OSS License Identification at Scale: A Comprehensive Dataset Using World of Code
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| Published in: | arXiv.org (Dec 6, 2024), p. n/a |
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| Other Authors: | , , |
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Cornell University Library, arXiv.org
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| Online Access: | Citation/Abstract Full text outside of ProQuest |
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|---|---|---|---|
| 001 | 3102578362 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 035 | |a 3102578362 | ||
| 045 | 0 | |b d20241206 | |
| 100 | 1 | |a Jahanshahi, Mahmoud | |
| 245 | 1 | |a OSS License Identification at Scale: A Comprehensive Dataset Using World of Code | |
| 260 | |b Cornell University Library, arXiv.org |c Dec 6, 2024 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a The proliferation of open source software (OSS) and different types of reuse has made it incredibly difficult to perform an essential legal and compliance task of accurate license identification within the software supply chain. This study presents a reusable and comprehensive dataset of OSS licenses, created using the World of Code (WoC) infrastructure. By scanning all files containing "license" in their file paths, and applying the approximate matching via winnowing algorithm to identify the most similar license from the SPDX list, we found and identified 5.5 million distinct license blobs in OSS projects. The dataset includes a detailed project-to-license (P2L) map with commit timestamps, enabling dynamic analysis of license adoption and changes over time. To verify the accuracy of the dataset we use stratified sampling and manual review, achieving a final accuracy of 92.08%, with precision of 87.14%, recall of 95.45%, and an F1 score of 91.11%. This dataset is intended to support a range of research and practical tasks, including the detection of license noncompliance, the investigations of license changes, study of licensing trends, and the development of compliance tools. The dataset is open, providing a valuable resource for developers, researchers, and legal professionals in the OSS community. | |
| 653 | |a Algorithms | ||
| 653 | |a Licensing | ||
| 653 | |a Source code | ||
| 653 | |a Datasets | ||
| 653 | |a Licenses | ||
| 653 | |a Licensing (technology) | ||
| 653 | |a Open source software | ||
| 700 | 1 | |a Reid, David | |
| 700 | 1 | |a McDaniel, Adam | |
| 700 | 1 | |a Mockus, Audris | |
| 773 | 0 | |t arXiv.org |g (Dec 6, 2024), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3102578362/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/2409.04824 |