Does My README File Need To Be Updated? Exploring LLM-Based README Maintenance
Haoyu Gao, Hong Yi Lin, Christoph Treude, Gregory Gay, Mansooreh Zahedi

TL;DR
This paper presents a lightweight LLM-based approach to identify and suggest precise updates for README files in open source projects, aiming to reduce outdated documentation issues through a human-in-the-loop workflow.
Contribution
It introduces a novel LLM-driven pipeline that detects when README updates are needed, locates update points, and justifies changes within a practical OSS development context.
Findings
High precision in identifying outdated PRs needing README updates
Effective localization of update points within documentation
Positive developer feedback and practical utility demonstrated
Abstract
The README file serves as a critical source of information for gaining an overview and helping developers onboard to an Open Source Software (OSS) project. Yet, documentation issues persist; in particular, ``outdated'' documentation is perceived by developers as one of the most frequent and severe challenges with gaining project understanding. While previous studies have aimed to mitigate this problem, they typically either rely on highly-engineered solutions focused on specific code components or employ generative methods that are ineffective for incremental maintenance. In this study, we propose a lightweight Large Language Model (LLM)-driven approach to facilitate precise, localised README file updates within a human-in-the-loop workflow. Specifically, given a pull request (PR), our pipeline determines whether an update is necessary; if so, it identifies the precise locations where…
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Taxonomy
TopicsSoftware Engineering Research · Open Source Software Innovations · Scientific Computing and Data Management
