Improving Code Review by Predicting Reviewers and Acceptance of Patches
Gaeul Jeong, Sunghun Kim, Thomas Zimmermann, Kwangkeun Yi · 2009
Code reviews are an important part of software development because they help to increase code quality and reliability. For this paper, we observed the review processes of two open-source projects, Firefox and Mozilla Core. We noticed that code reviews are mostly organized manually. In particular, finding appropriate reviewers is a complex and time-consuming task and, surprisingly, impacts the review outcome: review requests without an initial reviewer assignment have lower chances to be accepted (and take longer). Based on our observations we propose two improvements: (1) predict whether a given patch is acceptable and (2) suggest reviewers for a patch. We implemented and tested both approaches for the Firefox and Mozilla Core projects. In our experiments, the prediction accuracy was 73% for the the review outcome and 51‐80% for the reviewer recommendation. The values for accuracy are higher than those of comparable approaches and are high enough to be useful and applicable in practice.