A Controlled Experiment on the Energy Efficiency of the Source Code Generated by Code Llama

Fuente: arXiv
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Main Authors: Cursaru, Vlad-Andrei, Duits, Laura, Milligan, Joel, Ural, Damla, Sanchez, Berta Rodriguez, Stoico, Vincenzo, Malavolta, Ivano
Format: Preprint
Published: 2024
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author Cursaru, Vlad-Andrei
Duits, Laura
Milligan, Joel
Ural, Damla
Sanchez, Berta Rodriguez
Stoico, Vincenzo
Malavolta, Ivano
author_facet Cursaru, Vlad-Andrei
Duits, Laura
Milligan, Joel
Ural, Damla
Sanchez, Berta Rodriguez
Stoico, Vincenzo
Malavolta, Ivano
contents Context. Nowadays, 83% of software developers use Large Language Models (LLMs) to generate code. LLMs recently became essential to increase the productivity of software developers and decrease the time and cost of software development. Developers ranging from novices to experts use LLM tools not only to detect and patch bugs, but also to integrate generated code into their software. However, as of today there is no objective assessment of the energy efficiency of the source code generated by LLM tools. Released in August 2023, Code Llama is one of the most recent LLM tools. Goal. In this paper, we present an empirical study that assesses the energy efficiency of Code Llama with respect to human-written source code. Method. We design an experiment involving three human-written benchmarks implemented in C++, JavaScript, and Python. We ask Code Llama to generate the code of the benchmarks using different prompts and temperatures. Therefore, we execute both implementations and profile their energy efficiency. Results. Our study shows that the energy efficiency of code generated by Code Llama is heavily-dependent on the chosen programming language and the specific code problem at hand. Also, human implementations tend to be more energy efficient overall, with generated JavaScript code outperforming its human counterpart. Moreover, explicitly asking Code Llama to generate energy-efficient code results in an equal or worse energy efficiency, as well as using different temperatures seems not to affect the energy efficiency of generated code. Conclusions. According to our results, code generated using Code Llama does not guarantee energy efficiency, even when prompted to do so. Therefore, software developers should evaluate the energy efficiency of generated code before integrating it into the software system under development.
format Preprint
id arxiv_https___arxiv_org_abs_2405_03616
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Controlled Experiment on the Energy Efficiency of the Source Code Generated by Code Llama
Cursaru, Vlad-Andrei
Duits, Laura
Milligan, Joel
Ural, Damla
Sanchez, Berta Rodriguez
Stoico, Vincenzo
Malavolta, Ivano
Software Engineering
Artificial Intelligence
Context. Nowadays, 83% of software developers use Large Language Models (LLMs) to generate code. LLMs recently became essential to increase the productivity of software developers and decrease the time and cost of software development. Developers ranging from novices to experts use LLM tools not only to detect and patch bugs, but also to integrate generated code into their software. However, as of today there is no objective assessment of the energy efficiency of the source code generated by LLM tools. Released in August 2023, Code Llama is one of the most recent LLM tools. Goal. In this paper, we present an empirical study that assesses the energy efficiency of Code Llama with respect to human-written source code. Method. We design an experiment involving three human-written benchmarks implemented in C++, JavaScript, and Python. We ask Code Llama to generate the code of the benchmarks using different prompts and temperatures. Therefore, we execute both implementations and profile their energy efficiency. Results. Our study shows that the energy efficiency of code generated by Code Llama is heavily-dependent on the chosen programming language and the specific code problem at hand. Also, human implementations tend to be more energy efficient overall, with generated JavaScript code outperforming its human counterpart. Moreover, explicitly asking Code Llama to generate energy-efficient code results in an equal or worse energy efficiency, as well as using different temperatures seems not to affect the energy efficiency of generated code. Conclusions. According to our results, code generated using Code Llama does not guarantee energy efficiency, even when prompted to do so. Therefore, software developers should evaluate the energy efficiency of generated code before integrating it into the software system under development.
title A Controlled Experiment on the Energy Efficiency of the Source Code Generated by Code Llama
topic Software Engineering
Artificial Intelligence
url https://arxiv.org/abs/2405.03616