What Makes a Code Review Useful to OpenDev Developers? An Empirical Investigation
Not on the map. Why?
Abstract (arXiv)
Context: Due to the association of significant efforts, even a minor improvement in the effectiveness of Code Reviews(CR) can incur significant savings for a software development organization. Aim: This study aims to develop a finer grain understanding of what makes a code review comment useful to OSS developers, to what extent a code review comment is considered useful to them, and how various contextual and participant-related factors influence its usefulness level. Method: On this goal, we have conducted a three-stage mixed-method study. We randomly selected 2,500 CR comments from the OpenDev Nova project and manually categorized the comments. We designed a survey of OpenDev developers to better understand their perspectives on useful CRs. Combining our survey-obtained scores with our manually labeled dataset, we trained two regression models - one to identify factors that influence the usefulness of CR comments and the other to identify factors that improve the odds of `Functional' defect identification over the others. Key findings: The results of our study suggest that a CR comment's usefulness is dictated not only by its technical contributions such as defect findings or quality improvement tips but also by its linguistic characteristics such as comprehensibility and politeness. While a reviewer's coding experience positively associates with CR usefulness, the number of mutual reviews, comment volume in a file, the total number of lines added /modified, and CR interval has the opposite associations. While authorship and reviewership experiences for the files under review have been the most popular attributes for reviewer recommendation systems, we do not find any significant association of those attributes with CR usefulness.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2023.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 2; 2025: 4; 2026: 4.
10 papers.
- 2024CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smellscited by 8
- 2025LAURA: Enhancing Code Review Generation with Context-Enriched Retrieval-Augmented LLMcited by 8
- 2024Leveraging Reviewer Experience in Code Review Comment Generationcited by 4
- 2026Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agentscited by 3
- 2025Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvementscited by 2
- 2025CodeWatcher: IDE Telemetry Data Extraction Tool for Understanding Coding Interactions with LLMscited by 2
- 2026Rethinking Code Review in the Age of AI: A Vision for Agentic Code Reviewcited by 1
- 2026Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wildcited by 1
- 2025Exploring the Potential of Large Language Models in Fine-Grained Review Comment Classificationcited by 0
- 2026From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Benchcited by 0
- 2026From Static to Dynamic: Benchmarking Real-World Code Review with MCR-Bench27 Aug 2026
- 2026Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild3 Jul 2026
- 2026Rethinking Code Review in the Age of AI: A Vision for Agentic Code Review17 May 2026
- 2026Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agents27 Jan 2026
- 2025LAURA: Enhancing Code Review Generation with Context-Enriched Retrieval-Augmented LLM1 Dec 2025
- 2025CodeWatcher: IDE Telemetry Data Extraction Tool for Understanding Coding Interactions with LLMs13 Oct 2025
- 2025Exploring the Potential of Large Language Models in Fine-Grained Review Comment Classification13 Aug 2025
- 2025Augmenting Large Language Models with Static Code Analysis for Automated Code Quality Improvements12 Jun 2025
- 2024CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells29 Sep 2024
- 2024Leveraging Reviewer Experience in Code Review Comment Generation17 Sep 2024