AI 中文总结
研究GenAI在GitHub仓库中的应用，通过分析多组数据，发现人工智能辅助仓库有不同特点，相关问题常涉外部依赖，表明GenAI会将维护成本转移到验证内容、管理依赖及验证特定行为上。
AI 中文摘要
生成式人工智能（GenAI）可以减少代码生成工作量，但可能会将工作转移到文档、验证、调试和维护上。我们通过分析622个公开表明采用GenAI的用户、179个具有可见人工智能辅助配置文件的仓库、179个匹配的传统仓库以及在人工智能辅助仓库中创建的248个问题，研究了GitHub上GenAI采用者中可观察到的维护成本信号。人工智能辅助仓库涵盖多种项目类型，包含更长且有更多标题和代码块的README文件，而传统仓库包含更多外部URL。关于GenAI技术的问题通常涉及外部依赖，如API速率限制和对GenAI提供商API的依赖。这些发现表明，人工智能辅助将维护成本转移到验证生成内容、管理外部人工智能依赖以及验证特定于人工智能的行为上。
英文摘要
Generative artificial intelligence (GenAI) can reduce code-generation effort, but it may shift work to documentation, validation, debugging, and maintenance. We study observable maintenance-cost signals among GenAI adopters on GitHub by analyzing 622 users who publicly signal adoption, 179 repositories with visible AI-assistance configuration files, 179 matched traditional repositories, and 248 issues created in AI-assisted repositories. AI-assisted repositories span diverse project types and contain longer README files with more headers and code blocks, while traditional repositories contain more external URLs. Issues concerning GenAI technology often involve external dependencies, such as API rate limits and reliance on GenAI provider APIs. These findings suggest that AI assistance shifts maintenance costs toward verifying generated content, managing external AI dependencies, and validating AI-specific behavior.
Comments26 pages, 3 figures, 6 tables
