| Project/Area Number |
15500022
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Software
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| Research Institution | Osaka University |
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Principal Investigator |
KIKUNO Tohru Osaka University, Graduate School of Information Science and Technology, Professor, 大学院・情報科学研究科, 教授 (50093745)
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| Co-Investigator(Kenkyū-buntansha) |
MIZUNO Osamu Osaka University, Graduate School of Information Science and Technology, Assistant Professor, 大学院・情報科学研究科, 助手 (60314407)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2005: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2004: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2003: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | Software Development / Software Quality / Metrics / Software Testing / Software Review / Statistical Analysis |
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| Research Abstract |
In this research, we tried to develop a quality estimation method for software development which emphasizes on practical use, especially, ease for the implementation in the actual development field. To do so, we consider the following three viewpoints :
1.Prediction of software quality suing the metrics data collected from the design and coding phases in the software development.
We proposed a method to predict final quality of products using time series data of detected defects in design and coding phases. In more detail, we classified all projects into 4 groups according to the trend of defects detection. We then analyzed resultant quality of the classes.
2. Prediction of software quality using subjective data such as validity of development plan and difference between planned and actual progress of software development.
Here, in order to improve the accuracy of prediction, we introduced additional data, subjective questionnaire about software risks at the beginning of project. We considered that the software risks deeply related to the final quality of product. We modeled the relationship among risks and final quality using Bayesian belief network.
3. Method to improve quality using simulation technique
Finally we tried to simulate the software risk and to estimate quality of software products for each phase of software development. To do so, we developed a system to estimate software quality using Bayesian classifier at each phase of development. By using this method, practical estimation of software quality can be achieved.
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