 --> 00:01:10,030
modify the final program so that now, instead of printing hello
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00:01:10,030 --> 00:01:13,420
world, it will print hello followed by the first argument that I
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00:01:13,420 --> 00:01:15,700
will pass to the program. And if I do that, and I
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00:01:15,700 --> 00:01:19,420
go and I run the program, what I get is exactly what I
26
00:01:19,420 --> 00:01:23,420
was expecting, which is Hello George. So this is the way in which you
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can pass arguments to your execution, which
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is something that might come in handy
29
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for some other projects. When you need to run some code with an argument.

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Now let's look at how we can do debugging within
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Eclipse. I created a new file called AddNumbers which I'm
3
00:00:06,240 --> 00:00:10,770
showing here. It takes two numbers, parses them into integers,
4
00:00:10,770 --> 00:00:14,870
adds them and prints the sum, supposedly, of the two numbers.
5
00:00:14,870 --> 00:00:17,450
Now we look at the run configuration for this program,
6
00:00:17,450 --> 00:00:19,670
and here you can see that we're passing two arguments,
7
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two and five, to the program. So now let's run
8
00:00:22,060 --> 00:00:25,468
our program and see what happens. And the result says that
9
00:00:25,468 --> 00:00:28,150
2 plus 5 is equal to 10, which is not
10
00:00:28,150 --> 00:00:31,030
exactly correct. So we need to debug our program. We
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00:00:31,030 --> 00:00:33,310
need to figure out what's wrong with the program, why
12
00:00:33,310 --> 00:00:37,140
the wrong result was, produced. So we're going to add a break
13
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point here by double-clicking here on the side of the
14
00:00:40,260 --> 00:00:42,940
code. And the break point is basically a place where I'm
15
00:00:42,940 --> 00:00:46,240
telling my debugger to stop during the execution because I
16
00:00:46,240 --> 00:00:50,750
want to inspect the state of the program. So to start
17
00:00:50,750 --> 00:00:54,690
debugging, we select Debug as Java Application from the Context
18
00:00:54,690 --> 00:00:58,170
menu, similar to what we were doing for running the program.
19
00:00:58,170 --> 00:01:00,190
And as you can see, this asks us whether we want
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00:01:00,190 --> 00:01:03,720
to pass to the debug perspective, which is a, a perspective
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specifically designed for debugging. We say yes. And as you
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see here, it shows us, it's like a different, set of
23
00:01:10,750 --> 00:01:13,310
views, so we can see the code down here with an
24
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indication of where the execution is. And of course the execution
25
00:01:16,100 --> 00:01:18,610
stopped at the break point, which is exactly where
26
00:01:18,610 --> 00:01:21,850
we told the debugger to stop. So let's look at
27
00:01:21,850 --> 00:01:24,400
some of the other views in this perspective. The view
28
00:01:24,400 --> 00:01:27,370
here on the right-hand side, for example, shows the variables
29
00:01:27,370 --> 00:01:30,720
in scope and the break points that are currently active
30
00:01:30,720 --> 00:01:33,240
for the debugging session. This is where the editor is
31
00:01:33,240 --> 00:01:36,710
at. The outline of the program and the console at
32
00:01:36,710 --> 00:01:41,520
the bottom. So now let's execute one line by clicking
33
00:01:41,520 --> 00:01:45,400
on the Step Over button here at the top, and this will
34
00:01:45,400 --> 00:01:49,150
execute the line that is currently highlighted and therefore it will move to
35
00:01:49,150 --> 00:01:51,500
the next line. And as you can see, one nice feature is that
36
00:01:51,500 --> 00:01:54,760
if I move the mouse over a variable, I can see the value
37
00:01:54,760 --> 00:01:57,710
of the variable. And the same thing I can do if I look
38
00:01:57,710 --> 00:02:00,690
at the variables windows here on the right. If I click it, it
39
00:02:00,690 --> 00:02:03,960
will tell me what is the value of the variable, and in case
40
00:02:03,960 --> 00:02:07,410
of more complex variables you can even expand it and get more details.
41
00:02:07,410 --> 00:02:10,870
So now let's step over another line by clicking again this button,
42
00:02:10,870 --> 00:02:13,180
and as you can see now we get to the line that
43
00:02:13,180 --> 00:02:16,410
is actually performing the sum, supposedly, so now let's do the same
44
00:02:16,410 --> 00:02:19,100
thing that we did before, and let's mouse over b, and we can
45
00:02:19,100 --> 00:02:22,150
see that the value of b is five, as expected. So now
46
00:02:22,150 --> 00:02:27,080
let's step over this line as well, and execute the actual sum. And
47
00:02:27,080 --> 00:02:29,730
doing the mouseover thing, we can see that the value of sum
48
00:02:29,730 --> 00:02:33,000
is ten, which is not right, of course. In fact, if we check
49
00:02:33,000 --> 00:02:35,590
a gain we can see that value of A is two. The
50
00:02:35,590 --> 00:02:39,130
value of B is five and therefore it's clear that there's something
51
00:02:39,130 --> 00:02:41,780
wrong going on here, and at this point we can notice that
52
00:02:41,780 --> 00:02:44,030
here we are doing multiplication instead
53
00:02:44,030 --> 00:02:46,010
of addition. And therefore that's what the
54
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error is. And this is clearly a very simple case. Right? A
55
00:02:49,260 --> 00:02:51,440
case in which probably you just needed to look at the code and
56
00:02:51,440 --> 00:02:54,150
you didn't need the debugger. But you probably got the idea right?
57
00:02:54,150 --> 00:02:58,055
So this can be extremely useful when you're debugging, when you're studying more
58
00:02:58,055 --> 00:03:01,533
complex programs. If you want to stop the debugger because you're
59
00:03:01,533 --> 00:03:04,557
done with your debugging session as in this case, you can
60
00:03:04,557 --> 00:03:07,518
either click here on the Terminate button or you can also
61
00:03:07,518 --> 00:03:11,109
just simply tell the debugger to continue the execution, to resume
62
00:03:11,109 --> 00:03:15,140
the execution until the program terminates naturally. So, in this case,
63
00:03:15,140 --> 00:03:17,520
we're going to click here just to show what happens. And what
64
00:03:17,520 --> 00:03:20,230
happens is that, you know, the execution will just continue until
65
00:03:20,230 --> 00:03:23,690
the program exits. So now let's say that we want to fix
66
00:03:23,690 --> 00:03:27,740
this problem that we just discovered. So we replace the multiplication
67
00:03:27,740 --> 00:03:30,600
with an addition, we save the program, and we execute the
68
00:03:30,600 --> 00:03:33,860
program again by clicking on this button. And at this point,
69
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unsurprisingly, we get the right result as shown in the console.

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Hi and welcome to the second lesson on tools of the trade. In the
2
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previous lesson we talked about IDEs. Integrated
3
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Development Environments and in particular we discussed
4
00:00:13,300 --> 00:00:16,460
the eclipse ID. Today we're going to
5
00:00:16,460 --> 00:00:19,780
talk about another fundamental type of tools
6
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in the software engineering arena. Version control
7
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systems. And these are also called, revision
8
00:00:26,140 --> 00:00:30,620
or source control systems. In particular, we will focus on a
9
00:00:30,620 --> 00:00:36,320
specific version control system called git. And as we did for eclipse,
10
00:00:36,320 --> 00:00:40,510
we will first present git from a conceptual standpoint. And then
11
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we will do a demo. To get some hands-on experience with GIT.

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One good representative of distributed version control systems, is
2
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GIT. A distributed version control system that was initially designed
3
00:00:08,320 --> 00:00:11,297
and developed by Linus Torvalds. I'm pretty sure you
4
00:00:11,297 --> 00:00:14,140
know who Linus Torvalds is. He's basically this guy who
5
00:00:14,140 --> 00:00:17,070
started and created the Linux operating system. And Linus
6
00:00:17,070 --> 00:00:20,140
was unhappy with the existing version control systems, and wanted
7
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a different one. He wanted to use it for maintaining
8
00:00:22,610 --> 00:00:25,330
the Linux kernel. In particular, he wanted one with some
9
00:00:25,330 --> 00:00:28,550
key characteristics. For example, the fact that it was distributed. He
10
00:00:28,550 --> 00:00:30,470
wanted it to be fast. He wanted it to have a
11
00:00:30,470 --> 00:00:33,660
simple design. And he wanted to have a strong support for
12
00:00:33,660 --> 00:00:37,370
parallel branches, because many people were contributing to the kernel at the
13
00:00:37,370 --> 00:00:41,620
same time. And therefore there many different branches of development. And
14
00:00:41,620 --> 00:00:45,120
finally, he wanted for the virtual control system to be able to
15
00:00:45,120 --> 00:00:48,070
handle large projects. As the Linux kernel is, and to do
16
00:00:48,070 --> 00:00:50,480
it in an efficient way. So if you want to get an idea
17
00:00:50,480 --> 00:00:54,210
of how popular GIT is today, there was a survey performed across the
18
00:00:54,210 --> 00:00:58,330
Eclipse IDE users, and it showed that in 2013 GIT was used by
19
00:00:58,330 --> 00:01:02,950
about 30% of the developers. So the, it had a 30% adoption rate.
20
00:01:02,950 --> 00:01:06,430
So we will use a GIT as a version control system for the class.

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As we did for Eclipse, and IDEs in general, we want
2
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to start a GIT in a hands on way. So we're going
3
00:00:05,133 --> 00:00:08,425
to start by seeing how to install GIT. And GIT is also
4
00:00:08,425 --> 00:00:12,440
multiplatform, so you can install it no matter what operating system you
5
00:00:12,440 --> 00:00:15,980
are using, unless of course you are using some arcane operating system.
6
00:00:15,980 --> 00:00:18,530
But if you are using Linux, for instance, there should be a
7
00:00:18,530 --> 00:00:22,608
package available that can install GIT for your specific distribution. If you're
8
00:00:22,608 --> 00:00:25,460
using Mac OS, GIT is also available as part of XCode and
9
00:00:25,460 --> 00:00:29,270
also as an independent package. Finally, if you're using Windows, GIT is
10
00:00:29,270 --> 00:00:33,090
available as a package with an installer. In general, you can go
11
00:00:33,090 --> 00:00:37,290
here to get information about how to get GIT, where to download
12
00:00:37,290 --> 00:00:39,975
it, how to install it, and so on. So, now what I'd
13
00:00:39,975 --> 00:00:42,312
like for you to do is to go, get GIT, install it,
14
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in case you don't have it installed already on your machine. And
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after that, you should be able to run GIT from the command
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line. And, that's exactly what we're going to do through a demo.

