一句话：将 AutoCodeRover 程序改进智能体适配为 SonarQube 修复智能体，自动为静态分析问题生成补丁并接入 PR 审查流程。
静态分析工具 SonarQube 会报告大量安全漏洞与代码质量 issue，给开发者带来沉重的人工修复负担。本文将 AutoCodeRover 程序改进智能体适配到 SonarQube issue 的自动修复，提出 SonarQube Remediation Agent，使其能够以安全可信的方式与关键任务代码库交互，并应对大规模 issue 处理与用户交互设计等实际挑战。该智能体被集成到软件开发生命周期中，在 pull request 审查工作流中建议补丁，帮助开发者借助 SonarQube 高效提升软件质量与安全性。论文以经验与教训的形式总结了这一适配过程中的实践问题与应对方案。
Agentic systems have been gaining traction in solving software engineering tasks. These tasks span from writing documentation, fixing faults in the codebase, and developing new features. A promising application of LLM agents is addressing software "issues", with an issue capturing a unit of improvement needed in a software project. Issues can be detected and constructed by static analysis tools, such as SonarQube. Static analysis tools frequently generate a substantial number of reports related to security vulnerabilities and code quality, imposing a significant manual workload on developers. With the advances in agentic AI, there is potential to automatically remediate these issues, thereby reducing developer effort. In this paper, we present our experience and lessons learned in adapting the AutoCodeRover program improvement agent to automatically propose patches for issues reported by SonarQube. We name this new agent SonarQube Remediation Agent, specialized for fixing SonarQube issues. SonarQube Remediation Agent is designed to be capable of interacting with mission-critical codebases in a secure and trustworthy manner. We discuss our approach in tackling practical challenges such as handling large volumes of issues and designing seamless user interactions. SonarQube Remediation Agent is integrated into the software development lifecycle by suggesting patches during the pull request review workflow, enabling developers to efficiently improve software quality and security with SonarQube.
@inproceedings{MirchevSRZR26,
title = {AutoCodeRover: Agentic Program Repair for SonarQube Issues},
author = {Martin Mirchev and Ridwan Shariffdeen and Haifeng Ruan and Yuntong Zhang and Abhik Roychoudhury},
booktitle = {FSE},
year = {2026},
doi = {10.1145/3803437.3805209}
}