Does Co-Development with AI Assistants Lead to More Maintainable Code? A Registered Report

• URL: http://arxiv.org/abs/2408.10758v1
• Date: Tue, 20 Aug 2024 11:48:42 GMT
• Title: Does Co-Development with AI Assistants Lead to More Maintainable Code? A Registered Report
• Authors: Markus Borg, Dave Hewett, Donald Graham, Noric Couderc, Emma Söderberg, Luke Church, Dave Farley,
• Abstract summary: This study aims to examine the influence of AI assistants on software maintainability. In Phase 1, developers will add a new feature to a Java project, with or without the aid of an AI assistant. In Phase 2, a randomized controlled trial, will involve a different set of developers evolving random Phase 1 projects - working without AI assistants.
• Score: 6.7428644467224
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: [Background/Context] AI assistants like GitHub Copilot are transforming software engineering; several studies have highlighted productivity improvements. However, their impact on code quality, particularly in terms of maintainability, requires further investigation. [Objective/Aim] This study aims to examine the influence of AI assistants on software maintainability, specifically assessing how these tools affect the ability of developers to evolve code. [Method] We will conduct a two-phased controlled experiment involving professional developers. In Phase 1, developers will add a new feature to a Java project, with or without the aid of an AI assistant. Phase 2, a randomized controlled trial, will involve a different set of developers evolving random Phase 1 projects - working without AI assistants. We will employ Bayesian analysis to evaluate differences in completion time, perceived productivity, code quality, and test coverage.

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