Development of fault-prone prediction model using web cloud system
| Project/Area Number |
24500038
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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 | Kyoto Institute of Technology |
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Principal Investigator |
MIZUNO Osamu 京都工芸繊維大学, 工芸科学研究科, 准教授 (60314407)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2012: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | ソフトウェア / ソースコード / リポジトリマイニング / 識別子 / トピック分析 / ソフトウェアリポジトリ / 不具合予測 / ソフトウェア開発 / マイニング / 不具合 / ソフトウェア開発効率化・安定化 / ソフトウェア工学 / データマイニング / ソフトウェア品質 |
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| Outline of Final Research Achievements |
In this research, we proposed a system to predict fault-prone modules in software source code. To do so, we focused on the vocabulary of the identifiers in source code. First, we developed a system to find topics in the faulty source code. Second, we developed a system to restore abbreviated identifiers to the original identifiers using a deep learning technique. By these models, we found the ways to utilise identifiers in software for fault-prone module prediction.
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Report
(4 results)
Research Products
(14 results)
