Commentfinder: a simpler, faster, more accurate code review comments recommendation
Y Hong, C Tantithamthavorn… - Proceedings of the 30th …, 2022 - dl.acm.org
Proceedings of the 30th ACM joint European software engineering conference …, 2022•dl.acm.org
Code review is an effective quality assurance practice, but can be labor-intensive since
developers have to manually review the code and provide written feedback. Recently, a
Deep Learning (DL)-based approach was introduced to automatically recommend code
review comments based on changed methods. While the approach showed promising
results, it requires expensive computational resource and time which limits its use in
practice. To address this limitation, we propose CommentFinder–a retrieval-based approach …
developers have to manually review the code and provide written feedback. Recently, a
Deep Learning (DL)-based approach was introduced to automatically recommend code
review comments based on changed methods. While the approach showed promising
results, it requires expensive computational resource and time which limits its use in
practice. To address this limitation, we propose CommentFinder–a retrieval-based approach …
Code review is an effective quality assurance practice, but can be labor-intensive since developers have to manually review the code and provide written feedback. Recently, a Deep Learning (DL)-based approach was introduced to automatically recommend code review comments based on changed methods. While the approach showed promising results, it requires expensive computational resource and time which limits its use in practice. To address this limitation, we propose CommentFinder – a retrieval-based approach to recommend code review comments. Through an empirical evaluation of 151,019 changed methods, we evaluate the effectiveness and efficiency of CommentFinder against the state-of-the-art approach. We find that when recommending the best-1 review comment candidate, our CommentFinder is 32% better than prior work in recommending the correct code review comment. In addition, CommentFinder is 49 times faster than the prior work. These findings highlight that our CommentFinder could help reviewers to reduce the manual efforts by recommending code review comments, while requiring less computational time.
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