Runtime Verification: Monitoring, Knowledge, and Uncertainty (Lecture Notes)

2026-04-29

AI Summary

This work addresses the challenges of model uncertainty and unpredictability in partially observable or black-box systems during runtime by proposing a unified theoretical framework that integrates epistemic logic with temporal logic. Leveraging automata theory, it systematically formalizes core concepts—including specification, diagnosis, opacity, and monitorability—and synthesizes lightweight online monitors through offline analysis. The approach is extended to real-time systems, resolving key issues related to their temporal semantics and algorithmic complexity. Furthermore, the study precisely characterizes the fundamental limits of runtime verification, thereby establishing a constructive and implementable foundation for practical deployment of monitoring mechanisms.

Abstract

Runtime verification is a lightweight verification technique that complements model checking by analyzing system executions at runtime rather than exploring a complete system model in advance. It is particularly useful for partially observable or black-box systems, where uncertainty can only be resolved through observation. These lecture notes present automata-theoretic, temporal-logical, and epistemic foundations of runtime verification. They cover specification formalisms, diagnosis, opacity, and monitorability, and explain how offline analysis can be used to construct monitors that operate online on observed executions. The notes also discuss timed extensions and the additional algorithmic and semantic challenges that arise in the real-time setting.

Problem

• runtime verification
• partial observability
• uncertainty
• black-box systems
• monitoring

Innovation

• runtime verification
• epistemic logic
• monitorability
• opacity
• timed systems