Formal Verification

Formal verification studies rigorous ways to show that systems satisfy properties such as safety, security, and correctness. It represents systems and requirements with logic, then uses theorem proving, model checking, SMT solving, static analysis, and runtime monitoring to prove properties or find counterexamples. These methods apply to software, hardware, protocols, neural networks, robotics, and AI agents, where failures can be costly and testing covers only selected executions. Current work combines automation and language models to reduce proof effort, but scalability and whether specifications faithfully capture intended behavior remain central challenges.