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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.16853 |
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| _version_ | 1866915459640590336 |
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| author | Sharma, Pratyush Nidhi Wright, Lauren Herfurth, Anne Sokiyna, Munsif Sharma, Pratyaksh Nidhi Das, Sethu Siponen, Mikko |
| author_facet | Sharma, Pratyush Nidhi Wright, Lauren Herfurth, Anne Sokiyna, Munsif Sharma, Pratyaksh Nidhi Das, Sethu Siponen, Mikko |
| contents | Generative AI coding assistants (ACAs) are widely adopted yet pose serious legal and compliance risks. ACAs can generate code governed by restrictive open-source licenses (e.g., GPL), potentially exposing companies to litigation or forced open-sourcing. Few developers are trained in these risks, and legal standards vary globally, especially with outsourcing. Our article introduces DevLicOps, a practical framework that helps IT leaders manage ACA-related licensing risks through governance, incident response, and informed tradeoffs. As ACA adoption grows and legal frameworks evolve, proactive license compliance is essential for responsible, risk-aware software development in the AI era. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_16853 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code Sharma, Pratyush Nidhi Wright, Lauren Herfurth, Anne Sokiyna, Munsif Sharma, Pratyaksh Nidhi Das, Sethu Siponen, Mikko Software Engineering Artificial Intelligence Generative AI coding assistants (ACAs) are widely adopted yet pose serious legal and compliance risks. ACAs can generate code governed by restrictive open-source licenses (e.g., GPL), potentially exposing companies to litigation or forced open-sourcing. Few developers are trained in these risks, and legal standards vary globally, especially with outsourcing. Our article introduces DevLicOps, a practical framework that helps IT leaders manage ACA-related licensing risks through governance, incident response, and informed tradeoffs. As ACA adoption grows and legal frameworks evolve, proactive license compliance is essential for responsible, risk-aware software development in the AI era. |
| title | DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2508.16853 |