180 lines
4.3 KiB
Plaintext
180 lines
4.3 KiB
Plaintext
1
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Unfortunately, extracting requirements from these sources is not
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2
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00:00:03,440 --> 00:00:06,220
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a straightforward task, as there are many issues involved
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3
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00:00:06,220 --> 00:00:09,470
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with the requirements elicitation. One first problem is the
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4
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00:00:09,470 --> 00:00:13,930
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thin spread of domain knowledge. Knowledge is rarely available
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00:00:13,930 --> 00:00:15,970
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in an explicit form, that is, it is
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00:00:15,970 --> 00:00:20,310
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almost never written down. Moreover, knowledge is often distributed
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00:00:20,310 --> 00:00:23,410
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across many sources. For example, in the graphical depiction
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8
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00:00:23,410 --> 00:00:25,590
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here, to find out that this is the purpose
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9
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00:00:25,590 --> 00:00:28,240
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of the project. The developer, the analyist, needs to talk
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00:00:28,240 --> 00:00:30,870
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to a lot of different people. And, to make things even
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00:00:30,870 --> 00:00:34,400
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worse. There are often conflicts between the knowledge gathered from
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00:00:34,400 --> 00:00:37,610
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different sources. A second issue is the fact that the knowledge
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00:00:37,610 --> 00:00:41,090
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is often tacit. What is also called the say, do
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00:00:41,090 --> 00:00:44,052
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problem. In the example shown here. For instance. We have a
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00:00:44,052 --> 00:00:47,650
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customer that is describing to the analyst. The way in which
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00:00:47,650 --> 00:00:51,060
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he accomplishes a task. So it performs these three steps and
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00:00:51,060 --> 00:00:54,300
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reaches the goal. Whereas in practice, the actual way in
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00:00:54,300 --> 00:00:57,530
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which this task accomplished is by going through a larger number
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00:00:57,530 --> 00:00:59,880
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of steps to get to the same goal. So the point
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00:00:59,880 --> 00:01:02,650
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here is that, even if the knowledge were more concentrated, so
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00:01:02,650 --> 00:01:05,660
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not as spread as in this example. People simply find
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it hard to describe knowledge that they regularly use. So it
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00:01:08,680 --> 00:01:11,740
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is hard to make this knowledge explicit, to pass this knowledge
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00:01:11,740 --> 00:01:13,130
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to someone else. Yet another
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00:01:13,130 --> 00:01:16,690
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problem is limited observability. Identifying requirements
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00:01:16,690 --> 00:01:20,570
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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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00:01:23,550 --> 00:01:25,750
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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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00:01:27,980 --> 00:01:31,530
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confusing. That introduces noise. Moreover, even when this is not the
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00:01:31,530 --> 00:01:34,460
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case, the presence of an observer might change their problem. It
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00:01:34,460 --> 00:01:38,020
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is very typical for human subjects to improve or modify an
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00:01:38,020 --> 00:01:41,760
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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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00:01:50,910 --> 00:01:54,270
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For several reasons. People might not feel free to tell you what you
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00:01:54,270 --> 00:01:57,030
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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
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from the real one. In order to influence you. So, they might have
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a hidden agenda, and mislead you, either
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consciously or unconsciously. So, all these issues
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00:02:11,860 --> 00:02:14,370
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add to the complexity of collecting requirements,
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45
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of identifying the purpose of a system.
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