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But before jumping into the demo I would like
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to give a high level overview of the GIT workflow,
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which will help you better, following the demo. So let
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me start by representing four fundamental elements in the GIT
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workflow which are these four: the workspace which is your
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local directory. The index, also called the stage, and we'll
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see in a minute what the index is. Then, we
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have the local repository. We'll also refer to this as
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HEAD in the, when we explain the different commands
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and then, the word flow. And finally, the remote repository.
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If you consider a file in your work space it
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can be in three possible states. It can be committed
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which means that the data, the latest changes to the
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file are safely stored here. It could be modified, which
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is the case of the file being changed and no,
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none of these changes being saved to the local repository
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so locally modified or it can be staged. And
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stage means that the file is basically part of this
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index. And what that means, that it's been tagged
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to be considered in the next commit. And I know
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that this is not all 100% intuitive, so let's
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look at that again by considering the actual workflow and
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let's see what happens when you issue the different
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commands in git. So the first command that you normally
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run in case you, you're getting access to a remote
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repository, is the git clone command. And the git clone,
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followed by the url for that repository, will create a
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local copy of the repository in your workspace. And of
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course, you don't have to do this step if you're
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creating the repository yourself. The next command that we already
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saw is the command add. And what the command add
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does is to add a file that is in the
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workspace to this index. And we say that after that, the
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file is staged. So it's marked to be committed, but not
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yet committed. And here I'm just mentioning this minus u option.
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If you specify the minus u option, you will also consider deleted
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files File, but let's not get there for now, we'll talk
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about that when we do the demo. As I said, if you
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add the file, it just gets added to this index but
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is not actually committed, so what you need to do, is to
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commit the file, so when you execute git commit, all the
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files that are staged, that are released it here, their changes
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will be committed to the local repository. So your files, as
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I was saying, they can be in three states. They will
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go from the modified state to the stage state when you
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execute the app. And then from the stage state to the
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committed state when you perform a GIT Commit. Okay, so at
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this point your changes are safely stored in the local repository.
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Notice that you can also perform these two steps at
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once by executing a Commit -a. So if you have
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a set of modified files, and all these files are
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already part of the repository, so they're already known to diversion
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control system, you can simply execute a commit -a.
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And what the commit -a command will do, it
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will stage your file and then commit them. All at
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once. So it's a convenient shortcut. Of course, as I said,
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this will not work if the file is a new file.
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So if a file is a new file, you have to manually add
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it. Otherwise commit -a will just stage and commit at once.
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As we discussed when we looked at the diffence between centralized
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and decentralized version console system. We saw that in the case
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of the decentralized, there is a local repository which is this one.
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And then you have to explicitly push your changes to a remote
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repository, and this is exactly what the git push command does. It pushes
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your changes that are in the local repository to the remote repository
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so at this point all of your changes will be
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visible to anyone who has access to the remote repository.
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Now, let's see the opposite flow so how does it
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work when you're actually getting files from the repository instead
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of committing files to the repository. So the first command
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I want to mention is the get fetch command and
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what the get fetch command does is to get files from
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the remote repositories to your local repository, but not yet to
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your working directory. And we will see what is the usefullness of
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doing this operation. Of having the files all in the local respository,
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but not in your local directory. So, what that means, just to
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make sure that we're on the same page. Is that you
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will not see these files when you workspace. You will still have
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your local files here. So this is sort of a physical distinction.
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In order to get your data files from the local repositories to
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your workspace you have to issue another command. Which is
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the command git merge. Git merge will take the changes in
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local repository and get them to your local workspace. So at
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this point your files will be updated. To what is in
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the remote reposity. Or at least what was in the
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remote reposity at the time of the fetch. SImilarly to what
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happened for the add and commit. There's a shortcut which is
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the command git pull. So in case you want to get
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the changes directly. To your work space with a single
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command, you can issue a git pull command and what will
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happen, is that the changes will get collected from the
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remote repository and they will go to your local repository and
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to your work space, at once. So this has the
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same affect as performing a git fetch and a git merge.
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So if we can do everything in one command, why,
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why we want to fetch and berch as two separate operations?
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So one of the reason is because this allows us
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to compare files before we actually get the latest version
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of the files. In particular, I can run the command
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git diff head to get the difference between my local files,
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the files in my working directory, and the files in
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my local repository. So what I can do, I can
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fetch the files from the remote repository, and once I
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fetch these files. I can run a git diff head and
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check what the differences are. And based on the differences decide
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whether I want to merge or not. So while we are talking about
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git diff, there is something else that you can use with the
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diff command. So what you can do, you can run git diff
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without further specifying head. In this case, what the command tell you
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is the difference between the files that you have in your work
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space and the ones that are staged for a commit. So basically,
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what it will be telling you, is that what you could still
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add to the stage for the further commit, and that you
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haven't already. So what local changes will not make it to the
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next commit, basically. And this you can use, for example, as
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a sanity check before doing a commit to make sure all the
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local changes that you have, and that you want to commit,
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are actually staged and therefore will be considered. So now we will
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cover all of the commands that we saw here. In our practical
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demo. But please feel free to refer back to this Git Workflow
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to get a kind of a high level vision. Or maybe you want to keep it next to
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you, because this really gives you the overall structure
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and the overall view of what happens when you
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run the different commands. And it also helps you
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visualize The different elements that are relevant when you're
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using GIT. So the workspace, once more, the index
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or stage, the local repository, and the remote repository.

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Now that we saw some of the git basic
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functionalities in practice, let's go a step further. If
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you remember I mentioned before that many of these
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version control systems are actually integrated into IDE's. So
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what were going to look at next is what happens
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if we put together git and eclipse. And the
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result is egit, or EGit is a plug in
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for the eclipse IDE that adds git functionality to eclipse.
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So let's see how that works in practice. So
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support for git is available in many IDE's including
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Eclipse. And if you want to get github
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for Eclipse, you should go to eclipse.github.com and you can
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download the plugin. So this bring us to the
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plugin page and you can use the provided URL
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and directions to install the plugin. In this case
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we're going to copy this address. So we're going to
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Eclipse, Help, Install new software. We can click on Add
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to add a new site from which to get software. We
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paste the location that we just copied here. And we
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can give it a descriptive name. In this case I'll just
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call it Eclipse Git plugin. Then when I click okay,
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Eclipse will go, and look for plugins. And as you can
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see, there are two options. We can select both of them,
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and click on next. You can see that the Eclipse identified
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a few dependencies. You can click next and accept them. You can
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accept the terms and conditions for the plug in, and then just
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finish. And at this point, Eclipse will install the plugin, which might
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take a little bit of time. So we're just going to speed it up.
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And when Eclipse is done, you will get this prompt that will
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tell you that you need to restart Eclipse for the plugin to
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be actually installed. And at this point, you want to click yes. And
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when Eclipse restarts. You'll have your plugin. We're going to go to the git
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repository perspective that we can select here. And when we click
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OK, you can see that our display will change. And since
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we don't have any repository yet, we are provided with the
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possibility of adding an existing local git repository, cloning a git repository
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or creating a new local git repository. We're going to add an
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existing local repository. This is the one that we created earlier,
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so we'll select it and click finish, and you can see
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that my project is now added to this set of git repositories.
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Now let's check out the project from the repository by selecting import
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project. And here you can import something as an existing project, you
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can use a new project wizard, and in this case I chose
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the option of importing as a general project. Then I click Next and
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as you can see, I have the project name up there and
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I can click Finish. So now, if I go to the resource perspective
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by clicking here, I can see that the project has been added
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to my set of projects. And I can see all the files within
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the project, particularly, if I click on the README, you can see
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that we have the Readme file that we created before. Same thing for
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the test file. One thing I can do at this point, it
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to execute different git commands, perform
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different git operations by using the team
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submenu in the contactual menu. And here there are several things
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I can do including some advanced commands. And just to give it a
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shot, I am going to try to click show local history, and this
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shows the history of the file. For example it shows the author and
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it shows when he was created, when he was authored. Lets make
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some changes to this file by adding some new content. Okay. I saved
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the file and now I can see that error that indicates that my
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file was locally changed. So now if I go to the team menu,
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you can see that I have the option to add to the index,
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to stage the file. And now I got this new label that star
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that shows the files added to the index. And now at this point,
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I can go to the team menu again and I can actually commit
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the file by selecting the corresponding entry. This allows me to enter
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the commit message, exactly in the same way which I could do
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that from the command line with the textual editor. And after I
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put the comment there, I can actually commit. And now if we
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look at the history view, we can see here that we have
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a new version for the file that we just modified. And we
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can also see the commit comment. And, at this point, if we
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had remote repository we could push our changes to that remote repository
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as well. Again, using the team submenu and
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the contextual menu. And, speaking of remote repositories, what we
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are going to see next is how to use GitHub
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repositories which are remote repositories that are hosted on GitHub.

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In the interview that we did at the beginning of the class,
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we talked with John about GitHub, where GitHub is a Git hosting website, and
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John told you all about it. For this class, we will be
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using GitHub as our Git hosting. Let's see how GitHub works in practice and
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let's see some of the common features offered by GitHub.
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This is what we'll do in the third part of this Git demo. What I'm showing here
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is the GitHub website and as I said, GitHub is a Git hosting website and
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you can create an account on GitHub by simply signing up on the website. And
9
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because we already have an account that we're simply going to sign in
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to see what kind of functionality GitHub offers. And we're going to specify our
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username and password. And as you can see on the GitHub website,
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you can use this menu up on the right to create a new repository or
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change the account settings. Let's click on our user profile. And
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here we can see some statistics for our user. For
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example, we can see statistic about our contributions and our repositories. So
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now if we go to the Repositories view, we can create a new repository.
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We give it a name. Let's call it myrepo. We can provide the description for
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the repository. If we want, we can initialize the repository by adding a README
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file. And even though we are not doing it right now, if you can see up here,
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you can also add a license here on the right and it allows you
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to choose from a set of predefined licenses. And you can also a .gitignore file,
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which, in case you don't know what that is, it's a very convenient file that
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will automatically exclude from the repositories file that should not be added.
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So if you remember in the lesson we said there are things that you should not
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add to the repositories. For example, derived files. So
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here, using this menu, you can pick the type of project that you have.
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For example, Java project or PHP project or many other kinds of projects. And
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the GitHub will automatically add that file for you.
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But let's skip that for now and simply create our repository. And
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that creates a repository that contains the README file because that's what we
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decided to do. And it also allows you to edit the README file by clicking on it.
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It will bring up an editor and here you can write, you know,
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for example, initial readme for your project. Then you can add your
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commit message up there and then you can commit the changes to your README file.
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The site also provides many other features, like, for example, creating issues,
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pull requests, adding and editing a wiki, and also, you know,
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defining other characteristics and settings for the repository. Now, if we go to
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the repository, you can see that we also get the HTTPS link for the repository.
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So this is the URL that you can use to clone your repository. If you remember,
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with a git clone command, that's the URL that you can specify. So
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let's try to do that and clone that repository. So we're going to copy this URL.
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To do that, we're going to execute git clone and specify the URL that we
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just copied. And you can see that the project was created, was cloned locally.
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And if we go under myrepo, which is the name of the repository, you can see that
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the README file that we created on GitHub is here. So if we create a new file,
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which we're going to call again, newFile just to be clear. And then we
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can add it, commit it, specifying as usual a commit message. So at this point,
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we can push our locked out changes to the remote GitHub repository. And
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because the GitHub repository is password protected,
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we have to specify our login and password. And of course, if you
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pass the wrong password, GitHub is not going to let you in. So let's try again.
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Let's try to get the password right this time. I'm going to specify again,
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my login and my password. At this point, the push is successful and
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my changes are actually pushed to the master, which is the GitHub repository.
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To double check that, let's go back to the GitHub repository and as you can see,
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that the file that we added, newFile, is there as expected. And of course,
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there's many more things that you can do on the GitHub website, so
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I strongly encourage you to go and try out things. But
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the key message here is that the GitHub is a Git hosting website where you
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can get an account and create your remote repositories.

