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Decoding the Silence: A Comprehensive Analysis of the Dynamics and Underlying Factors of Stalled Pull Requests

Year: 2025
Type: conference-paper
Abstract: Background:Pull Requests (PRs) are central to pull-based development in open-source projects, enabling code reviews and collaborative contributions. However, many PRs become inactive and are ultimately abandoned or closed. Although prior studies have explored this issue, the underlying causes of inactivity and the effectiveness of existing interventions remain insufficiently understood. Aims:This study aims to identify PR types that are more prone to stalling, investigate the fine-grained causes of inactivity from both authors’ and reviewers’ perspectives, and provide actionable recommendations to improve the PR process and reduce waste. Method:We analyzed 14,234 stalled PRs and 164,562 code review comments from 19 popular open-source GitHub repositories. An LLM-based classifier was developed to automatically categorize PRs by type. In addition, we conducted both qualitative and quantitative analyses of review comments to uncover the causes of inactivity from the perspectives of both authors and reviewers. Results:Our findings reveal that certain PR types, such as enhancements and refactorings, are more prone to stalling. We identified key factors contributing to inactivity, including vague or conflicting review comments and insufficient reviewer engagement. Inactivity often arises from miscommunication, process fatigue, overlooked contributions, and differing expectations between authors and reviewers. Conclusions:Understanding the causes of PR stalling can help inform strategies to mitigate abandonment. Our study offers practical recommendations to improve reviewer responsiveness, enhance comment clarity, and foster contributor engagement. These insights can streamline collaboration, enhance the efficiency of open-source development workflows, and open future research avenues.
DOI: 10.5281/zenodo.15286675
Author: Annonymous
Language: English
Open Access status: green
OpenAlex ID: W6930740607
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