软件专业人员如何评估人工智能生成的代码？（注册报告）
How Do Software Professionals Evaluate AI-Generated Code? (Registered Report)
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中文总结 AI 辅助
探讨软件专业人员如何评估人工智能生成的代码，采用建构主义扎根理论研究，通过调查、半结构化及阶梯访谈收集数据，旨在基于专业人员的描述构建评估该类代码的理论。
中文摘要 AI 辅助
生成式人工智能工具的最新进展极大地改变了软件专业人员编写、评估和与代码交互的方式。诸如GitHub Copilot、ChatGPT和Claude等生成式人工智能工具越来越多地融入日常工作流程。尽管这些工具的采用和依赖不断增加，但软件专业人员如何评估它们生成的代码仍不清楚。为探索该主题，我们将进行一项建构主义扎根理论研究，包括调查、半结构化访谈和阶梯访谈。在完成初步调查数据收集后，我们旨在迭代采访20至50名软件专业人员，直至达到理论饱和。本研究旨在基于软件专业人员对评估实践、看法和偏好的描述，构建一个关于他们如何评估人工智能生成代码的理论。
英文摘要
Recent advances in generative AI tools have significantly changed how software professionals write, evaluate, and interact with code. Generative AI tools such as GitHub Copilot, ChatGPT, and Claude are increasingly being integrated into everyday workflows. Despite the growing adoption of and reliance on these tools, it remains unclear as to how software professionals evaluate the code they generate. To explore this topic, we will conduct a constructivist grounded theory study that incorporates a survey, semi-structured interviews, and laddering interviews. With the initial survey data collection complete, we aim to interview 20--50 software professionals iteratively until theoretical saturation is achieved. This research aims to build a theory of how software professionals evaluate AI-generated code, grounded in their accounts of evaluative practices, perceptions, and preferences.
