Do Generative AI Tools Ensure Green Code? An Investigative Study
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 10 Jun 2025.
Builds on
5 of 22 references.
References · 5
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2023ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generationcited by 168
- 2023How Secure is Code Generated by ChatGPT?cited by 81
- 2023Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPTcited by 71
- 2022Towards a Green Quotient for Software Projectscited by 1
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.