The impact of human factors on the participation decision of reviewers in modern code review
Empirical Software Engineering, 2019•Springer
Abstract Modern Code Review (MCR) plays a key role in software quality practices. In MCR
process, a new patch (ie, a set of code changes) is encouraged to be examined by
reviewers in order to identify weaknesses in source code prior to an integration into main
software repositories. To mitigate the risk of having future defects, prior work suggests that
MCR should be performed with sufficient review participation. Indeed, recent work shows
that a low number of participated reviewers is associated with poor software quality …
process, a new patch (ie, a set of code changes) is encouraged to be examined by
reviewers in order to identify weaknesses in source code prior to an integration into main
software repositories. To mitigate the risk of having future defects, prior work suggests that
MCR should be performed with sufficient review participation. Indeed, recent work shows
that a low number of participated reviewers is associated with poor software quality …
Abstract
Modern Code Review (MCR) plays a key role in software quality practices. In MCR process, a new patch (i.e., a set of code changes) is encouraged to be examined by reviewers in order to identify weaknesses in source code prior to an integration into main software repositories. To mitigate the risk of having future defects, prior work suggests that MCR should be performed with sufficient review participation. Indeed, recent work shows that a low number of participated reviewers is associated with poor software quality. However, there is a likely case that a new patch still suffers from poor review participation even though reviewers were invited. Hence, in this paper, we set out to investigate the factors that are associated with the participation decision of an invited reviewer. Through a case study of 230,090 patches spread across the Android, LibreOffice, OpenStack and Qt systems, we find that (1) 16%-66% of patches have at least one invited reviewer who did not respond to the review invitation; (2) human factors play an important role in predicting whether or not an invited reviewer will participate in a review; (3) a review participation rate of an invited reviewers and code authoring experience of an invited reviewer are highly associated with the participation decision of an invited reviewer. These results can help practitioners better understand about how human factors associate with the participation decision of reviewers and serve as guidelines for inviting reviewers, leading to a better inviting decision and a better reviewer participation.
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