期刊
EMPIRICAL SOFTWARE ENGINEERING
卷 28, 期 5, 页码 -出版社
SPRINGER
DOI: 10.1007/s10664-023-10336-5
关键词
Emoji reaction; Code reviews; Mining software repositories
This study analyzed a large number of pull requests on GitHub and found correlations between emoji reactions and review time, first-time contributors, comment intentions, and sentiment consistency. The results suggest that emoji reactions not only reduce commenting noise, but also play a positive role in facilitating collaborative communication during the review process.
Open source software development has become more social and collaborative, evident GitHub. Since 2016, GitHub started to support more informal methods such as emoji reactions, with the goal to reduce commenting noise when reviewing any code changes to a repository. From a code review context, the extent to which emoji reactions facilitate a more efficient review process is unknown. We conduct an empirical study to mine 1,850 active repositories across seven popular languages to analyze 365,811 Pull Requests (PRs) for their emoji reactions against the review time, first-time contributors, comment intentions, and the consistency of the sentiments. Answering these four research perspectives, we first find that the number of emoji reactions has a significant correlation with the review time. Second, our results show that a PR submitted by a first-time contributor is less likely to receive emoji reactions. Third, the results reveal that the comments with an intention of information giving, are more likely to receive an emoji reaction. Fourth, we observe that only a small proportion of sentiments are not consistent between comments and emoji reactions, i.e., with 11.8% of instances being identified. In these cases, the prevalent reason is when reviewers cheer up authors that admit to a mistake, i.e., acknowledge a mistake. Apart from reducing commenting noise, our work suggests that emoji reactions play a positive role in facilitating collaborative communication during the review process.
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