Beyond Dependencies: The Role of Copy-Based Reuse in Open Source Software Development
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Abstract (arXiv)
In Open Source Software, resources of any project are open for reuse by introducing dependencies or copying the resource itself. In contrast to dependency-based reuse, the infrastructure to systematically support copy-based reuse appears to be entirely missing. Our aim is to enable future research and tool development to increase efficiency and reduce the risks of copy-based reuse. We seek a better understanding of such reuse by measuring its prevalence and identifying factors affecting the propensity to reuse. To identify reused artifacts and trace their origins, our method exploits World of Code infrastructure. We begin with a set of theory-derived factors related to the propensity to reuse, sample instances of different reuse types, and survey developers to better understand their intentions. Our results indicate that copy-based reuse is common, with many developers being aware of it when writing code. The propensity for a file to be reused varies greatly among languages and between source code and binary files, consistently decreasing over time. Files introduced by popular projects are more likely to be reused, but at least half of reused resources originate from ``small'' and ``medium'' projects. Developers had various reasons for reuse but were generally positive about using a package manager.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Sep 2024.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2025Cracks in The Stack: Hidden Vulnerabilities and Licensing Risks in LLM Pre-Training Datasetscited by 4
- 2024Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detectioncited by 3
- 2026Stdlib or Third-Party? Empirical Performance and Correctness of LLM-Assisted Zero-Dependency Python Librariescited by 0
- 2026Stdlib or Third-Party? Empirical Performance and Correctness of LLM-Assisted Zero-Dependency Python Libraries20 May 2026
- 2025Cracks in The Stack: Hidden Vulnerabilities and Licensing Risks in LLM Pre-Training Datasets5 Jan 2025
- 2024Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection16 Dec 2024