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Now that we are done with our demo, I just want
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to go through a quick GIT recap to remind you of the
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main commands that we saw, and what they do. And you can
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also use these as sort of a reference when you work with
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GIT. And by the way, if you look around and you do
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a search, you can see that there's tons of examples on the
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web of GitHub tutorials, videos, examples, manuals. So feel free to
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explore. And I'm actually going to put some references to tutorials and
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videos that I found particularly useful in the notes for the class.

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So, let me start by recapping some of the operations that
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we can perform on local repositories. I'm just going to list them
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here and go through them by separating them into three main
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categories. The first one is commands that, to create a repository and
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notice that not all of these are git commands, that for
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example, to create the repository, we would normally want to. Create a
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directory, which is exactly what we did in our demo. We want
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to go to that directory and then execute the git init statement,
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which initializes that directory as a git repository. The second
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category includes commands that we'll use to modify the content of
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the repository. We saw that we can use git add
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to add a specific file or a complete directory to our
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index. So to the list of files that will be
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committed, that will be considered in the next commit. Then we
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can use commit to actually commit the changes that we
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made to those files to our local repository, and we can
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also use git move and git rm or git remove
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to move files around and to remove files. Finally, the
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third category is the category of commands that we can
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use to inspect the concrete repository. And this set includes git
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log, that we can use to see the log of
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the repository, git status, that can give us important information
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about the status of the file center repository. Git diff,
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that we can use to see the differences between for example,
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our local files. And the remote files. And finally git
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show, that will show us information about our last commit. What
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we committed, what were the changes and so on. And again,
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we saw most or all of these commands in our demo.
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So let me also remind you of a possible workflow. Which
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again, we already saw but it's always good to go through
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it once more. And remember that this is just an example.
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It's just a possible workflow. You can do many different things,
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you can have many different workflows with git. This is just
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up to illustrate some of the things that you can do. So,
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you might do some local editing. Execute git status to see what
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files you changed. Then you might run a git diff on the
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files to see what are these changes. And then you can run
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git commit -a to commit your changes. And in case you
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want to specify the commit message right away without having to go
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through an editor, you can also add the -m parameter and
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specify the message here on the same line.

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SImilarly, let's go through some commands that you can run on
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remote repositories. First command is the command to copy a repository,
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which is git clone in which you get a remote repository and you make a lot of
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copy in your working directory. The repository can be specified as a URL.
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It can be a local file, it can be specified using the HTTP or
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the SSH protocol, and there's also other ways to do it.
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This creates a complete local copy of the repository, as it says, and links it
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to the remote repository, which is what is called the origin. And if you want,
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you could also actually link to the repository, later. Then the normal way of
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receiving changes from a repository is to perform a git pull command. And we saw
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that you can also perform the same operation through two commands, get fetch and
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git merge. In case you want to inspect the changes before actually merging them,
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before actually getting them in your local copy. And
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if you want to send changes that you have in your local repository to
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a remote repository, you will use the git push command.

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This is ultimately pretty simple. All you need to do is visit
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github.com/join and set up a free GitHub account. If you already have a GitHub,
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account you can sign in using your existing account. If you want to
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use a separate identity for the class, feel free to set up a second one.

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Na verdade é muito simples.
Só tens que ir a
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github.com/join e criar uma conta grátis
no GitHub. Se já tiveres uma conta GitHub,
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podes entrar com a tua conta.
Se quiseres
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criar uma diferente para o curso,
podes criar uma segunda sem problemas.

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>> And I thought that the best way to break the ice on version
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control systems and Git and some other
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related concepts was to interview John Britton who
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works with GitHub. So let's go and see what John has to say about
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Git, about version control systems in general,
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and about GitHub. John is in Tapei, if I'm not wrong.
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>> That's correct.
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>> Okay so we're, you know we couldn't
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go there so we're interviewing him remotely. And I
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want, I just want to thank you so much and John for agreeing to talk to us.
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>> Thank you very much for having me it was my pleasure.
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>> And, I'm just going to ask, a few
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general questions because John is an expert on,
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Git and GitHub. John is a developer and
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a community builder is active in both the
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open source and the open education areas. And
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as an educational liaison we have, is working
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to improve Computer Science education by bringing the
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principles of open source into the classroom. And
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I'm going to start with an general question,
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which is what is a version control system?
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>> So, a version control system is
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a tool that software developers use. Anybody
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who's doing you know, working with digital
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assets, digital projects can also use for
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keeping track of, you know, revisions of your project, and when I say revisions, I
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mean essentially snapshots of your project over time. So you can imagine doing
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some work and then every so often, be it, every couple of
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hours, every couple of days, saving a permanent snapshot of your project.
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>> Why is this useful? I understand that
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it is nice to take a snapshot of your
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project, but what did you do with the
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snapshot afterwards? I think the most immediately obvious benefit
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to having snapshots of your project to keeping
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revisions is that you can go back. If you
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have ever worked on a project and got to
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a point where you solved a bunch of your
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problems, and there is just one more step to do. And
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you start working on trying to solve that last step, and
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you break things, you make it worse then it was an
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hour ago. At that point its easier to just go back
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to what you had then trying to figure out what you
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broke. So you can always go back in time, and the
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other big one is being able to collaborate with multiple people,
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so its pretty seldom these days that you. Work on a production
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totally on your own. It's most common to work in, you
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know, in teams and small groups. And so, using a revision
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control system allows you to collaborate with other people. And make
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sure that you don't step on each other's toes as you're working.
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>> Alright, that's great, because those are exactly some of the
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topics that we're going to cover in the lesson. And so since we're
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going to talk about the specifics of version control system which is
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Git and you're definitely an expert in, in Git. So what would
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you say is specifically special about Git? What characterizes it
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and how does it compare to other version control systems.
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>> So if any of you have used version control systems before, you
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may have heard of something like subversion, CVS, or maybe a commercial solution
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like ProForce. I think the main important characteristics of Git are first that
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it's open source. And the second,
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that it's a distributed version control system.
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So what that means, the distributed version
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control system is essentially a system for tracking
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revisions of your software that doesn't have any
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central repository. So the biggest characteristic is that
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I can do my work and you can also work on the same project at
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the same time without communicating with each other
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and without communicating to a central system.
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>> Okay, great. And so now that we saw what Git is, what is
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GitHub and how does it fit into
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this picture of the distributed, revision control system?
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>> So GitHub is, the world's largest code host, and we essentially have a
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website where you can collaborate with people
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when you're writing code. There's two ways you
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can use GitHub. You can use it publicly for open source and you can use
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it in private within your team, or your company, or within your class. And, Git
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Hub started out just as a way to host your Git repositories. But it's
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actually grown into quite a bit more. It's
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an entire collaboration system around your code.
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>> How many users do you have?
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>> I would say that we're approaching five million.
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I don't know the exact number. We're definitely more
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than four million right now. But yeah, I'd say
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somewhere, somewhere close to between four and five million.
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>> So that's a lot space I'd guess. Terabytes of disk
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space, I would imagine.
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>> There are a lot of GIT repositories on, on our servers.
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>> Something else you want to say? I
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guess that the when taking about GitHub there's one
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thing that you kind of can't leave out and
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that's that's a feature that's called a pull request.
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So when you're using GitHub, you can share
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your Git repository, do some work, and actually do
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do a code review. Of proposed changes which
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is what we call a pull request on github.com.
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Essentially what it lets you do is have a discussion
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about a set of proposed changes and leave feedback in
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line with the code. You could say for example, this
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method needs to be re-factored or I think I found if
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off by one error here, just different kinds of feedback
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so that before you totally integrate some proposed changes. You have,
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kind of a conversation about what your code. And I
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think that's really valuable when you are working in a team.
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>> Thank you, John, that was very informative and
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thanks again for taking the time to talk to us.
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>> No problem, thanks for having me. I'll talk to you soon.
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>> Let's thank again John for enlightening us
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on some aspects of version control systems, Git and
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GitHub. And now, let's go over some of the
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topics that we discussed with John to recap them.

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So first of all, what is a version
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control system? A version control system or VCS,
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is a system that allows you to manage
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multiple revisions of the same unit of information. For
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example of documents, of source files or any
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other item of that sort. And as the graphical
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depiction shows, a VCS allows a multiple actors.
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Here we have four, to cooperate and share files.
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Now, let's drill into this concept in a little
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more detail. And let's do that by discussing why
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is VCS useful, especially in the context of software
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engineering and of software development. So first of all,
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using a version control system enforces discipline, because it
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manages the process by which the control of items
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passes from one person to another. Another important aspect
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of VCS is that it allows you for archiving versions.
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So you can store subsequent versions of source controlled
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items into a VCS. And not only you can
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store versions, you can also maintain a lot of
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interesting and important historical information
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about these versions. For example,
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a VCL will store information such as, who is
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the author for this specific version stored in the system.
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Or, for another example, on what day and what
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time that version was stored. And a lot of other
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interesting information about the specific version of the
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item. Information that you can then retrieve and for
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example, use to compare versions. Obviously, the fact of
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having a central repository in which all these items
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are stored enables collaboration, so people can more easily
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share data, share files, share documents through the use
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of VCS. And I'm sure that you all had
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the experience of deleting a file by mistake or
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modifying a file in the wrong way, or in the
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most common case of changing something in your code for instance.
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And breaking something and not being able to go back
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to a version that was working. Not remembering, for example, what
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is that you changed that broke the code. In all
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these cases a version control system can be extremely useful because
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it will allow you to recover from this accidental deletions
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or edits. And for example, to go back of yesterdays version
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that was working perfectly, and also to compare, for example, yesterdays
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version with today version and see what is that you changed.
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Finally, a version control system will normally also allow you to
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conserve and save disk space on both the source control client
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and on the server. Why? Well, for instance because it's centralizing
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the management of the version. So instead of having many copies
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spread around, you'll have only one central point where these copies
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are stored or a few points where these copies are stored.
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In addition, version control system often
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uses efficient algorithms to store these changes.
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And therefore, you can keep many versions without taking up too much space.

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usth/ICT2.7/P1L4 Version Control Subtitles/4 - VCS Quiz - lang_en_vs4.srt
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Now before we continue, and we look at more details
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of version control systems, I want to ask you a
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quick question about VCS. I want to know whether you
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have used a version control system before, and if so,
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which one or which ones. I'm going to list in
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here some of the most commonly used version control systems,
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like CVS, Subversion, GIT, and I'm also allowing you to
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specify other VCS in case you have used different ones.

