Measuring the Runtime Performance of C++ Code Written by Humans Using Github Copilot
Daniel Erhabor, Sreeharsha Udayashankar, Meiyappan Nagappan, Samer Al-Kiswany
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"></tex> code with (statistically significant) slower runtime performance.
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