Does the AI Reviewer Alleviate or Aggravate the Maintenance Burden? Evidence from GitHub Copilot Reviewer
Type: article
Abstract: This study examines how AI-based code reviewers reshape contribution behavior and maintenance dynamics in open-source software (OSS) communities. AI reviewers provide scalable, fast, and standardized evaluations. They reshape contributions as well as maintainers' workload. Leveraging the introduction of GitHub Copilot Reviewer on GitHub as a natural experiment in 2025, we investigate how AI review affects maintainers' workload and review efficiency as well as contribution behavior. We find that repository maintainers initially face a sharp increase in PR submissions and a higher review workload after the adoption of the AI reviewer. Over time, human contributions decline while the increase in bot-generated PRs is sustained. Interestingly, survival analysis reveals that AI reviewers increase review efficiency for human PR contributions, whereas bot PRs take longer to review and merge. Our findings suggest that while AI reviewers increase review efficiency, they aggravate the maintenance burden by encouraging more code contributions via humans and bots.
Authors: Xu, Feiyang, Medapa, Poonacha K., Tunç, Murat
Institution: Tilburg University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7222907695