CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918152534753280 |
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| author | Bifolco, Daniele Annicchiarico, Guido Barbiero, Pierluigi Di Penta, Massimiliano Zampetti, Fiorella |
| author_facet | Bifolco, Daniele Annicchiarico, Guido Barbiero, Pierluigi Di Penta, Massimiliano Zampetti, Fiorella |
| contents | Large Language Models (LLMs) are widely used in software development tasks nowadays. Unlike reusing code taken from the Web, for LLMs' generated code, developers are concerned about its lack of trustworthiness and possible copyright or licensing violations, due to the lack of code provenance information. This paper proposes CodeGenLink, a GitHub CoPilot extension for Visual Studio Code aimed at (i) suggesting links containing code very similar to automatically generated code, and (ii) whenever possible, indicating the license of the likely origin of the code. CodeGenLink retrieves candidate links by combining LLMs with their web search features and then performs similarity analysis between the generated and retrieved code. Preliminary results show that CodeGenLink effectively filters unrelated links via similarity analysis and provides licensing information when available. Tool URL: https://github.com/danielebifolco/CodeGenLink Tool Video: https://youtu.be/M6nqjBf9_pw |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_01077 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code Bifolco, Daniele Annicchiarico, Guido Barbiero, Pierluigi Di Penta, Massimiliano Zampetti, Fiorella Software Engineering Artificial Intelligence Large Language Models (LLMs) are widely used in software development tasks nowadays. Unlike reusing code taken from the Web, for LLMs' generated code, developers are concerned about its lack of trustworthiness and possible copyright or licensing violations, due to the lack of code provenance information. This paper proposes CodeGenLink, a GitHub CoPilot extension for Visual Studio Code aimed at (i) suggesting links containing code very similar to automatically generated code, and (ii) whenever possible, indicating the license of the likely origin of the code. CodeGenLink retrieves candidate links by combining LLMs with their web search features and then performs similarity analysis between the generated and retrieved code. Preliminary results show that CodeGenLink effectively filters unrelated links via similarity analysis and provides licensing information when available. Tool URL: https://github.com/danielebifolco/CodeGenLink Tool Video: https://youtu.be/M6nqjBf9_pw |
| title | CodeGenLink: A Tool to Find the Likely Origin and License of Automatically Generated Code |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2510.01077 |