超越代码生成：软件工程实践中ChatGPT使用情况的观察性研究
Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice
AI总结：
本研究通过观察24名专业软件工程师一周内的ChatGPT使用情况，发现从业者更倾向于用其获取任务指导而非直接生成代码，并提出了涵盖交互目的、内外部因素的LLM使用体验理论框架，为相关研究提供参考。
摘要：
大语言模型（Large Language Models, LLMs）作为支持工具，在学术界和公众中被广泛讨论，可用于几乎所有依赖文本生成的场景，包括软件工程领域。目前，关于ChatGPT这类基于LLM的工具对行业工程师的实际实用性，争议颇多但实证证据不足。我们开展了一项观察性研究，招募24名在工作中使用ChatGPT达一周的专业软件工程师，定性分析他们与聊天机器人的对话以及通过退出调研收集的整体使用体验。研究发现，从业者并不期望ChatGPT生成可直接使用的软件制品（如代码），反而更多用它获取任务解决思路，或以更抽象的方式学习某个主题。我们还提出了一个理论框架，阐释（i）交互目的、（ii）内部因素（如用户性格）、（iii）外部因素（如公司政策）如何共同影响使用体验，即感知有用性和信任度。我们期望该框架能为未来研究所用，推动学术界对软件工程从业者使用LLM的讨论，并作为该领域未来LLM实证研究设计的参考基准。
英文摘要：
Large Language Models (LLMs) are frequently discussed in academia and the general public as support tools for virtually any use case that relies on the production of text, including software engineering. Currently there is much debate, but little empirical evidence, regarding the practical usefulness of LLM-based tools such as ChatGPT for engineers in industry. We conduct an observational study of 24 professional software engineers who have been using ChatGPT over a period of one week in their jobs, and qualitatively analyse their dialogues with the chatbot as well as their overall experience (as captured by an exit survey). We find that, rather than expecting ChatGPT to generate ready-to-use software artifacts (e.g., code), practitioners more often use ChatGPT to receive guidance on how to solve their tasks or learn about a topic in more abstract terms. We also propose a theoretical framework for how (i) purpose of the interaction, (ii) internal factors (e.g., the user's personality), and (iii) external factors (e.g., company policy) together shape the experience (in terms of perceived usefulness and trust). We envision that our framework can be used by future research to further the academic discussion on LLM usage by software engineering practitioners, and to serve as a reference point for the design of future empirical LLM research in this domain.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
