STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices
LLM-based root cause analysis (RCA) agents have recently emerged as a promising paradigm for incident diagnosis in microservice AIOps. However, their reliability remains fragile: an error in early evidence collection, hypothesis formulation, or causal analysis can propagate through the reasoning trace and eventually corrupt the final diagnosis. In this paper, we present \textbf{STAR}, a \emph{Stage-attributed Triage and Repair} framework for repairing erroneous RCA traces. STAR explicitly decomposes an RCA workflow into four structured stages, namely \emph{Evidence Package} (EP), \emph{Hypothesis Set} (HS), \emph{Analysis Structure} (AS), and \emph{Decision Report} (DR), and treats agent ...
| Authors | Junle Wang, Xingchuang Liao, Wenjun Wu |
|---|---|
| Primary category | cs.AI |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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