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Echoes of AI: Investigating the Downstream Effects of AI Assistants on Software Maintainability
arXiv – CS AI|Markus Borg, Dave Hewett, Nadim Hagatulah, Noric Couderc, Emma S\"oderberg, Donald Graham, Uttam Kini, Dave Farley||6 views
🤖AI Summary
A controlled study of 151 professional developers found that AI coding assistants like GitHub Copilot provide significant productivity gains (30.7% faster completion) but don't impact code maintainability when other developers later modify the code. The research suggests AI-assisted code is neither easier nor harder for subsequent developers to work with.
Key Takeaways
- →AI coding assistants reduced development time by 30.7% median, with habitual users seeing 55.9% speedup
- →Code created with AI assistance showed no significant differences in maintainability when evolved by other developers
- →No systematic advantages or disadvantages were detected in code quality or completion time for subsequent evolution
- →Study involved 151 participants with 95% being professional developers in a two-phase controlled experiment
- →Future research should examine risks like code bloat and cognitive debt from increased AI reliance
#ai-coding#github-copilot#software-development#maintainability#productivity#developer-tools#code-quality#research-study
Read Original →via arXiv – CS AI
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