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usth/ICT2.7/P1L4 Version Control Subtitles/5 - VCS Quiz Solution - lang_en_vs7.srt
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And of course there's no right answer for this. I just wanted to collect some
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statistics. To see what kind of previous
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experience you have with this kind of systems.

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usth/ICT2.7/P1L4 Version Control Subtitles/6 - Essential Actions - lang_en_vs5.srt
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What I want to do next, is to look at how
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version control systems actually work. We saw what they are. We
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saw why they are useful. But how do they actually work?
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And we're going to do that by starting from some essential
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actions that version control systems perform. The first one is the
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addition of files. So, when you use a version control system,
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you can add a file to the repository. And at that
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point the file will be accessible to other people who have access
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to the repository. And now the fundamental action is commit.
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When you change a file, a file that is already in
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the repository, when you make some local changes to a
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file that is already in the repository, you want then to
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commit your changes to the central repository, so they can
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become visible to all of the other users on the repository. Finally,
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another fundamental action is the action of updating a file. If
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we have a repository and someone else can modify the files
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in the repository, I want to be able to get
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the changes that other people made to the files in the
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repository. And these are just three of the basic actions, but
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there are many, many more. And we'll see several of those.

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Before looking at additional actions, though, I would like to
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see what is the basic workflow in a version control system
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using the three actions that we just saw. And to
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do that I'm going to use two of our friends, Brad
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and Janet. So we have Janet here, Brad, and a
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VCS that they are using. Now imagine that Janet creates a
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file called foo.txt and puts some information in the file.
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At that point she might want to add the file to
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the repository and to commit it so that her changes
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and the file get to the central repository. And when she
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adds and commit, that's exactly what will happen, in foo
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will be come available here, and will be accessible to the
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other users. In this case it'll be accessible to Brad.
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If Brett were to run an update command, what will happen
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is that the file foo.txt will be copied on the local
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work space of Brad and Brad will be able to access
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the file. At this point Brad might want to modify
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the file, for example add something to this existing file.
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After doing that, he also may want to share the
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updated file with Janet. To do that, he will commit the
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file and the result will be exactly the same of
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when Janet committed her file. That the updated file will
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be sent to the repository and the repository will store
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that information and make it available for other users. So now,
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if Janet performs an update, she will get the
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new version of foo.txt with the additional information that was
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added by Brad. And we will see all of this
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in action in our next demo in a few minutes.

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usth/ICT2.7/P1L4 Version Control Subtitles/8 - "Don'ts" in VCS - lang_en_vs5.srt
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Before getting to the demo, I want to say a few
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more things. In particular, I discuss the main don'ts in VCS. So,
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what are some things that you don't want to do, and
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you should not do, when you're using a version control system? And
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I'm going to mention two, in particular, because these are two
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that I witnessed several times when I was teaching this class and
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also when collaborating with other people. So, there are two kinds
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of resources that you don't want to add to a VCS normally.
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One is derived files. For example an executable that is
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derived by compiling a set of source files, where the
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source files all already in the repository. At that point,
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there is no reason to also add the executable file in
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the repository. So in general, any executable file should not
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be added to repository. The second class of files that I
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want to mention is these bulky binary files. If you
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have one such file, it is normally not a good idea
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to store them under a version control system, to store them
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in the repository. There might be exceptions to these rules, but in
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general, these are the kind of files that you want to
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keep local, and you don't want to put in the VCS repository.
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Another typical mistake, and that happens all the time, especially to
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novice users of VCS. Is that you get your file from VCS
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and so you get your local copy of the file that
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was in the VCS, and you want to make some changes, and
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before making the changes you decided, no, no let me actually save
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a local copy of the file, and I'm going to work on
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that one. Or let me save it before I modify it, or
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let take a snap shot of a whole tree of files. Just because
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I don't really trust the fact that VCS is going to be
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able to help and is going to be able to recover from possible
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mistakes. Never ever do that. I have seen that done many times,
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and it always leads to disasters. First of all it is useless, and
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second it's risky. Because then what happens is that at
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the time in which you have to turn in your assignment,
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in the case you are doing an assignment, but even in
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more serious situation, when you have to turn in your code,
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for example to your colleagues. You always end up being confused
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about which is the version that you're really using. So absolutely
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no local copies. No local redundancy when you're using a version
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control system. Trust the version control system, and trust the version
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control system to be able to manage your versions. You
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can always save it, commit it, retrieve previous versions, and you'll
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be able to do everything that you can do by copying
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the file yourself, and even more. So again, try the VCS.

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usth/ICT2.7/P1L4 Version Control Subtitles/9 - Two Main Types of VCS - lang_en_vs5.srt
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Something else I want to mention is that there
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are many different version control systems but we can classify
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them normally in two main types: centralized VCS's and
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decentralized VCS's. So what is the difference between these two?
5
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Let's use again our friends Janet and Brett.
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In the case of a centralized version control system
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there is a single centralized, as the name says,
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repository. On which they are commiting their files. So when
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Janet commits a file. The file will go from
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her local working directory to the repository, and the same
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will happen to Brett. The decentralized system is a little
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more interesting because in this case, they will both have
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sort of a local repository in which they can commit
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their changes. So they can commit changes without the other
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users of the VCS being able to see these changes.
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And when they're happy with the version. And when they're
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ready to release the version, they can push it to a central
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repository. And at that point, it will become available to the other
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users of the repository. To the other users of the VCS. There
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are several advantages in a distributive
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system. I'm just going to mention a few,
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because there are really many. One is the fact of having this
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local version. If you used VCS before, I'm sure you've been in
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the situation in which you want to kind of take a snapshot
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of what you have. But you don't want that snapshot to be available
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to the other users. Because it's still not ready to be
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released, to be looked up. If you're using a centralized system,
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there's really no way you can do that, unless you make
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a local copy, which is something we said you don't want
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to do. With a distributor, with a decentralized VCS you can
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commit your local changes here, in your local repository, and you
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can push them to the central repository only when you're ready.
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Another big advantage, is that you can use multiple remote repository.
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In fact, centralized is not the right name for this
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one. This is just a remote repository, and I can have
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more than one. For example, Brad might want to push
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to another remote repository. As well. For instance, this could be
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a repository where the files are accessible for wider distribution.
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Imagine developing a software system in which a team is sharing
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internal versions, and then only some of these versions are actually
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pushed to the repository that is seeable to the whole world.

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usth/ICT2.7/P1L5 Requirements Gathering Subtitles/1 - Gathering Requirements - lang_en_vs3.srt
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Gathering requirements is one of the most difficult tasks a software
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engineer faces. In industry, you may gather requirements from end users,
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external clients, or from co-workers in other areas of your own
4
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company. Occasionally, you may receive a well documented set of requirements.
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However, in most cases, you will need to glean the requirements
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from conversations with the prospective clients, and distill them down into
7
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something actionable on your own. Suppose a teacher came to you
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with a request for a piece of software their students could
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use to find out the average length of the sentences in
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their essays. What questions come into mind to help you figure
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out the full requirements for this project. Write down a list
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of at least ten questions that might help you determine them.
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Please take the time to do this before moving on. There's
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no penalty for looking ahead, but if you skip this exercise
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you'll cheat yourself out of the benefits of brainstorming and getting
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your mind around the project before being bombarded by more information.

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usth/ICT2.7/P1L5 Requirements Gathering Subtitles/2 - Choosing Good Questions - lang_en_vs3.srt
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Now that you've written some of your own questions, consider the following
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three. Which is the most likely to be useful for determining the detailed
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requirements? Maybe, what OSes should it run on? Or maybe, how will the
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user specify input? Or finally, how many lines of code should it take?

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usth/ICT2.7/P1L5 Requirements Gathering Subtitles/3 - Choosing Good Questions Solution - lang_en_vs3.srt
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The last question is almost never a reasonable one. For one
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thing, the client should not need to know or care about
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how many lines of code make up the program's source code.
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In forming requirements, you should avoid
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implementation specific questions that do not
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directly interface with the user. The first question is very relevant
7
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in some situations. For example, a graphic sentence with video game or
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performance is key. However, you should not write any operating system
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specific code unless absolutely needed, and should strive to make your code
10
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platform independent whenever possible. The
11
00:00:28,070 --> 00:00:30,990
second question, however, is very relevant.
12
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Now that you've thought a bit about what you might ask of
13
00:00:32,870 --> 00:00:35,810
the client requesting this program, let's watch Alvin, one of Udasea's
14
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engineers, asking his own questions. He'll be speaking with Lauren, the client.

