抄録
Manual code inspections are intense and time-consuming activities to improve the maintainability and reusability of source code. Although automatic detection of high-risk source code file by metrics thresholds can help inspectors, determining the optimal thresholds is difficult Thus, we propose an iterative process to define and improve GQM models with metrics thresholds to detect high-risk files Our process clarifies experts' viewpoints in the inspection and the measurement metrics using the GQM method, define how to interpret the metrics values, searches concrete thresholds for a specific project by supervised learning using some of the file in the project as training data, and analyzes how to improve models and thresholds. We implemented our tool in R language and evaluated our process using a industrial project. Small-sized embedded C++ systems require only a few training data.
本文言語 | English |
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ホスト出版物のタイトル | Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016 |
出版社 | Institute of Electrical and Electronics Engineers Inc. |
ページ | 3813-3816 |
ページ数 | 4 |
ISBN(電子版) | 9781509025961 |
DOI | |
出版ステータス | Published - 2017 2月 8 |
イベント | 2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore 継続期間: 2016 11月 22 → 2016 11月 25 |
Other
Other | 2016 IEEE Region 10 Conference, TENCON 2016 |
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国/地域 | Singapore |
City | Singapore |
Period | 16/11/22 → 16/11/25 |
ASJC Scopus subject areas
- コンピュータ サイエンスの応用
- 電子工学および電気工学