Do Generative AI Tools Ensure Green Code? An Investigative Study
June 10, 2025 Β· Declared Dead Β· π 2024 IEEE/ACM International Workshop on Responsible AI Engineering (RAIE)
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Authors
Samarth Sikand, Rohit Mehra, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden
arXiv ID
2506.08790
Category
cs.SE: Software Engineering
Cross-listed
cs.AI,
cs.CY
Citations
8
Venue
2024 IEEE/ACM International Workshop on Responsible AI Engineering (RAIE)
Last Checked
4 months ago
Abstract
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.
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