mlsanityData to 14 Oct 2026

A Complete Set of Related Git Repositories Identified via Community Detection Approaches Based on Shared Commits

arXiv 2002.02707 ↗First posted 7 Feb 2020cs.SIcited by 3

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Abstract (arXiv)

In order to understand the state and evolution of the entirety of open source software we need to get a handle on the set of distinct software projects. Most of open source projects presently utilize Git, which is a distributed version control system allowing easy creation of clones and resulting in numerous repositories that are almost entirely based on some parent repository from which they were cloned. Git commits are based on Merkle Tree and two commits are highly unlikely to be produced independently. Shared commits, therefore, appear like an excellent way to group cloned repositories and obtain an accurate map for such repositories. We use World of Code infrastructure containing approximately 2B commits and 100M repositories to create and share such a map. We discover that the largest group contains almost 14M repositories most of which are unrelated to each other. As it turns out, the developers can push git object to an arbitrary repository or pull objects from unrelated repositories, thus linking unrelated repositories. To address this, we apply Louvain community detection algorithm to this very large graph consisting of links between commits and projects. The approach successfully reduces the size of the megacluster with the largest group of highly interconnected projects containing under 100K repositories. We expect the tools that the resulting map of related projects as well as tools and methods to handle the very large graph will serve as a reference set for mining software projects and other applications. Further work is needed to determine different types of relationships among projects induced by shared commits and other relationships, for example, by shared source code or similar filenames.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Feb 2020.

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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 0; 2025: 1; 2026: 1.

3 papers.