Do Generative AI Tools Ensure Green Code? An Investigative Study
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918053172740096 |
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| author | Sikand, Samarth Mehra, Rohit Sharma, Vibhu Saujanya Kaulgud, Vikrant Podder, Sanjay Burden, Adam P. |
| author_facet | Sikand, Samarth Mehra, Rohit Sharma, Vibhu Saujanya Kaulgud, Vikrant Podder, Sanjay Burden, Adam P. |
| contents | Software sustainability is emerging as a primary concern, aiming to optimize resource utilization, minimize environmental impact, and promote a greener, more resilient digital ecosystem. The sustainability or "greenness" of software is typically determined by the adoption of sustainable coding practices. With a maturing ecosystem around generative AI, many software developers now rely on these tools to generate code using natural language prompts. Despite their potential advantages, there is a significant lack of studies on the sustainability aspects of AI-generated code. Specifically, how environmentally friendly is the AI-generated code based upon its adoption of sustainable coding practices? In this paper, we present the results of an early investigation into the sustainability aspects of AI-generated code across three popular generative AI tools - ChatGPT, BARD, and Copilot. The results highlight the default non-green behavior of tools for generating code, across multiple rules and scenarios. It underscores the need for further in-depth investigations and effective remediation strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_08790 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Do Generative AI Tools Ensure Green Code? An Investigative Study Sikand, Samarth Mehra, Rohit Sharma, Vibhu Saujanya Kaulgud, Vikrant Podder, Sanjay Burden, Adam P. Software Engineering Artificial Intelligence Computers and Society Software sustainability is emerging as a primary concern, aiming to optimize resource utilization, minimize environmental impact, and promote a greener, more resilient digital ecosystem. The sustainability or "greenness" of software is typically determined by the adoption of sustainable coding practices. With a maturing ecosystem around generative AI, many software developers now rely on these tools to generate code using natural language prompts. Despite their potential advantages, there is a significant lack of studies on the sustainability aspects of AI-generated code. Specifically, how environmentally friendly is the AI-generated code based upon its adoption of sustainable coding practices? In this paper, we present the results of an early investigation into the sustainability aspects of AI-generated code across three popular generative AI tools - ChatGPT, BARD, and Copilot. The results highlight the default non-green behavior of tools for generating code, across multiple rules and scenarios. It underscores the need for further in-depth investigations and effective remediation strategies. |
| title | Do Generative AI Tools Ensure Green Code? An Investigative Study |
| topic | Software Engineering Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2506.08790 |