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DevGPT: Studying Developer-ChatGPT Conversations

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arxiv 2309.03914 v2 pith:JDHP2M2D submitted 2023-08-31 cs.SE

Tao Xiao , Christoph Treude , Hideaki Hata , Kenichi Matsumoto This is my paper
classification cs.SE
keywords chatgptdatasetcodedevgptsoftwareconversationsdeveloperdevelopers
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper introduces DevGPT, a dataset curated to explore how software developers interact with ChatGPT, a prominent large language model (LLM). The dataset encompasses 29,778 prompts and responses from ChatGPT, including 19,106 code snippets, and is linked to corresponding software development artifacts such as source code, commits, issues, pull requests, discussions, and Hacker News threads. This comprehensive dataset is derived from shared ChatGPT conversations collected from GitHub and Hacker News, providing a rich resource for understanding the dynamics of developer interactions with ChatGPT, the nature of their inquiries, and the impact of these interactions on their work. DevGPT enables the study of developer queries, the effectiveness of ChatGPT in code generation and problem solving, and the broader implications of AI-assisted programming. By providing this dataset, the paper paves the way for novel research avenues in software engineering, particularly in understanding and improving the use of LLMs like ChatGPT by developers.

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  1. Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows

    cs.SE 2025-07 conditional novelty 7.0 of 10

    A 20-developer controlled study found that the coding agent OpenHands improved task completion by 35 percentage points and halved user effort versus GitHub Copilot, while reducing user understanding of outputs.

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