IC3 is a state-of-the-art algorithm for hardware model checking that proves safety properties by incrementally constructing an inductive invariant consisting of a set of lemmas. Its effectiveness depends on generalization heuristics that identify useful lemmas and guide proof search. However, many leading IC3 hardware model checkers operate on lowered, bit-level representations, where high-level design relationships are difficult to exploit for generalization. Those operating at a higher level remain limited in exploiting high-level design structure and semantics. We present Agentic-IC3, built on Pono's word-level model-checking infrastructure, which integrates a language-model agent into IC3 to guide semantic proof search using register-transfer-level (RTL) design information. The framework exposes an agent-oriented interface to a persistent IC3 backend, allowing the agent to interact with an explicit, evolving proof state throughout verification. Across successive proof obligations, the agent relates intermediate proof states and solver feedback to the RTL and proposes high-level lemmas through both SAT and UNSAT generalization. Beyond generalization, the agent can introduce derived observation signals to express design relationships succinctly and obtain more informative feedback, and backtrack to revise proposals that lead to unproductive proof branches. The backend checks proposals before updating the proof state, preserving soundness and providing feedback for further reasoning. On a suite of 14 benchmarks spanning security information-flow verification and functional verification of communication protocols, processors, and functional units, Agentic-IC3 solves 10 cases within a one-hour timeout, including 4 unsolved by all three evaluated baselines: rIC3, Pono-IC3Bits, and A-IC3.

翻译：暂无翻译