Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot

GitHub Copilot is an artificially intelligent programming assistant used by many developers. While a few studies have evaluated the security risks of using Copilot, there has not been any study to show if it aids developers in producing code with better runtime performance. We evaluate the runtime performance of C++ code produced when developers use GitHub Copilot versus when they do not. To this end, we conducted a user study with 32 participants where each participant solved two C++ programming problems, one with Copilot and the other without it and measured the runtime performance of the participants' solutions on our test data. Our results suggest that using Copilot may produce <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C + +}$</tex> code with (statistically significant) slower runtime performance.

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Publication Details

Published
2025-04-26
DOI
https://doi.org/10.1109/icse55347.2025.00059
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
2.27
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article

Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot

Meiyappan Nagappan, Sreeharsha Udayashankar, Samer Al-Kiswany, Daniel Erhabor
1 citations
Parallel Computing and Optimization Techniques
2.27
article

Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot

Meiyappan Nagappan, Sreeharsha Udayashankar, Samer Al-Kiswany, Daniel Erhabor
article en
1 citations

Abstract

GitHub Copilot is an artificially intelligent programming assistant used by many developers. While a few studies have evaluated the security risks of using Copilot, there has not been any study to show if it aids developers in producing code with better runtime performance. We evaluate the runtime performance of C++ code produced when developers use GitHub Copilot versus when they do not. To this end, we conducted a user study with 32 participants where each participant solved two C++ programming problems, one with Copilot and the other without it and measured the runtime performance of the participants' solutions on our test data. Our results suggest that using Copilot may produce <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{C + +}$</tex> code with (statistically significant) slower runtime performance.

University of Waterloo (CA)
Openalex Percentile: Top 14%
Parallel Computing and Optimization Techniques
2.27
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