🤖 AI Summary
This work addresses the challenge of real-time health monitoring and regulatory compliance verification for cyber-physical systems (e.g., unmanned aerial vehicles). We propose a multi-paradigm, synergistic formal verification framework integrating RTLola (stream-based runtime monitoring), UPPAAL (real-time model checking), TLA+ (distributed protocol modeling), Coq and Isabelle/HOL (higher-order interactive theorem proving), and SMT solvers. A key innovation is a machine learning–driven abstraction-refinement strategy enabling heterogeneous language interoperability and compositional correctness guarantees. Compared to conventional approaches, our framework significantly improves formal modeling efficiency and scalability for industrial-scale systems. The methodology has yielded 52 peer-reviewed publications and advanced the engineering adoption of formal methods in safety-critical domains—including autonomous driving, medical software, and blockchain protocols—demonstrating robust practical impact and cross-domain applicability.