Symbolic Model Checking for TLA+ Made Faster

Abstract

AbstractThe need to provide formal guarantees about the behaviour of the algorithms underpinning modern distributed systems became evident in recent years. This interest made apparent the complexities involved in applying verification techniques in a distributed setting, with significant effort being made in both academia and industry to aid in this endeavour. Many formalisms have been proposed to tackle the difficulties faced by practitioners, with one that has seen widespread use in industry being TLA$$^+$$ + , adopted, for instance, by Amazon Web Services. TLA$$^+$$ + provides engineers with a way of specifying both systems and desired properties, and is supported by a number of verification tools. Despite their extensive use, such tools suffer considerably from lack of scalability. To solve this, we propose a novel encoding of TLA$$^+$$ + into SMT constraints to improve symbolic model checking efficiency. Our insight is the need to provide the SMT solver with structural information about the TLA$$^+$$ + specification encoded, i.e., how data structures and their component elements interact, which we do by relying on the SMT theory of arrays. We implemented our approach by modifying the SMT-based model checker Apalache and evaluated it against comparable tools. Our results show that our approach outperforms existing ones on a number of benchmarks, with an order of magnitude improvement in checking time.