| Budget Amount *help |
¥4,050,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥450,000)
Fiscal Year 2007: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2006: ¥2,100,000 (Direct Cost: ¥2,100,000)
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| Research Abstract |
An information system is embedded in a specific business or activities in an organization, thus, the knowledge about such a business and an organization, i.e. domain knowledge, is crucially important in a requirements analysis for such a system. Therefore, the effective and efficient usage of domain knowledge is very important in requirements analysis.
In order to use domain knowledge documents effectively and efficiently, not only the contents but also the representation is important. In addition, knowledge of stakeholder who uses such domain knowledge is also important. In this research, we report the results about the method for domain knowledge creation, the method for providing such knowledge, the effect of different representations during requirements analysis, and personalization for domain knowledge during requirements definition.
We developed and evaluated a method for domain knowledge creation based on documents about existing similar systems.
Based on the domain knowledge, we p
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roposed a requirements definition method for a similar new system.
To investigate how to show such domain knowledge effectively, we designed four metrics that measure the effect of the requirements specification. By using the metrics, we did comparative experiments that evaluate the effect of the representations on the quality of requirements documents. We analyzed two requirements documents each of which is constructed by using different domain knowledge representations: one is dictionary style and the other is UML style. As a result, dictionary style seemed to be adequate for the comprehensive description and UML style seemed to be adequate for the as-is reuse of the domain knowledge.
We defined a measure for identifying difficulty of domain knowledge and another measure for expertise of a stakeholder. During a experimental study, we confirmed these two measures contribute to personalization for domain knowledge. Finally, we developed a prototype tool for supporting requirements definition based on the results above. Less
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