Do Generative AI Tools Ensure Green Code? An Investigative Study

• URL: http://arxiv.org/abs/2506.08790v1
• Date: Tue, 10 Jun 2025 13:38:41 GMT
• Title: Do Generative AI Tools Ensure Green Code? An Investigative Study
• Authors: Samarth Sikand, Rohit Mehra, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden,
• Abstract summary: We present the results of an early investigation into the sustainability aspects of AI-generated code across three popular generative AI tools.<n>Results highlight the default non-green behavior of tools for generating code, across multiple rules and scenarios.
• Score: 9.067268029288195
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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