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usth/ICT2.7/P1L5 Requirements Gathering Subtitles/4 - Requirements Interview - lang_en_vs3.srt
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Hi, I'm Lauren.
2
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>> Hi, I'm Alvin.
3
00:00:01,990 --> 00:00:06,470
>> I'm an instructor at a university nearby and I've been noticing that when
4
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my students write their essays, they have
5
00:00:09,700 --> 00:00:13,100
very long, very wordy sentences and I would
6
00:00:13,100 --> 00:00:17,600
like to develop some kind of tool that they can use to keep track of
7
00:00:17,600 --> 00:00:20,440
this and maybe perfect their writing style.
8
00:00:20,440 --> 00:00:21,410
Do you think that's something you could do?
9
00:00:21,410 --> 00:00:25,850
>> I think so. Let's start by helping me get acquainted with the students
10
00:00:25,850 --> 00:00:29,620
in the class. So how many students do we have in this class typically?
11
00:00:29,620 --> 00:00:34,000
>> Usually about 45 per unit, but I can have up to six units a semester.
12
00:00:34,000 --> 00:00:36,420
>> 45 students, and six sections per
13
00:00:36,420 --> 00:00:39,220
semester. That's a farily reasonable size. So,
14
00:00:39,220 --> 00:00:42,790
do you know anything about what the students are using as far as computers go?
15
00:00:42,790 --> 00:00:46,640
>> I don't know what kind of computers they're using. And they
16
00:00:46,640 --> 00:00:50,960
could be, I don't know, anywhere from having no tech experience to
17
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being pretty proficient.
18
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>> Do you know anything about how
19
00:00:54,930 --> 00:00:57,350
familiar the students are with computers in general?
20
00:00:57,350 --> 00:00:59,540
>> I'm sure we have some people on the low end that have
21
00:00:59,540 --> 00:01:01,430
never done any type of programming, and
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00:01:01,430 --> 00:01:03,680
then some people who are pretty self-sufficient.
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00:01:03,680 --> 00:01:07,210
>> Okay, and I guess my last question related to
24
00:01:07,210 --> 00:01:10,170
the students is, what is the students actually submitting to you.
25
00:01:10,170 --> 00:01:14,080
>> They've been sending just raw text files via email to me.
26
00:01:14,080 --> 00:01:16,660
>> So from the sounds of things
27
00:01:16,660 --> 00:01:19,140
we have a fairly broad, I guess base
28
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of students to work with, both in technical proficiency
29
00:01:23,100 --> 00:01:27,180
as well as their operating system environments potentially.
30
00:01:27,180 --> 00:01:29,420
So I think what we'll probably do to start
31
00:01:29,420 --> 00:01:33,270
off with is make a command line, Java
32
00:01:33,270 --> 00:01:36,760
based tool. That the students can run and we'll
33
00:01:36,760 --> 00:01:39,910
give them a fair amount of you know, documentation
34
00:01:39,910 --> 00:01:41,690
on how to use the tool. And I expect
35
00:01:41,690 --> 00:01:45,090
that there will be a lot of little error conditions that may happen
36
00:01:45,090 --> 00:01:49,320
that we want to produce a reasonably friendly message were anything to go wrong.
37
00:01:49,320 --> 00:01:50,480
>> Yeah. That'd be great.
38
00:01:50,480 --> 00:01:54,750
>> So, a little bit more, I guess about
39
00:01:54,750 --> 00:01:58,539
the actual essay itself, its submission, what constitutes a word?
40
00:01:59,820 --> 00:02:03,190
>> I really only care about the longer words, so, is there a
41
00:02:03,190 --> 00:02:06,140
way that we can only count words that are maybe above three letters?
42
00:02:06,140 --> 00:02:06,830
>> I think
43
00:02:06,830 --> 00:02:08,508
that's something we can do. And I think
44
00:02:08,508 --> 00:02:10,030
that because you seem a little bit unsure
45
00:02:10,030 --> 00:02:11,540
we might be able to have that be
46
00:02:11,540 --> 00:02:13,820
a little bit more flexible than we otherwise would.
47
00:02:13,820 --> 00:02:14,500
>> Great.
48
00:02:14,500 --> 00:02:18,330
>> What does a sentence mean to you? Is it kind of flexible?
49
00:02:18,330 --> 00:02:21,280
>> I would say anything that ends in a period or
50
00:02:21,280 --> 00:02:25,870
even a question mark. Maybe even an exclamation mark. or, something
51
00:02:25,870 --> 00:02:28,760
even, maybe even with a comma or semi-colon. I really only
52
00:02:28,760 --> 00:02:32,370
care about the sentences that aren't gramatically correct and are too long.
53
00:02:32,370 --> 00:02:35,180
>> I think we can probably make that a little bit more flexible too
54
00:02:35,180 --> 00:02:37,520
so that way, you can kind of say we're going to, or you want to include them.
55
00:02:37,520 --> 00:02:38,020
>> Mm-hm.
56
00:02:38,020 --> 00:02:41,786
>> So maybe, sounds like you are little bit on the fence
57
00:02:41,786 --> 00:02:45,100
about whether or not say, a comma should be considered a sentence.
58
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>> Mm.
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00:02:45,130 --> 00:02:46,370
>> Entirely on its own or not. So we
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00:02:46,370 --> 00:02:49,830
can probably make that a little bit configurable as well.
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00:02:51,880 --> 00:02:56,510
And so, just to confirm the actual end result to
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00:02:56,510 --> 00:02:59,870
the student is the average number of words per sentence?
63
00:02:59,870 --> 00:03:01,610
>> Yeah, yeah that'd be fine.
64
00:03:01,610 --> 00:03:07,430
>> Okay, overall to start off with, looks like we have some
65
00:03:07,430 --> 00:03:10,280
sort of customization of the word length that we want to look for.
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00:03:10,280 --> 00:03:10,780
>> Mm-hm. Yeah.
67
00:03:12,000 --> 00:03:14,650
>> We have some kind of variability in
68
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what we want to have as acceptable sentence structure.
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00:03:17,880 --> 00:03:24,570
So, periods, question marks, semicolons, things like that. And, the end result
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to the student is if we're successful, they'll get the average number of
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00:03:27,260 --> 00:03:31,060
words per sentence. Otherwise we tell them something a little bit helpful to
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00:03:31,060 --> 00:03:33,240
kind of put them on the right track to use the tool correctly.
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00:03:33,240 --> 00:03:34,620
>> Yeah that's the error codes right?
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00:03:35,850 --> 00:03:38,150
>> Hopefully not error codes but something a little bit nicer.
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00:03:38,150 --> 00:03:39,800
>> [LAUGH] Okay.
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00:03:39,800 --> 00:03:41,150
>> So I think I have enough to
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00:03:41,150 --> 00:03:43,440
get started and produce something that's you know,
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a reasonable I guess, rough draft. Of something
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00:03:47,150 --> 00:03:48,700
that you can use to help your class out.
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>> Great. Thank you.
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00:03:49,590 --> 00:03:50,240
>> Thank you.

83
usth/ICT2.7/P1L5 Requirements Gathering Subtitles/5 - Average Sentence Length Requirements - lang_en_vs3.srt
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1
00:00:00,340 --> 00:00:02,300
You've heard Alvin come up with several conclusions for how to
2
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set up the program. And we're going to ask that you follow his
3
00:00:04,510 --> 00:00:07,590
instincts. We'll spell that out here in a little more technical details
4
00:00:07,590 --> 00:00:11,030
so that everyone is working from the same basic starting point. The
5
00:00:11,030 --> 00:00:13,770
program must be written in Java and must not make you any
6
00:00:13,770 --> 00:00:16,730
nonstandard Java libraries. You will be tested on a machine with the
7
00:00:16,730 --> 00:00:21,060
vanilla installation of Java 1.6. Your program must compile on the command
8
00:00:21,060 --> 00:00:25,360
line using the Java C command without any additional options. All code
9
00:00:25,360 --> 00:00:27,530
required to execute the program that is not part of the
10
00:00:27,530 --> 00:00:31,950
standard JDK, must be included as source code with your program.
11
00:00:31,950 --> 00:00:34,380
Your program should be an application. That is, it should have
12
00:00:34,380 --> 00:00:37,160
a main method and should be executable from the command line using
13
00:00:37,160 --> 00:00:40,100
the Java command. The user should be able to provide a
14
00:00:40,100 --> 00:00:42,450
file path to the file they wish to be analyzed as a
15
00:00:42,450 --> 00:00:45,880
command line argument. User should be able to specify which delimiters
16
00:00:45,880 --> 00:00:50,570
count as sentence separators, using the flag -d, defaulting to Lauren's initial
17
00:00:50,570 --> 00:00:53,930
thoughts on what should be used as delimiters. The user should be
18
00:00:53,930 --> 00:00:58,170
able to specify a lower limit for word length, using the flag -l,
19
00:00:58,170 --> 00:01:02,100
defaulting to Lauren's guess at what value might be good. Finally, the program's
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output should be the average sentence
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length. Rounded down to the nearest integer.

55
usth/ICT2.7/P2L1 Requirements Engineering Subtitles/1 - Lesson Overview - lang_en_vs4.srt
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1
00:00:00,340 --> 00:00:05,670
Hello and welcome to the second part of our software engineering course. In the
2
00:00:05,670 --> 00:00:09,030
previous mini-course, we discussed some basic principles
3
00:00:09,030 --> 00:00:12,430
behind software engineering. We provided an overview of
4
00:00:12,430 --> 00:00:15,790
several software process models and we introduced
5
00:00:15,790 --> 00:00:18,530
some important tools that can help developers
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00:00:18,530 --> 00:00:21,363
increase their productivity. In this mini-course, we
7
00:00:21,363 --> 00:00:25,740
will focus on requirement and prototyping. More precisely,
8
00:00:25,740 --> 00:00:28,840
we will discuss in depth requirements
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00:00:28,840 --> 00:00:32,400
engineering activities. We will also discuss
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00:00:32,400 --> 00:00:34,950
techniques to perform a system analysis
11
00:00:34,950 --> 00:00:38,720
and design in an object-oriented fashion. So,
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00:00:38,720 --> 00:00:42,250
let's start the first lesson of this mini-course, which is about the use
13
00:00:42,250 --> 00:00:45,230
of engineering techniques to understand and
14
00:00:45,230 --> 00:00:48,450
specify the purpose of a software system.

15
usth/ICT2.7/P2L1 Requirements Engineering Subtitles/10 - Completeness Quiz - lang_en_vs4.srt
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1
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So now that we saw which of these requirements are pertinent and
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which ones are not, can we consider the above list of requirements
3
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of the list of these requirements marked here as a complete list
4
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of requirements for a gym? And you have two options, yes or no.

23
usth/ICT2.7/P2L1 Requirements Engineering Subtitles/11 - Completeness Quiz Solution - lang_en_vs4.srt
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1
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And the answer is clearly no.
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Obviously, there are many missing requirements here.
3
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For example, requirements about registration for the
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00:00:07,910 --> 00:00:11,560
customers, requirements about fitness program creation, membership
5
00:00:11,560 --> 00:00:15,481
types, and so on. Plus, we are also missing all of the nonfunctional
6
00:00:15,481 --> 00:00:19,270
requirements, which we haven't seen yet, but that we will discuss in a bit.

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usth/ICT2.7/P2L1 Requirements Engineering Subtitles/12 - Irrelevant Requirements Quiz - lang_en_vs4.srt
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1
00:00:00,140 --> 00:00:02,400
In the previous quiz, we saw that some of the requirements
2
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that they put in the list were not pertinent. They were
3
00:00:04,920 --> 00:00:08,590
irrelevant. So let me ask you. Why can irrelevant requirements be
4
00:00:08,590 --> 00:00:12,170
harmful? Why is that a problem to have irrelevant requirements? So
5
00:00:12,170 --> 00:00:15,060
here, I'm giving you four possible answers. And I'd like for
6
00:00:15,060 --> 00:00:18,150
you to mark all that apply. Can irrelevant requirements be harmful
7
00:00:18,150 --> 00:00:21,210
because they may lead to missing functionality in the final product.
8
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Because they can introduce inconsistency. Because
9
00:00:23,390 --> 00:00:25,410
they can waste the project resources.
10
00:00:25,410 --> 00:00:28,170
Or because they may introduce bugs in the software system. And
11
00:00:28,170 --> 00:00:30,680
as I said, more than one can be a valid reason.

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usth/ICT2.7/P2L1 Requirements Engineering Subtitles/13 - Irrelevant Requirements Quiz Solution - lang_en_vs5.srt
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1
00:00:00,200 --> 00:00:02,920
So let's go through the list. Definitely irrelevant requirements
2
00:00:02,920 --> 00:00:06,370
cannot lead to missing functionality in the final product, because
3
00:00:06,370 --> 00:00:10,730
irrelevant requirements actually refer to unneeded functionality in the system.
4
00:00:10,730 --> 00:00:13,030
So functionality that is put in the requirements, but it
5
00:00:13,030 --> 00:00:15,120
is not really needed. So we're not going to mark
6
00:00:15,120 --> 00:00:19,400
this one. Indeed, irrelevant requirements can introduce inconsistencies. So they
7
00:00:19,400 --> 00:00:22,490
could be irrelevant requirements that not only are not pertinent
8
00:00:22,490 --> 00:00:25,620
but they are inconsistent with some of the pertinent requirements.
9
00:00:25,620 --> 00:00:29,220
They can also waste project resources, because if we spend time
10
00:00:29,220 --> 00:00:31,920
designing and then implementing the parts of the system that we
11
00:00:31,920 --> 00:00:35,410
refer to these irrelevant requirements, of course, we are wasting project
12
00:00:35,410 --> 00:00:38,570
resources. And I will not mark the last one because there's really
13
00:00:38,570 --> 00:00:42,220
no correlation between any irrelevant requirements and bugs in the software
14
00:00:42,220 --> 00:00:45,350
system. Of course, by implementing the part of the system that refers
15
00:00:45,350 --> 00:00:47,960
to an irrelevant requirement you might introduce a bug. But that's
16
00:00:47,960 --> 00:00:51,020
not necessarily the case, and there really no correlation between the two.

