Experiences in developing the mCRL2 toolset

Groote, Jan Friso; Keiren, Jeroen J. A.; Stappers, Frank P. M.; Wesselink, J.W.; Willemse, Tim A. C.

doi:10.1002/spe.1021

Cited by 9 publications

(4 citation statements)

References 19 publications

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“…The advantage of using this toolset as a starting point is that it has interfaces with multiple popular model checkers, such as DiVinE [2] and mCRL2 [17]. However, DiVinE is based on Kripke structures, where the states instead of the transitions are labelled.…”

Section: Methodsmentioning

confidence: 99%

Towards Informed Swarm Verification

Wijs

2011

Lecture Notes in Computer Science

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Abstract. In this paper, we propose a new method to perform large scale grid model checking. A manager distributes the workload over many embarrassingly parallel jobs. Only little communication is needed between a worker and the manager, and only once the worker is ready for more work. The novelty here is that the individual jobs together form a so-called cumulatively exhaustive set, meaning that even though each job explores only a part of the state space, together, the tasks explore all states reachable from the initial state.

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Section: Methodsmentioning

confidence: 99%

Towards Informed Swarm Verification

Wijs

2011

Lecture Notes in Computer Science

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“…The fact that one of the most advanced toolsets for the mCRL2 specification language [20], based on process algebra ACP, still does not support recursive parallelism [27], can be perceived as a limitation in some cases. Therefore, it can be considered as another source of motivation.…”

Section: Motivationmentioning

confidence: 99%

Abstraction-enriched Formal Methods Integration

Šimoňák¹,

Uchnár²,

Fecil'ak³

et al. 2018

ACTA POLYTECH HUNG

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The paper presents the results of our research in the field of combining process algebra and Petri nets. To provide better support for design and analysis of larger-scale systems by means of abstraction mechanism, the method itself and the tools allowing its practical application have been enhanced significantly. The theoretical aspects and implementation of enhancements are discussed in detail. Careful testing, along with the process of implementing the new functionality into one of the involved tools, helped us to disclose its certain hidden imperfections, which are subsequently addressed.

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“…One can view the program counter of each process as a normal state variable, check for its current value in a separate guard, and update it in the transitions. But our definition is more general, since it can also be applied to models without a natural notion of a fixed set of processes, for instance rulebased systems, such as the linear process equations in mCRL [12].…”

Section: Definition 3 (Structural Transition)mentioning

confidence: 99%

“…Previous work defines partial order reduction in terms of either petri-nets [34] or parallel components with local program counters, called processes [14,9]. While this allows the exploitation of certain formalismspecific properties, like fairness [23] and token conditions [32], is also complicates the application to other formalisms, for instance, rule-based systems [12]. Moreover, current implementations are tightly coupled to a particular specification language in order to compute a good syntactic approximation of a sufficient successor set.…”

Section: Introductionmentioning

confidence: 99%

Guard-Based Partial-Order Reduction

Laarman

Pater

Pol

et al. 2013

Model Checking Software

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Abstract. This paper aims at making partial order reduction independent of the modeling language. Our starting point is the stubborn set algorithm of Valmari (see also Godefroid's thesis), which relies on necessary enabling sets. We generalize it to a guard-based algorithm, which can be implemented on top of an abstract model checking interface. We extend the generalized algorithm by introducing necessary disabling sets and adding a heuristics to improve state space reduction. The effect of the changes to the algorithm are measured using an implementation in the LTSmin model checking toolset. We compare our results to the Spin model checker, both on the benchmarks from the BEEM database, as well as on a number of Promela models. In many cases, the reduction obtained by our algorithm surpasses the ideal upper bound on the reduction obtained by the ample set method, as established empirically by Geldenhuys, Hansen and Valmari.

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Experiences in developing the mCRL2 toolset

Cited by 9 publications

References 19 publications

Towards Informed Swarm Verification

Towards Informed Swarm Verification

Abstraction-enriched Formal Methods Integration

Guard-Based Partial-Order Reduction

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