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Assessing the Impact of File Ordering Strategies on Code Review Process

Published: 14 June 2023 Publication History
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    Popular modern code review tools (e.g., Gerrit and GitHub) sort files in a code review in alphabetical order. A prior study (on open-source projects) shows that the changed files’ positions in the code review affect the review process. Their results show that files placed lower in the order have less chance of receiving reviewing efforts than the other files. Hence, there is a higher chance of missing defects in these files. This paper explores the impact of file order in the code review of the well-known industrial project IntelliJ IDEA. First, we verify the results of the prior study on a big proprietary software project. Then, we explore an alternative to the default Alphabetical order: ordering changed files according to their code diff. Our results confirm the observations of the previous study. We discover that reviewers leave more comments on the files shown higher in the code review. Moreover, these results show that, even with the data skewed toward Alphabetical order, ordering changed files according to their code diff performs better than standard Alphabetical order regarding placing problematic files, which needs more reviewing effort, in the code review. These results confirm that exploring various ordering strategies for code review needs more exploration.

    References

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    1. Assessing the Impact of File Ordering Strategies on Code Review Process

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      cover image ACM Other conferences
      EASE '23: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering
      June 2023
      544 pages
      ISBN:9798400700446
      DOI:10.1145/3593434
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 14 June 2023

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      Author Tags

      1. Code Review
      2. Cognitive Bias
      3. Ranking Metrics

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      Overall Acceptance Rate 71 of 232 submissions, 31%

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