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usth/ICT2.7/P2L1 Requirements Engineering Subtitles/14 - Best Practices - lang_en_vs5.srt
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But we collect requirements all the time, right? Every
2
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time we build a software system. So how do people
3
00:00:04,960 --> 00:00:08,320
cope with these difficulties? What are the best practices?
4
00:00:08,320 --> 00:00:12,950
In practice, developers or analysts usually identify a whole bunch
5
00:00:12,950 --> 00:00:16,590
of requirements. Sometimes the easiest and most obvious ones. They
6
00:00:16,590 --> 00:00:19,370
bring those to the stakeholders, and the stakeholders have to
7
00:00:19,370 --> 00:00:23,100
read the requirements, understand them, and if they agree, sign
8
00:00:23,100 --> 00:00:25,580
off on them. And the problem is that in general,
9
00:00:25,580 --> 00:00:28,910
these requirements documents are difficult to read. They are long, they
10
00:00:28,910 --> 00:00:32,470
are often unstructured. They typically contain a lot of information. And
11
00:00:32,470 --> 00:00:35,310
in general, they are not exactly a pleasant read. So what
12
00:00:35,310 --> 00:00:39,710
happens is that often the stakeholders are short on time, overwhelmed
13
00:00:39,710 --> 00:00:42,380
by the amount of information they're given and so they give
14
00:00:42,380 --> 00:00:44,800
in to the pressure and sign. And this is a bit
15
00:00:44,800 --> 00:00:47,300
of a dramatization clearly but it's clear that what we are
16
00:00:47,300 --> 00:00:50,640
looking at is not an ideal scenario. Clearly this is not
17
00:00:50,640 --> 00:00:53,810
the way to identify the real purpose of a software system to
18
00:00:53,810 --> 00:00:57,920
collect good requirements. And since one of the major causes for project
19
00:00:57,920 --> 00:01:02,130
failure is the inadequacy of requirements, we should really avoid this kind
20
00:01:02,130 --> 00:01:03,590
of scenario. We should follow a
21
00:01:03,590 --> 00:01:06,810
rigorous and effective requirements engineering process instead.

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usth/ICT2.7/P2L1 Requirements Engineering Subtitles/15 - RE Definition Breakdown - lang_en_vs4.srt
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1
00:00:00,130 --> 00:00:02,540
But how can we do that? How can we identify the purpose
2
00:00:02,540 --> 00:00:06,080
of the system and collect good requirements? To answer that question, let me
3
00:00:06,080 --> 00:00:07,800
give you another definition of requirements
4
00:00:07,800 --> 00:00:09,590
engineering. And this one is a classical
5
00:00:09,590 --> 00:00:13,010
one, one that summarizes what we discussed so far, and then we can
6
00:00:13,010 --> 00:00:16,180
use as some sort of reference. And it is a little long.
7
00:00:16,180 --> 00:00:18,710
Definitely longer than the one that we saw at the beginning. But it's
8
00:00:18,710 --> 00:00:21,840
an important one and it contains a lot of very relevant points. So,
9
00:00:21,840 --> 00:00:25,210
we're going to go through it and highlight these points. So the definition says,
10
00:00:25,210 --> 00:00:28,970
that the requirements engineering is a set of activities concerned
11
00:00:28,970 --> 00:00:32,990
with identifying and communicating the purpose of a software intensive
12
00:00:32,990 --> 00:00:35,770
system and the context in which it will be used.
13
00:00:35,770 --> 00:00:38,570
And this is exactly what we said at the beginning. But
14
00:00:38,570 --> 00:00:40,940
something we can highlight in here, is the fact that
15
00:00:40,940 --> 00:00:44,210
we're talking about a set of activities. So, what that means
16
00:00:44,210 --> 00:00:46,800
is that requirements engineering is not just a phase or
17
00:00:46,800 --> 00:00:51,050
a stage. It also says that it's about identifying and communicating.
18
00:00:51,050 --> 00:00:53,720
And what that is telling us is that communication is
19
00:00:53,720 --> 00:00:56,670
as important as the analysis. So, it's important to be
20
00:00:56,670 --> 00:00:59,990
able to communicate these requirements not only to collect them.
21
00:00:59,990 --> 00:01:02,018
And we will discuss many reasons why that is the
22
00:01:02,018 --> 00:01:05,880
case. It explicitly talks about purpose. So that allows me
23
00:01:05,880 --> 00:01:10,310
to stress, once more, that quality means fitness-for-purpose. We cannot
24
00:01:10,310 --> 00:01:14,410
say anything about quality unless we understand the purpose. And
25
00:01:14,410 --> 00:01:16,210
the last thing I want to point out in this first
26
00:01:16,210 --> 00:01:18,420
part of the definition is the use of the term
27
00:01:18,420 --> 00:01:21,060
context. This is also something else that we mentioned at
28
00:01:21,060 --> 00:01:24,890
the beginning, that designers, analysts, need to know how and
29
00:01:24,890 --> 00:01:28,015
where the system will be used. Without this information, you
30
00:01:28,015 --> 00:01:30,455
cannot really understand what the system should do and you
31
00:01:30,455 --> 00:01:33,280
cannot really build the system. So now, let's continue and
32
00:01:33,280 --> 00:01:35,755
read the second part of the definition that says, hence.
33
00:01:35,755 --> 00:01:41,550
Requirements engineering acts as the bridge between the real-world needs of
34
00:01:41,550 --> 00:01:45,315
users, customers, and other constituencies affected by a
35
00:01:45,315 --> 00:01:49,440
software system and the capabilities and opportunities afforded
36
00:01:49,440 --> 00:01:52,870
by software-intensive technologies. This is a long sentence,
37
00:01:52,870 --> 00:01:55,030
but also here, we can point out a
38
00:01:55,030 --> 00:01:57,670
few interesting and relevant points. Let me start
39
00:01:57,670 --> 00:02:00,612
by highlighting two parts. Real-world needs, and the
40
00:02:00,612 --> 00:02:04,150
capabilities, and opportunities. So, what are these two
41
00:02:04,150 --> 00:02:07,000
parts telling us? They are telling us that requirements
42
00:02:07,000 --> 00:02:09,949
are partly about what is needed, the real-world needs
43
00:02:09,949 --> 00:02:13,520
of all these stakeholders. But they're also partly about what
44
00:02:13,520 --> 00:02:16,100
is possible, what we can actually build. We need
45
00:02:16,100 --> 00:02:19,260
to compromise between these two things. And, finally, I would
46
00:02:19,260 --> 00:02:23,000
like to point out this term constituencies, which indicates
47
00:02:23,000 --> 00:02:26,220
that we need to identify all of the stakeholders, not
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just the customer and the users, so anybody who is
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affected by a software system. It is very important to
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consider all of these actors. Otherwise, again,
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we'll be missing requirements, we'll be missing
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part of the purpose of the system and we will build a suboptimal system.

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So at this point, we have talked quite a bit about
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requirements engineering, but we haven't
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really discussed what are requirements exactly.
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So what is a requirement? To define that I am going
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to use this diagram which is a classical one. So you might
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have seen it before. So, discussing this diagram allows me to
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point out a few interesting things about requirements and define them
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in a better way. At a high level this diagram contains
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two main parts, the domain of the machine, which is the hardware,
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operating system, libraries and so on, on which the
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software will run. And the domain of the application, which
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is a world in which the software will operate.
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And the machine domain is characterized by computers, which are
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the hardware devices, and programs, which is the software
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that runs on these devices. The application domain, conversely, is
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characterized by domain properties, which are things that are true
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of the world anyways, whether I'm building my system or
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not, and requirements, which are things in the world we
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would like to achieve by delivering the system that we are
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building. Basically, to put it in a different way, the former,
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the domain properties, represents the assumptions that we make on the
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domain. And the latter, the requirements, are the actual requirements
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that we aim to collect. So we have something here, right,
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at the intersection of this application domain and this machine domain.
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And what is that? And this is what we normally call
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the specification, which is a description, often a formal description,
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of what the system that we are building should do to
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meet the requirements. So this is a bridge between these two
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domains. And as the graphical depiction shows, the specification is written
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in terms of shared phenomena. Things that are observable in both
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the machine domain and the application domain. And just to make
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things a little more concrete, I want to give you a
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couple of examples of what these phenomena, these shared phenomena, are.
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And we can think about two main kinds of phenomena.
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The first one are events in the real world that the
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machine can directly sense. For example, a button being pushed or
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a sensor being activated. These are events that happen here, but
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that the machine can detect. So they're events that can
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be used to define the specification. And the second type of
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phenomena are actions in the real world that the machine can
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directly cause. For example, an image appearing on a screen or
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a device being turned on and off. Again, this is something
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that the machine can make happen and then can have manifestation in
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the real world. And again this is therefore something on which
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the specification can predicate, something that
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we can describe in our specification.
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And this is sort of a philosophical discussion, but even if
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you don't care about the philosophical discussion, the one take away point
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that I would like for you to get from this discussion is
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the fact that when writing a specification you have to be aware
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of the fact that you're talking about shared phenomena. Events in the real
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world that the machine can sense and actions in the real world that the
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machine can cause. So this is what the specification is about, a bridge between
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these two worlds that define what the
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system should do to satisfy the requirements.

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Since we just discussed application
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domain, machine domain, and the specificiation,
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let's make sure that these concepts are well understood. To do that,
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I'm going to use a quiz, and I would like for you
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to refer to the figure that we just discussed that I'm also
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reproducing here on a small scale on the right. And then
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referring to the figure, you should indicate for each of the items
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that I'm going to show you here shortly. Whether they belong to
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the machine domain. In this case, we're going to put a one next
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to the icon. The application domain, in this case you should
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put two. Or their intersection, and in this case you should
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put three. So this is the lists of items. So let
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me read it. An algorithm sorts a list of books in alphabetical
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order by the first author's name. A notification of the arrival
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of a message appears on a smart watch. An employee wants to
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organize a meeting with a set of colleagues. And finally, a
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user clicks a link on a web page. So again, put 1,
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2, or 3 here in these lots, depending on whether you think that these items
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belong to the machine domain, the application
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domain, or their intersection. So, their specification, here.

