Impact of Coding Style Checker on Code Review - A Case Study on the OpenStack Projects

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Code review is key to ensuring the absence of potential issues in source code. Code review is changing from a costly manual check by reviewer to a cost-efficient automatic check by coding style checkers. So that patch authors can verify the changed code before submitting their patches. Although cost-efficiency, the checkers do not detect all potential issues, requiring reviewers to verify the submitted patches based on their knowledge. It would be most efficient if patch authors will learn potential issues and remove the same type of issues from patches prior to code review. This study investigates potential issues that patch authors have repeatedly introduced in their patch submissions despite receiving feedback. To understand the impact of adopting checkers to patch authors' coding style improvement, this study compares two types of potential issues: Automatically Detected Issues by checkers (ADIs) and Manually Detected Issues by reviewers (MDIs). In a case study using an OpenStack code review dataset, we found that the patch authors have repeatedly introduced the same type of MDIs, while they do not repeat ADIs. This result suggests that the introduction of code style checkers might promote the patch authors' effective potential issues learning.

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