GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More

• URL: http://arxiv.org/abs/2504.09651v1
• Date: Sun, 13 Apr 2025 16:55:28 GMT
• Title: GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More
• Authors: Avinash Patil,
• Abstract summary: We present GitBugs, a comprehen-sive and up-to-date dataset of over 150,000 bug reports from nine actively maintained open-source projects.<n>GitBugs aggregates data from Github, Bugzilla and Jira issue trackers, offering standardized categorical fields for classification tasks.<n>It includes ex- ploratory analysis notebooks and detailed project-level statistics, such as duplicate rates and resolution times.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Bug reports provide critical insights into software quality, yet existing datasets often suffer from limited scope, outdated content, or insufficient metadata for machine learning.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 comprehen- sive 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 ex- ploratory 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 bench- marking and advancing automated bug report analysis. Access the data and code at https://github.com/av9ash/gitbugs/.

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