In recent years, the LTSmin model checker has been extended with support for several new modelling languages, including probabilistic (Mapa) and timed systems (Uppaal). Also, connecting additional language front-ends or ad-hoc state-space generators to LTSmin was simplified using custom C-code. From symbolic and distributed reachability analysis and minimisation, LTSmin's functionality has developed into a model checker with multi-core algorithms for on-the-fly LTL checking with partial-order reduction, and multi-core symbolic checking for the modal µ-calculus, based on the multi-core decision diagram package Sylvan. In LTSmin, the modelling languages and the model checking algorithms are connected through a Partitioned Next-State Interface (Pins), that allows to abstract away from language details in the implementation of the analysis algorithms and on-the-fly optimisations. In the current paper, we present an overview of the toolset and its recent changes, and we demonstrate its performance and versatility in two case studies.

The LTL Model Checking problem is reducible to finding accepting cycles in a graph. The Nested Depth-First Search (Ndfs) algorithm detects accepting cycles efficiently: on-the-fly, with linear-time complexity and negligible memory overhead. The only downside of the algorithm is that it relies on an inherently-sequential, depth-first search. It has not been parallelized beyond running the independent nested search in a separate thread (dual core). In this paper, we introduce, for the first time, a multi-core Ndfs algorithm that can scale beyond two threads, while maintaining exactly the same worst-case time complexity. We prove this algorithm correct, and present experimental results obtained with an implementation in the LTSmin tool set on the entire Beem benchmark database. We measured considerable speedups compared to the current state of the art in parallel cycle detection algorithms.

Abstract. This paper contributes to the multi-core model checking of timed automata (TA) with respect to liveness properties, by investigating checking of TA Büchi emptiness under the very coarse inclusion abstraction or zone subsumption, an open problem in this field. We show that in general Büchi emptiness is not preserved under this abstraction, but some other structural properties are preserved. Based on those, we propose a variation of the classical nested depth-first search (ndfs) algorithm that exploits subsumption. In addition, we extend the multi-core cndfs algorithm with subsumption, providing the first parallel LTL model checking algorithm for timed automata. The algorithms are implemented in LTSmin, and experimental evaluations show the effectiveness and scalability of both contributions: subsumption halves the number of states in the real-world FDDI case study, and the multi-core algorithm yields speedups of up to 40 using 48 cores.

Abstract. This paper presents CNDFS, a tight integration of two earlier multicore nested depth-first search (NDFS) algorithms for LTL model checking. CNDFS combines the different strengths and avoids some weaknesses of its predecessors. We compare CNDFS to an earlier ad-hoc combination of those two algorithms and show several benefits: It has shorter and simpler code and a simpler correctness proof. It exhibits more robust performance with similar scalability, while at the same time reducing memory requirements. The algorithm has been implemented in the multi-core backend of the LTSMIN model checker, which is now benchmarked for the first time on a 48 core machine (previously 16). The experiments demonstrate better scalability than other parallel LTL model checking algorithms, but we also investigate apparent bottlenecks. Finally, we noticed that the multi-core NDFS algorithms produce shorter counterexamples, surprisingly often shorter than their BFS-based counterparts.