An empirical GitHub mining study finds vLLM is the most adopted LLM serving framework, parallel and memory optimizations dominate, and multi-framework use is rare.
Generating GitHub Repository Descriptions: A Comparison of Manual and Automated Approaches
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Given the vast number of repositories hosted on GitHub, project discovery and retrieval have become increasingly important for GitHub users. Repository descriptions serve as one of the first points of contact for users who are accessing a repository. However, repository owners often fail to provide a high-quality description; instead, they use vague terms, the purpose of the repository is poorly explained, or the description is omitted entirely. In this work, we examine the current practice of writing GitHub repository descriptions. Our investigation leads to the proposal of the LSP (Language, Software technology, and Purpose) template to formulate good descriptions for GitHub repositories that are clear, concise, and informative. To understand the extent to which current automated techniques can support generating repository descriptions, we compare the performance of state-of-the-art text summarization methods on this task. Finally, our user study with GitHub users reveals that automated summarization can adequately be used for default description generation for GitHub repositories, while the descriptions which follow the LSP template offer the most effective instrument for communicating with GitHub users.
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cs.SE 1years
2026 1verdicts
REJECT 1representative citing papers
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LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs
An empirical GitHub mining study finds vLLM is the most adopted LLM serving framework, parallel and memory optimizations dominate, and multi-framework use is rare.