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So let's look at each one of these items individually, starting from
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the first one. And here this item has to do with how
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the machine stores the information and
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how the corresponding algorithm is written.
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But it has no bearing in the real world. That is, in
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the application domain. Therefore this. Definitely
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belongs to the machine domain, and
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we're going to put a one here. What about a notification of
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the arrival of a message on a smart watch? This is an
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event that is generated within the machine, but it has an effect,
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an observable effect, in this case, in the real world as well.
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Therefore, we're going to mark this as three. So this is an
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event. This is something that belongs
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to the intersection between the application
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domain and the machine domain. So it's something that could be in
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the specification. Now what about an employee that wants to organize a
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meeting with a set of colleagues? This is an event that belongs
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to the application domain because it is a fact that it's true
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that exists. In the real world independently from the existence of a machine.
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Therefore, we're going to mark this as two.
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Finally, the event of a user clicking on a
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link on a web page is an event that occurs in the real world but that has an
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effect also within the machine and, therefore, we're
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going to mark this as three, something that happens
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at the intersection. between these two domains, and once
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more, something that could be in a specification.

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Among the requirement that we can collect from the application
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domain, we need to distinguish between two main types. And you've
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probably heard about these ones.
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Functional requirments and non-functional requiremnts. Functional
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requiremetns have to do with the functionality of the system, with
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what the system does with the computation. For example the elevator
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shall take people to the floor they select. That's a functional
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requirement, that has to do with the functionality of the system.
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Or for a very simple one, the system has to output
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the square root of the number past as
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an input. So these kind of requirements have in
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general well defined satisfaction criteria. So, for example, if
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for the latter one that we mentioned it is
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pretty clear how to check whether the output
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is actually the square root of the number passed
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in input. Non-functional requirements, conversely, refer to a system's
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non-functional properties, systems qualities.
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Such as security, accuracy, performance,
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cost. Or, you know, usability,
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adaptability, interoperability, reusability and so
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on. So, all these qualities the don't necessarily have to
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do with the functionality. And, unlike functional requirements, non functional
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requirements Do not always have clear satisfaction criteria. For example,
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if we say that the elevator must be fast, that's
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a non-functional requrement. Right? It has to do with the
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speed of the elevator, which is a quality of the
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elevator. But, it, it's not clear how such a requirement
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could be satisfied. How could we tell whether the elevator
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is fast or not. So, what we need to do
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in these cases Is that we need to refine these
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requirements so that they become verifiable. For the example that
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I just mentioned, for instance, we might say that the
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elevator must reach the requested floor in less than 30
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seconds from the moment when the floor button is pushed.
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This is still a non-functional requirment, but is a verifiable one.

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As we did for other lessons, before starting this
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lesson on requirements engineering, I want to ask a world
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expert on this topic a few questions. I'm here with
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Jane Cleland-Huang, a professor at the DePaul University. And Jane
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is a world expert in the area of requirements
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engineering, which is the theme of this lesson. So I'm
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talking to Jane who is currently in Chicago and I
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want to. Ask her a few questions about requirements engineering.
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So hi Jane how are you?
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>> Fine. Thank you Alex.
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>> And thank you so much for agreeing to
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be interviewed for our course, I'm sure the students
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will really benefit from this. And let me start
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with the first question which is what are software requirements?
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>> That's an interesting question. And software requirements
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basically provide us a description of what a
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system has to do. So, typically they describe
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the functionality of the features. That the system has
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to deliver in order to satisfy its stakeholders.
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And we usually talk about the requirement specification
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in terms of what the system's going to
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do. And we describe it sometimes formally in
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terms of set of shall statements, that the
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system shall do this or shall do that.
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Or we can use various templates to specify
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both textural requirements. But requirements can also be represented
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informally in, in the form of user stories, or use cases, or more
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formally in the form of state transition diagrams and even in kind of
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formal specifications. Especially for critical parts of safety critical systems.
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>> And another should discuss what the
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requirements are. What is the requirements engineering?
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>> So, that's also an interesting question because if you notice
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it's it's engineering and I'm sure in the
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other parts of the software engineering process that
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you're discussing in your course. Parts such as
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testing or coding. They don't have the word engineering
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there and I think one of the reasons
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requirements engineering has that term is because it covers
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a number of different activities. So it includes
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things such as working with stakeholders to elicit or
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to proactively discover what their requirements of the
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system are. Analyzing those requirements so that we
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understand the tradeoffs. So you might have different
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stakeholders that care about different things, and it
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might not be possible to deliver all of those things, so we have to analyze the
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feasibility of the requirements, explore the tradeoffs, emerge
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conflicts. And then of course the specification part,
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which we talked about a little bit already,
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and the validation, so did we in fact get
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the requirements right? Did we build a system
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that actually matches our, our requirements. And then on
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into the requirements management process. And the requirements
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management process. Kind of like goes through things like
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change management. So what if customer or stakeholders
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need the system to change? How do we manage
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changing requirements? And I think this is one of
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the reasons that we've coined the term engineering because
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that it's, has to be a systematic process which
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extends across. The whole of this is life cycle.
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>> And I guess my last question here is
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so now that we heard about software requirements and
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about software requirements engineering, why is requirements engineering so
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important? So what happens if we don't do it right?
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>> Well, I'm sure that, you know,
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many people have probably read the kind of
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report like Spanish report, and other reports of failed
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project, and things like that, and are aware that
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one of the major reasons for projects failing
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is because we didn't get the requirements right
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in the first place. So if we don't understand
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the requirements then we're simply going to build the
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wrong system. Getting requirements right includes all sorts of
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things such as finding the right group of stakeholders so we don't exclude major
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groups of stakeholders. Understanding the requirements correctly.
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There will be many, many different examples of
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projects that have failed. For example, in
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America the healthcare.gov failure, and while we cannot
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put the blame squarely in the area
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of requirements, because obviously the project was challenged
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for a number of different reasons. But
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clearly it underperformed in many respects related to
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security, performance, and reliability and these are all
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parts of the requirements process. Things that should
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have been discovered and the system should have
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been built in order to meet those requirements,
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getting the requirements right in the first place.
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Puts us, a project on the right foot.
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And so that gives us a much better chance
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of delivering to the customer what they need. And
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designing a solution that really meets those requirements. So,
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it's a critical part of the overall software engineering success.
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>> Okay. So that's critical. I mean, we better get our requirements right.
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>> Yeah.
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>> That's, that's the message.
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>> Yeah.
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>> Okay. Well, thank you so much Jane, for taking
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the time off your busy schedule to speak with us.
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I'm sure. The students really appreciate this, and we'll talk to you soon.
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>> Bye Alex, thank you.
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>> Bye, Jane, bye bye. Jane gave
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us an interesting perspective on requirements engineering
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and its importance. Let's now start our
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lesson with a general definition of requirements engineering.

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Another important distinction, when talking about requirements, is that
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between user and system requirements. So, let's start with defining
3
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user requirements. Those are requirements that are written for the
4
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customers and they're often in natural language and they don't
5
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contain technical details. And the reason for that is
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that their purpose is to allow customers, stakeholders, to check
7
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that the system will do what they intended. So it's
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a way for the analyst, the developers, to communicate with
9
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the customers, with the stakeholders. System requirements, on the
10
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other hand, are written for developers. Contain detailed functional and
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non functional requirements. Which we just discussed, and which
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are clearly and more rigourously specified than the user requirements.
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And the reason for this difference is that the
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purpose of the system requirements is to tell developers what
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to build. They must contain enough details so the
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developers can take them and use them to design and
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then develop a system. Just to give you a concrete
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example, here I'm showing you a user requirement that just says
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that the software must provide a means of representing and accessing
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external files created by other tools, and the corresponding system requirement.
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And as you can see, even if we don't read the
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whole requirements. The former is an informal and high level description
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of a piece of functionality, whereas the latter describes the same
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functionality but in a much more extensive and rigorous way. As
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I said, this is something that the developers can use to
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design and then build a system whereas this is something that
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can be used to communicate. With the stakeholders, with a non-technical
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audience. And we need to define both because they serve different purposes.

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After all these talking about requirements, let's have a small quiz, I
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want to ask you which of the
3
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following requirements are non-functional requirements? And here
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I'm listing the requirements, the first one says at the BowlingAlley program
5
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keeps track of the score during a game, the second one is that
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the WordCount program should be able to process large files. The third
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one is that the Login program for a website. Should be secure, and
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finally the last one says that the vending machine program should take coins
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as an input from the user. So, I want you to mark all
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the ones that are non-functional requirements, that
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don't refer to the functionality of the system.

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So, the first requirement clearly refers to some specific functionality of
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the Bowling Alley system, because it talks about what the system has
3
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to do from a functional standpoint. So, it's definitely not a non-functional
4
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requirement. On the other hand, the fact that the Word Count system
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should be able to process large files, is telling us something not
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about the functionality of the system, but rather about its qualities. The
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fact that it has to be scalable, that it has to be
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efficient and so we can consider this to be a non-functional requirement.
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Similarly, the fact that the Login program for a
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website should be secure is definitely telling us something
11
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about the quality of the system that has little
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to do with its functionality. And so this is
13
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also a non-functional requirement. Finally, the fact that the
14
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Vending Machine program should take coins as an input
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from the user is telling us something about the
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00:00:41,010 --> 00:00:44,100
functionality of the program and therefore, is a functional requirement.

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Now that we know what the requirements are and
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their main types, let's discuss where requirements come from and
3
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there are many possible sources for requirements so I'm
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going to list here the main ones. The first one are
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clearly stakeholders, anybody who is effected by the system
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and its functionality. Customers, users, and so on. The second
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typical social requirement is the application domain. For example,
8
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the fact that my software is running within a bank,
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or within a school. Why is the application domain a
10
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social requirement? Well, because there are constraints that are characteristics
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of the application domain that will affect the functionality of
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the system. For a simple example, just think about regulations.
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So banking regulations and school regulations in these cases. Those
14
00:00:40,400 --> 00:00:43,120
are things that might affect the functionality of my system
15
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and, therefore, that may become part of my requirements. And,
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finally, documentation can be an additional source of requirements. For example,
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notes, papers, manuals, books. So everything that refers to
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00:00:54,110 --> 00:00:56,610
the functionality of the system that we're going to build.

