Which bugs are missed in code reviews: An empirical study on SmartSHARK dataset
F. Khoshnoud, A. Rezaei Nasab, Z. Toudeji, A. Sami

TL;DR
This study investigates missed bugs in code reviews within open-source projects, categorizing them and analyzing their distribution to improve understanding of review shortcomings and bug types.
Contribution
The paper introduces a taxonomy of missed bugs in pull requests and provides empirical data on their distribution across different bug categories.
Findings
187 bugs missed in 173 pull requests identified
Semantic bugs constitute over half of missed bugs
Build and analysis check bugs are also significant
Abstract
In pull-based development systems, code reviews and pull request comments play important roles in improving code quality. In such systems, reviewers attempt to carefully check a piece of code by different unit tests. Unfortunately, sometimes they miss bugs in their review of pull requests, which lead to quality degradations of the systems. In other words, disastrous consequences occur when bugs are observed after merging the pull requests. The lack of a concrete understanding of these bugs led us to investigate and categorize them. In this research, we try to identify missed bugs in pull requests of SmartSHARK dataset projects. Our contribution is twofold. First, we hypothesized merged pull requests that have code reviews, code review comments, or pull request comments after merging, may have missed bugs after the code review. We considered these merged pull requests as candidate pull…
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Taxonomy
TopicsSoftware Engineering Research · Software System Performance and Reliability · Software Testing and Debugging Techniques
