A Dataset for GitHub Repository Deduplication: Extended Description
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Abstract (arXiv)
GitHub projects can be easily replicated through the site's fork process or through a Git clone-push sequence. This is a problem for empirical software engineering, because it can lead to skewed results or mistrained machine learning models. We provide a dataset of 10.6 million GitHub projects that are copies of others, and link each record with the project's ultimate parent. The ultimate parents were derived from a ranking along six metrics. The related projects were calculated as the connected components of an 18.2 million node and 12 million edge denoised graph created by directing edges to ultimate parents. The graph was created by filtering out more than 30 hand-picked and 2.3 million pattern-matched clumping projects. Projects that introduced unwanted clumping were identified by repeatedly visualizing shortest path distances between unrelated important projects. Our dataset identified 30 thousand duplicate projects in an existing popular reference dataset of 1.8 million projects. An evaluation of our dataset against another created independently with different methods found a significant overlap, but also differences attributed to the operational definition of what projects are considered as related.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Feb 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 0; 2025: 2.
6 papers.
- 2025The Fools are Certain; the Wise are Doubtful: Exploring LLM Confidence in Code Completioncited by 3
- 2021Repo2Vec: A Comprehensive Embedding Approach for Determining Repository Similaritycited by 2
- 2022An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detectioncited by 2
- 2025Light over Heavy: Automated Performance Requirements Quantification with Linguistic Inducementcited by 2
- 2022Topical: Learning Repository Embeddings from Source Code using Attentioncited by 0
- 2023Good Tools are Half the Work: Tool Usage in Deep Learning Projectscited by 0
- 2025Light over Heavy: Automated Performance Requirements Quantification with Linguistic Inducement5 Nov 2025
- 2025The Fools are Certain; the Wise are Doubtful: Exploring LLM Confidence in Code Completion22 Aug 2025
- 2023Good Tools are Half the Work: Tool Usage in Deep Learning Projects29 Oct 2023
- 2022Topical: Learning Repository Embeddings from Source Code using Attention19 Aug 2022
- 2022An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detection10 Mar 2022
- 2021Repo2Vec: A Comprehensive Embedding Approach for Determining Repository Similarity11 Jul 2021