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Unfortunately, extracting requirements from these sources is not
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a straightforward task, as there are many issues involved
3
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with the requirements elicitation. One first problem is the
4
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thin spread of domain knowledge. Knowledge is rarely available
5
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in an explicit form, that is, it is
6
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almost never written down. Moreover, knowledge is often distributed
7
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across many sources. For example, in the graphical depiction
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here, to find out that this is the purpose
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of the project. The developer, the analyist, needs to talk
10
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to a lot of different people. And, to make things even
11
00:00:30,870 --> 00:00:34,400
worse. There are often conflicts between the knowledge gathered from
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different sources. A second issue is the fact that the knowledge
13
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is often tacit. What is also called the say, do
14
00:00:41,090 --> 00:00:44,052
problem. In the example shown here. For instance. We have a
15
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customer that is describing to the analyst. The way in which
16
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he accomplishes a task. So it performs these three steps and
17
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reaches the goal. Whereas in practice, the actual way in
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which this task accomplished is by going through a larger number
19
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of steps to get to the same goal. So the point
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here is that, even if the knowledge were more concentrated, so
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not as spread as in this example. People simply find
22
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it hard to describe knowledge that they regularly use. So it
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is hard to make this knowledge explicit, to pass this knowledge
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to someone else. Yet another
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problem is limited observability. Identifying requirements
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through observation is often difficult as the problem owners might be
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too busy to perform the task that we need to observe.
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Or they might be doing a lot of other things together
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with the task that we need to observe, so that becomes
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confusing. That introduces noise. Moreover, even when this is not the
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case, the presence of an observer might change their problem. It
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is very typical for human subjects to improve or modify an
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aspect of their behavior, which is being experimentally measured in response
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to the fact that they know that they're being studied. You know
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that somebody's studying you and you change the way in which you behave.
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A typical issue. Finally, the information that we collect might be biased.
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For several reasons. People might not feel free to tell you what you
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need to know. Or, people might not want to tell you what
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you need to know. For example, in all the common cases in which
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the outcome might effect them, people might provide you a different picture
41
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from the real one. In order to influence you. So, they might have
42
00:02:06,770 --> 00:02:08,820
a hidden agenda, and mislead you, either
43
00:02:08,820 --> 00:02:11,860
consciously or unconsciously. So, all these issues
44
00:02:11,860 --> 00:02:14,370
add to the complexity of collecting requirements,
45
00:02:14,370 --> 00:02:16,522
of identifying the purpose of a system.

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To cover the intrinsic problem of eliciting requirements,
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many different techniques have been proposed. So here
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I list some of most traditional techniques for
4
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requirement elicitation and as I present those, please keep
5
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in mind that these techniques can be used
6
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separately or combined. A first technique is called background
7
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reading. And, this technique involves collecting information by
8
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reading existing documents such as company reports, organizational charts,
9
00:00:24,840 --> 00:00:29,280
policy manuals, job descriptions, documentation of existing systems and so
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on. And, this technique is especially appropriate when one Is
11
00:00:32,400 --> 00:00:35,370
not familiar with your organization for which the requirements are
12
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being collected. So you want to get some background before interviewing
13
00:00:38,950 --> 00:00:41,240
actual people. And one of the main imitations of these
14
00:00:41,240 --> 00:00:43,930
kinds of approaches is that written documents might be out
15
00:00:43,930 --> 00:00:46,320
of sync and they often are out of sync with
16
00:00:46,320 --> 00:00:49,970
reality. Tend to be long winded. It may contain many irrelevant
17
00:00:49,970 --> 00:00:51,850
details, so you may have to look at a lot
18
00:00:51,850 --> 00:00:54,810
of materials to extract enough information. The hard data and
19
00:00:54,810 --> 00:00:58,650
samples techniques consist in deciding which hard data we want
20
00:00:58,650 --> 00:01:01,680
to collect and choosing the sample of the population for which
21
00:01:01,680 --> 00:01:04,750
to collect such data and hard data includes facts and
22
00:01:04,750 --> 00:01:09,790
figures such as forms, invoices, financial information, survey results, marketing
23
00:01:09,790 --> 00:01:12,300
data, and so on. And the sampling of this data
24
00:01:12,300 --> 00:01:15,170
can be done in different ways. For example, the typical ways
25
00:01:15,170 --> 00:01:19,200
to do random selection. Interviews are another typical approach for
26
00:01:19,200 --> 00:01:21,870
requirement solicitation, and this is the approach that we use for
27
00:01:21,870 --> 00:01:24,910
the first project in this course, for instance. Interviews can be
28
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structured in which case there is an agenda of fairly open
29
00:01:27,720 --> 00:01:30,450
questions or they can be open ended in which case there
30
00:01:30,450 --> 00:01:32,770
is no preset agenda and the interview is more of a
31
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conversation. On the positive side, interviews can collect a rich set
32
00:01:36,500 --> 00:01:40,260
of information because they allow for uncovering opinions as well as
33
00:01:40,260 --> 00:01:43,230
hard facts. Moreover, they can probe in depth through follow
34
00:01:43,230 --> 00:01:46,790
up questions. On the more negative side, interviewing requires special
35
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skills that are difficult to master and require experience. And
36
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it is not enough to collect a lot of information. If
37
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this information is hard to analyze or even irrelevant, it
38
00:01:55,520 --> 00:01:58,250
might become useless. So you need to know how to conduct
39
00:01:58,250 --> 00:02:01,180
an interview in order to take advantage of these techniques.
40
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Surveys can also be extremely useful for gathering new requirements because
41
00:02:05,440 --> 00:02:08,550
they can quickly collect information from a large number
42
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of people. Moreover, they can be administered remotely. For
43
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example, by email, through the web. On the other
44
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hand, surveys tend to severely constrain the information that
45
00:02:16,750 --> 00:02:19,430
the user can provide and might miss opportunities to
46
00:02:19,430 --> 00:02:24,460
collect unforeseen, relevant information. Finally, meetings are generally used
47
00:02:24,460 --> 00:02:27,690
for summarization of findings and collection of feedback, so as
48
00:02:27,690 --> 00:02:30,500
to confirm or refute what has been learned. So the
49
00:02:30,500 --> 00:02:32,660
only additional thing I want to mention about meetings
50
00:02:32,660 --> 00:02:34,920
is the fact that it is fundamental that have clearly
51
00:02:34,920 --> 00:02:37,970
stated objectives and are planned carefully. This is something that
52
00:02:37,970 --> 00:02:40,730
should be quite obvious, but doesn't always happen in practice.

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So just for completeness, I want to mention some other
2
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techniques besides the traditional ones that we just saw that
3
00:00:05,340 --> 00:00:07,880
can be used for requirements solicitation. And these other
4
00:00:07,880 --> 00:00:10,740
techniques can be divided in three main groups. There are
5
00:00:10,740 --> 00:00:14,820
collaborative techniques that were created to support incremental development
6
00:00:14,820 --> 00:00:18,850
of complex systems with large diverse user populations. An example
7
00:00:18,850 --> 00:00:21,130
of such techniques which is widely used and you
8
00:00:21,130 --> 00:00:25,120
might know is brainstorming. There are also social approaches and
9
00:00:25,120 --> 00:00:28,140
these are approaches, techniques that exploit the social
10
00:00:28,140 --> 00:00:31,520
sciences to better collect information from the stakeholders and
11
00:00:31,520 --> 00:00:34,310
the environment. And among those I just want to mention
12
00:00:34,310 --> 00:00:36,730
ethnographic techniques which are based on the idea of
13
00:00:36,730 --> 00:00:40,100
collecting information on the participants by observing them
14
00:00:40,100 --> 00:00:44,660
in their original environment. Finally cognitive techniques, leverage cognitive
15
00:00:44,660 --> 00:00:48,490
science approaches to discover expert knowledge for example they
16
00:00:48,490 --> 00:00:51,260
can be used to understand the problem solving methods.
17
00:00:51,260 --> 00:00:54,000
And in case you're interested in finding out more about this and
18
00:00:54,000 --> 00:00:57,580
other techniques, I'm providing some references in the notes for the lesson.

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Once we collected the required knowledge on the requirements for
2
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the system that we're developing, we need to model it in
3
00:00:06,120 --> 00:00:08,430
a structured and clear way, so that it can be
4
00:00:08,430 --> 00:00:12,100
analyzed and refined. And there are really tons of ways to
5
00:00:12,100 --> 00:00:15,840
do that, depending on your focus and objectives. More specifically,
6
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when modeling requirements you need to decide what you want to
7
00:00:18,940 --> 00:00:21,710
model and how you want to model it. So let's look
8
00:00:21,710 --> 00:00:25,390
at these two aspects independently. What you decide to model depends
9
00:00:25,390 --> 00:00:28,270
on where your emphasis is. That is on which
10
00:00:28,270 --> 00:00:31,390
aspects of the requirements you want to focus. For
11
00:00:31,390 --> 00:00:34,880
example if your emphasis is on the characteristics of
12
00:00:34,880 --> 00:00:37,970
the enterprise of the company that you are analyzing you
13
00:00:37,970 --> 00:00:40,240
may want to model goals and objectives of the
14
00:00:40,240 --> 00:00:44,380
company, or its organizational structure, its task and dependencies
15
00:00:44,380 --> 00:00:47,040
and so on. Conversely, if your focus is on
16
00:00:47,040 --> 00:00:50,500
information and behaviors, you might want to concentrate on aspects
17
00:00:50,500 --> 00:00:53,800
such as the structure of information, various behavioral views
18
00:00:53,800 --> 00:00:55,480
some of which we will see in the next
19
00:00:55,480 --> 00:00:59,650
lesson, or maybe time or sequencing requirements. Finally, if
20
00:00:59,650 --> 00:01:02,750
you're mostly interested in the quality aspects of your
21
00:01:02,750 --> 00:01:06,790
system, you will focus on the various non-functional properties
22
00:01:06,790 --> 00:01:09,070
of the software that are relevant in the context
23
00:01:09,070 --> 00:01:13,570
considered. For example reliability, robustness, security, and so on.
24
00:01:13,570 --> 00:01:15,550
You will just pick the ones that are relevant for
25
00:01:15,550 --> 00:01:18,540
your context. And as we said, there's a second dimension.
26
00:01:18,540 --> 00:01:21,050
After you have decided what to model in your system,
27
00:01:21,050 --> 00:01:23,480
you have to decide how you want to model it.
28
00:01:23,480 --> 00:01:25,860
So I want to show here some options for modeling
29
00:01:25,860 --> 00:01:30,380
enterprises, information, and quality aspects. And as you can see
30
00:01:30,380 --> 00:01:34,100
here for each type of information there are many possible
31
00:01:34,100 --> 00:01:36,840
models that we can use to represent it. And all
32
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these models have advantages and
33
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disadvantages, different levels of formality and
34
00:01:41,400 --> 00:01:44,000
different focus. Something else that I want to point out
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about these models is the fact that these models are often
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orthogonal to one another, especially if we consider models in different
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categories. So what that means is that they're complimentary rather than
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mutually exclusive. Different models can be used to provide views
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of the requirements from different perspectives, and we will not see
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00:02:01,290 --> 00:02:03,700
most of these models in this course, but I wanted to
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list them anyways to give you an idea of how many
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there are and how vast is this area. As far
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as we are concerned in the course and for the
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projects we will express requirements using one of two main
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ways. Using natural language, that is informal specifications and using
46
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UML diagrams, which is graphical models. And we will introduce
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UML and the most important diagrams in the next lesson.
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And the only other type of models that I want
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to mentions explicitly are goal models because they're extremely popular.
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So the main idea with goal models is it start with the main goal of
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the system and then keep refining it
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by decomposing it in sub-goals. So it's kind
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of a very natural way of progressing.
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And you continue this refinement until you get
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to goals that can be operationalized, and represent
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the basic units of functionality of the system.

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