Abstract. We consider the problem of bounded model checking (BMC) for linear temporal logic (LTL). We present several efficient encodings that have size linear in the bound. Furthermore, we show how the encodings can be extended to LTL with past operators (PLTL). The generalised encoding is still of linear size, but cannot detect minimal length counterexamples. By using the virtual unrolling technique minimal length counterexamples can be captured, however, the size of the encoding is quadratic in the specification. We also extend virtual unrolling to Büchi automata, enabling them to accept minimal length counterexamples.Our BMC encodings can be made incremental in order to benefit from incremental SAT technology. With fairly small modifications the incremental encoding can be further enhanced with a termination check, allowing us to prove properties with BMC.An analysis of the liveness-to-safety transformation reveals many similarities to the BMC encodings in this paper. We conduct experiments to determine the advantage of employing dedicated BMC encodings for PLTL over combining more general but potentially less efficient approaches with BMC: the liveness-to-safety transformation with invariant checking and Büchi automata with fair cycle detection.Experiments clearly show that our new encodings improve performance of BMC considerably, particularly in the case of the incremental encoding, and that they are very competitive for finding bugs. Dedicated encodings seem to have an advantage over using more general methods with BMC. Using the liveness-to-safety translation with BDD-based invariant checking results in an efficient method to find shortest counterexamples that complements the BMC-based approach. For proving complex properties BDD-based methods still tend to perform better.
Abstract. Bounded model checking is an efficient method for finding bugs in system designs. The major drawback of the basic method is that it cannot prove properties, only disprove them. Recently, some progress has been made towards proving properties of LTL. We present an incremental and complete bounded model checking method for the full linear temporal logic with past (PLTL). Compared to previous works, our method both improves and extends current results in many ways: (i) our encoding is incremental, resulting in improvements in performance, (ii) we can prove non-existence of a counterexample at shallower depths in many cases, and (iii) we support full PLTL. We have implemented our method in the NuSMV2 model checker and report encouraging experimental results.
No abstract
Abstract.We consider the problem of bounded model checking for linear temporal logic with past operators (PLTL). PLTL is more attractive as a specification language than linear temporal logic without past operators (LTL) since many specifications are easier to express in PLTL. Although PLTL is not more expressive than LTL, it is exponentially more succinct. Our contribution is a new more efficient encoding of the bounded model checking problem for PLTL based on our previously presented encoding for LTL. The new encoding is linear in the bound. We have implemented the encoding in the NuSMV 2.1 model checking tool and compare it against the encoding in NuSMV by Benedetti and Cimatti. The experimental results show that our encoding performs significantly better than this previously used encoding.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.