Newest papers

RegoMender: A Multi-agent Framework for Automated Rego Policy Repair

Ruijie Zhang, Huaxiao Yin, Li Hu, Fanqi Kong, Haozhe Liang, Shaoyin Cheng, Kun Zhang, Bibo Tu · 2026 · IEEE/ACM International Conference on Automated Software Engineering (ASE)

DOI: 10.1145/3832783.3837490 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

然而,修复Rego政策仍然具有挑战性,因为其严格的语法,声明式语法和特定验证要求。现有的自动化程序修复(APR)方法主要用于主流语言,并努力适应Rego的独特的政策逻辑和修复工作流程。因此,Rego政策修复仍然是一个由试验和错误驱动的手动过程。为了解决这一问题,我们引入了RegoBench,第一个自动化的Rego政策基准,其中包括1,159个真实世界的缺陷,并建议RegoMender,一个反馈引导的多代理工作框架。通过共享黑板和原子工具包进行协作,RegoMender动态地执行修复,重写,或滚动,以解决复杂的修复场景。在RBenchender修复的实用性上,

Machine translation (Meta M2M100); the English original follows.

Abstract

Policy-as-Code (PaC) has emerged as a foundational paradigm in cloud-native systems. However, repairing Rego policies remains challenging due to their strict syntax, declarative semantics, and specific verification requirements. Existing automated program repair (APR) methods are mainly designed for mainstream languages and struggle to accommodate the unique policy logic and repair workflows of Rego. Thus, Rego policy repair remains a manual process driven by trial and error. To address this, we introduce RegoBench, the first automated Rego policy benchmark comprising 1,159 real-world defects, and propose RegoMender, a feedback-guided multi-agent framework. Collaborating via a shared blackboard and an atomic toolkit, RegoMender dynamically executes patching, rewriting, or rolling back, to resolve complex repair scenarios. Evaluated on RegoBench, RegoMender achieves syntactic and test-based semantic success rates of 82.9% and 77.9%, respectively, outperforming the strongest baseline by 13.4%. Unlike other approaches whose performance drops in complex scenarios, RegoMender maintains effectiveness across single-step and chained repair tasks. Furthermore, it generalizes strongly across HCL and SQL and achieves an 86.4% repair rate on 132 real-world CVE vulnerabilities, proving its robustness and practical utility for security.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Computer science, Process management, Business, Software engineering, Government (linguistics), Key (lock)

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange