Abstract-We propose a novel technique to mine powerful and generalized boolean relations among flip-flops in a sequential circuit for sequential equivalence checking. In contrast to traditional learning methods, our mining algorithm can detect inductive invariants as well as illegal state cubes. These invariants can be arbitrary boolean expressions and can thus prune a large don't care space during equivalence checking. Experimental results demonstrate that these general invariants can be very effective for sequential equivalence checking of circuits with no or very few equivalent signals between them, with low computational costs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.