The relationship between evolutionary coupling and defects in large industrial software
The relationship between evolutionary coupling and defects in large industrial software
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DOI：
10.1002/smr.1842
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发表时间：
2017-04
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影响因子：
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通讯作者：
Serkan Kirbas;Bora Caglayan;T. Hall;S. Counsell;David Bowes;A. Sen;A. Bener
中科院分区：
文献类型：
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作者：
Serkan Kirbas;Bora Caglayan;T. Hall;S. Counsell;David Bowes;A. Sen;A. Bener
进化耦合（EC）被定义为经常更改软件的2个或更多软件之间的隐式关系。工业软件系统并解释了为什么我们分析了2个大型工业系统：旧版金融系统和现代电信系统，我们从5个不同的软件存储库中收集了7年的历史数据。探索EC和软件缺陷之间的关系，我们分析了缺陷类型，大小和过程指标，以通过相关性来解释EC对缺陷的不同影响。进化耦合不太可能与软件的软件缺陷有更少的文件和更少的开发人员的贡献。 。
Evolutionary coupling (EC) is defined as the implicit relationship between 2 or more software artifacts that are frequently changed together. Changing software is widely reported to be defect‐prone. In this study, we investigate the effect of EC on the defect proneness of large industrial software systems and explain why the effects vary. We analysed 2 large industrial systems: a legacy financial system and a modern telecommunications system. We collected historical data for 7 years from 5 different software repositories containing 176 thousand files. We applied correlation and regression analysis to explore the relationship between EC and software defects, and we analysed defect types, size, and process metrics to explain different effects of EC on defects through correlation. Our results indicate that there is generally a positive correlation between EC and defects, but the correlation strength varies. Evolutionary coupling is less likely to have a relationship to software defects for parts of the software with fewer files and where fewer developers contributed. Evolutionary coupling measures showed higher correlation with some types of defects (based on root causes) such as code implementation and acceptance criteria. Although EC measures may be useful to explain defects, the explanatory power of such measures depends on defect types, size, and process metrics.