GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More
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Abstract (arXiv)
Bug reports provide critical insights into software quality, yet existing datasets often suffer from limited scope, outdated content, or insufficient metadata for machine learning. To address these limitations, we present GitBugs-a comprehensive and up-to-date dataset comprising over 150,000 bug reports from nine actively maintained open-source projects, including Firefox, Cassandra, and VS Code. GitBugs aggregates data from Github, Bugzilla and Jira issue trackers, offering standardized categorical fields for classification tasks and predefined train/test splits for duplicate bug detection. In addition, it includes exploratory analysis notebooks and detailed project-level statistics, such as duplicate rates and resolution times. GitBugs supports various software engineering research tasks, including duplicate detection, retrieval augmented generation, resolution prediction, automated triaging, and temporal analysis. The openly licensed dataset provides a valuable cross-project resource for benchmarking and advancing automated bug report analysis. Access the data and code at https://github.com/av9ash/gitbugs/.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). First posted on arXiv 13 Apr 2025.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2026Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reportscited by 1
- 2026When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judgescited by 1
- 2025When Bugs Linger: A Study of Anomalous Resolution Time Outliers and Their Themescited by 0
- 2026When Gradients Collide: Failure Modes of Multi-Objective Prompt Optimization for LLM Judges25 May 2026
- 2026Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports17 May 2026
- 2025When Bugs Linger: A Study of Anomalous Resolution Time Outliers and Their Themes19 Sep 2025
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- 2025From Reviewers' Lens: Understanding Bug Bounty Report Invalid Reasons with LLMs
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- 2025An Empirical Study of Bugs in Data Visualization Libraries
- 2026AgentSZZ: Teaching the LLM Agent to Play Detective with Bug-Inducing Commits