| Project/Area Number |
26330086
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Software
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| Research Institution | Okayama University (2015-2016)
Nara Institute of Science and Technology (2014) |
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Principal Investigator |
Monden Akito 岡山大学, 自然科学研究科, 教授 (80311786)
|
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| Co-Investigator(Renkei-kenkyūsha) |
KAMEI YASUTAKA 九州大学, 大学院システム情報科学研究院, 准教授 (10610222)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | ソフトウェアテスト / ソフトウェア品質保証 / ソフトウェアバグ予測 / シミュレーション / ソフトウェア工学 |
|---|
| Outline of Final Research Achievements |
To enable evaluation of effectiveness of test strategies based on software bug prediction, we formalized the problem of test strategies as a nonlinear optimization problem; and then, we showed that the problem can be solved as a separable convex problem. Next, as the bug prediction inherently contain errors, we proposed and evaluated a method that combines test strategies not using bug prediction. Then, to clarify the context where bug prediction become effective, we proposed a method to estimate the maximum amount of reducible test effort by bug prediction. From these achievements, practitioners are able to estimate the expected reducible test effort, which will promote employing bug prediction in industry.
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