构建首个大规模真实代码协作数据集，揭示AI写代码的实践全貌。
AIDev: Studying AI Coding Agents on GitHub
- 收集5个AI编码助手在真实项目中的93万条提交请求
- 覆盖超11万仓库、7万开发者，含评论与评审等完整上下文
- 适合研究人机协同编程、开发效率提升的学者与工程师
AI编码助手正快速改变软件工程，承担功能开发、调试和测试等任务。然而，研究界缺乏真实项目中这类工具使用情况的全面数据集。为此，我们推出AIDev，一个聚焦真实GitHub仓库中由AI生成的拉取请求（Agentic-PRs）的大规模数据集。AIDev收录了来自五个编码助手（OpenAI Codex、Devin、GitHub Copilot、Cursor、Claude Code）的932,791条Agentic-PRs，覆盖116,211个仓库及72,189名开发者。此外，数据集还包含33,596条精选的高星仓库（>100 stars）中的Agentic-PRs，涵盖评论、评审、提交记录及关联问题等丰富信息。该数据集为未来研究AI采纳、开发者生产力及人机协作提供了坚实基础。
原文摘要 · Abstract (English)
AI coding agents are rapidly transforming software engineering by performing tasks such as feature development, debugging, and testing. Despite their growing impact, the research community lacks a comprehensive dataset capturing how these agents are used in real-world projects. To address this gap, we introduce AIDev, a large-scale dataset focused on agent-authored pull requests (Agentic-PRs) in real-world GitHub repositories. AIDev aggregates 932,791 Agentic-PRs produced by five agents: OpenAI Codex, Devin, GitHub Copilot, Cursor, and Claude Code. These PRs span 116,211 repositories and involve 72,189 developers. In addition, AIDev includes a curated subset of 33,596 Agentic-PRs from 2,807 repositories with over 100 stars, providing further information such as comments, reviews, commits, and related issues. This dataset offers a foundation for future research on AI adoption, developer productivity, and human-AI collaboration in the new era of software engineering. > AI Agent, Agentic AI, Coding Agent, Agentic Coding, Agentic Software Engineering, Agentic Engineering
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。