Expectations, outcomes, and challenges of modern code review

By Alberto Bacchelli, Christian Bird. International Conference on Software Engineering, 2013

854 citations recorded by the source corpus.

Subfields: Computer Science Applications, Information Systems

View Paper: https://www.semanticscholar.org/paper/3ad467fe13ffa8ee705d62d8228a2c254a96f5bd

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Citations in the corpus

The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects (2014, background): “Indeed, Microsoft developers complain that reviews often focus on minor logic errors rather than discussing deeper design issues [2].”
Women’s Participation in Open Source Software: A Survey of the Literature (2021, methodology): “A code developer submits the code produced to another person (peer) to evaluate and find possible errors before merging the code to the project codebase [5].”
PyDriller: Python framework for mining software repositories (2018, background): “3264598 can empirically investigate, understand, and uncover useful and actionable insights for software engineering, such as understanding the impact of code smells [13–15], exploring how developers are doing code reviews [2, 4, 10, 21] and which testing practices they follow [20], predicting class”
Work Practices and Challenges in Pull-Based Development: The Contributor's Perspective (2014, methodology): “This merging behaviour is also in place within Microsoft [12] and in the Android project [13].”
The promises and perils of mining GitHub (2009, result): “The numbers are comparable with other work in code review [23, 22, 2], which suggests that the peer review process may have more fundamental underpinnings yet to be explored.”
Convergent contemporary software peer review practices (2013, methodology): “For more details, we refer the reader to an earlier empirical study [2] in which we investigated the purposes for code review (e.g., finding defects, sharing knowledge) along with the actual outcomes (e.g., creating awareness and gaining code understanding) at Microsoft.”
Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts (2017, background): “This is because programmers need to periodically review their code for defects, to look for regions of code to optimize, extend existing functionality or simply increase their knowledge base [5].”
An in-depth study of the promises and perils of mining GitHub (2015, result): “The numbers are comparable with other work on code review (Rigby et al. 2008; Rigby and Bird 2013; Bacchelli and Bird 2013) which suggests that the peer review process may have more fundamental underpinnings yet to be explored.”
Learning natural coding conventions (2014, background): “As part of this process, the reviewers can highlight portions of the code and begin a discussion (thread) regarding parts of the change (for more details regarding the process and tools used, see Bacchelli et al. [10]).”
A Security Perspective on Code Review: The Case of Chromium (2016, background): “The study by Bacchelli and Bird [5] showed similar MCR outcomes for industrial projects at Microsoft; Lassenius et al.”
Modern Code Review: A Case Study at Google (2017, methodology): “Previous studies investigated challenges in the review process overall [4, 26] and provided compelling evidence, also corroborated by our experience as engineers, that understanding code to review is a major hurdle.”
Learning to rank relevant files for bug reports using domain knowledge (2014, background): “A developer who is assigned a bug report usually needs to reproduce the abnormal behavior [22] and perform code reviews [2] in order to (cid:12)nd the cause.”
An empirical study of the impact of modern code review practices on software quality (2015, background): “Furthermore, a recent qualitative study at Microsoft indicates that sharing knowledge among team members is also considered a very important motivation of modern code review (Bacchelli and Bird, 2013).”