Investigating the Use of GitHub Copilot for Green Software

Maria Stivala (), Iffat Fatima () and Patricia Lago ()
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Maria Stivala: Vrije Universiteit Amsterdam
Iffat Fatima: Vrije Universiteit Amsterdam
Patricia Lago: Vrije Universiteit Amsterdam

A chapter in Advances and New Trends in Environmental Informatics, 2025, pp 219-235 from Springer

Abstract: Abstract This study empirically investigates the use of GitHub Copilot in developing energy-efficient software and the associated trade-offs. We compare the energy consumption and performance of human-written code to (i) the human-written code optimized by using GitHub Copilot, and (ii) code generated by GitHub Copilot. A set of 15 programming scenarios is used to test our hypothesis. GitHub Copilot is prompted for energy-efficient solutions. Our results demonstrate that GitHub Copilot-generated code can achieve significantly lower energy consumption when optimized, without compromising code quality. The study did not find statistically significant differences in energy consumption compared to human-written code. However, it highlights the potential of AI-assisted coding tools such as GitHub Copilot for developing energy-efficient software and the importance of explicitly prompting for energy consumption.

Keywords: Software development; Sustainability; Green coding; Energy consumption; GitHub Copilot; AI-generated; AI-assisted (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-85284-8_13

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DOI: 10.1007/978-3-031-85284-8_13

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