统一在线检测与诊断，实时定位系统故障
A Unified Framework for Runtime Verification and Model-Based Diagnosis in LOLA
- 用流语言统一建模系统、状态与观测数据
- 故障检测同时完成定位，无需额外工具链
- 支持时不变/瞬态故障，适应不确定观测
我们提出一个集成框架，将运行时验证与基于模型的诊断统一于流规格语言LOLA中。通过将系统描述、组件健康状态和观测结果编码为单一的流形式化方法，该方法可在不依赖独立工具链的情况下，实现连续、在线的故障定位与检测。框架支持时不变和瞬态故障，并自然兼容非确定性观测。
原文摘要 · Abstract (English)
We present an integrated framework that unifies runtime verification and model-based diagnosis within the stream specification language LOLA. By encoding system descriptions, component health states, and observations into a single stream-based formalism, the approach enables continuous, online fault localization directly alongside fault detection, without requiring separate toolchains. The framework supports both time-invariant and transient faults, and naturally accommodates nondeterministic observations.
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