Automatic Detection of Outdated Comments During Code Changes
In: 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 2018-07-01
Online
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Zugriff:
Comments are used as standard practice in software development to increase the readability of code and to express programmers' intentions in a more explicit manner. Nevertheless, keeping comments up-to-date is often neglected for programmers. In this paper, we proposed a machine learning based method for detecting the comments that should be changed during code changes. We utilized 64 features, taking the code before and after changes, comments and the relationship between the code and comments into account. Experimental results show that 74.6% of outdated comments can be detected using our method, and 77.2% of our detected outdated comments are real comments which require to be updated. In addition, the experimental results indicate that our model can help developers to discover outdated comments in historical versions of existing projects.
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Automatic Detection of Outdated Comments During Code Changes
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Autor/in / Beteiligte Person: | Luo, Xiaonan ; Chen, Huanchao ; Zhou, Fan ; Chen, Xiangping ; Liu, Zhiyong |
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Zeitschrift: | 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), 2018-07-01 |
Veröffentlichung: | IEEE, 2018 |
Medientyp: | unknown |
DOI: | 10.1109/compsac.2018.00028 |
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