Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
Shamse Tasnim Cynthia, Al Muttakin, Banani Roy
TL;DR
This work analyzes post-merge code quality of agent-generated bug-fix PRs using a large-scale differential SonarQube analysis across 1,210 merged Python PRs from the AIDev dataset. It normalizes quality metrics by code churn (per $KLOC$) to isolate intrinsic quality differences between agents. The findings show Code Smells dominate across severities, while Bugs are rarer but can be BLOCKER, with some high-severity patterns tied to specific rules (e.g., python:S930). Importantly, apparent per-agent quality differences largely disappear after normalization, suggesting that merge speed or volume is not a reliable proxy for post-merge quality and that systematic, size-aware quality gates are needed for agent-generated contributions.
Abstract
The increasing adoption of AI coding agents has increased the number of agent-generated pull requests (PRs) merged with little or no human intervention. Although such PRs promise productivity gains, their post-merge code quality remains underexplored, as prior work has largely relied on benchmarks and controlled tasks rather than large-scale post-merge analyses. To address this gap, we analyze 1,210 merged agent-generated bug-fix PRs from Python repositories in the AIDev dataset. Using SonarQube, we perform a differential analysis between base and merged commits to identify code quality issues newly introduced by PR changes. We examine issue frequency, density, severity, and rule-level prevalence across five agents. Our results show that apparent differences in raw issue counts across agents largely disappear after normalizing by code churn, indicating that higher issue counts are primarily driven by larger PRs. Across all agents, code smells dominate, particularly at critical and major severities, while bugs are less frequent but often severe. Overall, our findings show that merge success does not reliably reflect post-merge code quality, highlighting the need for systematic quality checks for agent-generated bug-fix PRs.