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Is ChatGPT-Generated Code Really Green?: Evaluating AI-Generated Solutions for Energy-Efficient Coding Practices
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AI
DOI：10.1109/MS.2025.3644903.png)
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Abstract
En 中文
Energy efficiency matters in software engineering as generative AI integrates into coding workflows. Prior quantitative studies miss context. We qualitatively analyze 200 deep-learning Stack Overflow questions, comparing ChatGPT 4o-mini and human answers, revealing strengths, gaps, and implications for practitioners designers.
Keywords:
Artificial intelligence
Energy efficiency
Codes
Encoding
Chatbots
Reliability
Optimization
Measurement
Deep learning
Computational modeling
Journal
IF:
3
Papers:
3.2K
Citations:
3.6K
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