AI RESEARCH
Quality and Security Signals in AI-Generated Python Refactoring Pull Requests
arXiv CS.AI
•
ArXi:2605.21453v1 Announce Type: cross As AI agents increasingly contribute to code development and maintenance, there is still limited empirical evidence on the quality and risk characteristics of their changes in real-world projects, particularly for refactoring-oriented contributions. It remains unclear how agent-authored refactoring edits affect maintainability, code quality, and security once merged into GitHub repositories. To address this gap, we conduct an empirical study of Python refactoring pull requests (PRs) from the AIDe dataset.