{"ID":6023485,"CreatedAt":"2026-07-08T01:00:23.257252134Z","UpdatedAt":"2026-07-10T09:36:36.276842708Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.06065","arxiv_id":"2607.06065","title":"SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review","abstract":"Coding agents increasingly generate pull requests (PRs) for real-world software issues, yet one-shot PR generation remains open-loop: the PR is proposed without systematic review, diagnosis, or revision. We introduce \\textbf{SWE-Review}, a framework for closing this loop with agentic code review. Given an issue and an AI-generated PR, a reviewer agent explores the repository, decides whether the PR should be accepted, and provides structured feedback for revision. We evaluate this setting with our proposed \\textbf{SWE-Review-Bench} to measure both review correctness and downstream revision usefulness. We further curate \\textbf{SWE-Review-Traj} dataset to study broader applications of agentic review and fill the data-scarcity gap for open reviewer training. Experiments show that agentic review continuously improves PRs through a generate-review-revise loop, outperforms single-turn fixed-context review in both decision accuracy and resolve rate after revision, transfers beyond review to improve issue-resolution models, and enables effective and efficient test-time scaling. These results position agentic code review as a practical mechanism for moving AI coding agents from one-shot PR generation toward closed-loop issue resolution.","short_abstract":"Coding agents increasingly generate pull requests (PRs) for real-world software issues, yet one-shot PR generation remains open-loop: the PR is proposed without systematic review, diagnosis, or revision. We introduce \\textbf{SWE-Review}, a framework for closing this loop with agentic code review. Given an issue and an...","url_abs":"https://arxiv.org/abs/2607.06065","url_pdf":"https://arxiv.org/pdf/2607.06065v1","authors":"[\"Ruoyu Wang\",\"Jierun Chen\",\"Shaowei Wang\",\"Chaofan Tao\",\"Sidi Yang\",\"Yuxin Jiang\",\"Kim-Hui Yap\",\"Lifeng Shang\",\"Xiaohui Li\",\"Haoli Bai\"]","published":"2026-07-07T09:37:45Z","proceeding":"cs.SE","tasks":"[\"cs.SE\"]","methods":"[]","has_code":false}