Generating BDDs for symbolic model checking in CCS

Enders, Reinhard; Filkorn, Thomas; Taubner, Dirk

doi:10.1007/3-540-55179-4_20

Cited by 34 publications

(27 citation statements)

References 4 publications

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“…The problem of managing huge state spaces is not new and it has been faced in many works (Burch, Clarke, McMillan, Dill, and Hwang 1990;Enders, Filkorn, and Taubner 1993;Siegle 1998), where several symbolic techniques have been proposed. These techniques use smart data structures to symbolically encode the system states achieving less memory occupancy than the one necessary to explicitly store them.…”

Section: Taylor and Francismentioning

confidence: 99%

Two-layer symbolic representation for stochastic models with phase-type distributed events

Longo

Scarpa

2013

International Journal of Systems Science

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Among the techniques that have been proposed for the analysis of non-Markovian models, the state space expansion approach showed great flexibility in terms of modelling capacities.The principal drawback is the explosion of the state space. This paper proposes a two-layer symbolic method for efficiently storing the expanded reachability graph of a non-Markovian model in the case in which continuous phase-type distributions are associated with the firing times of system events, and different memory policies are considered. At the lower layer, the reachability graph is symbolically represented in the form of a set of Kronecker matrices, while, at the higher layer, all the information needed to correctly manage event memory is stored in a multi-terminal multi-valued decision diagram. Such an information is collected by applying a symbolic algorithm, which is based on a couple of theorems. The efficiency of the proposed approach, in terms of memory occupation and execution time, is shown by applying it to a set of non-Markovian stochastic Petri nets and comparing it with a classical explicit expansion algorithm. Moreover, a comparison with a classical symbolic approach is performed whenever possible.

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Section: Taylor and Francismentioning

confidence: 99%

Two-layer symbolic representation for stochastic models with phase-type distributed events

Longo

Scarpa

2013

International Journal of Systems Science

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“…BDDs are used to represent formulas and relations in [8] for symbolic model checking. As far as process algebra tools are concerned, the use of BDDs has been tested with encouraging results in [10] and [36], More general approaches to the state explosion problem are presented when dealing with truly concurrent semantics in, e.g., [49,59,75]. However, all these techniques only preserve safety and liveness properties, but not bisimulation equivalences.…”

Section: Classification Criteriamentioning

confidence: 99%

“…It includes the system AUTO [11,32] and Ecrins [83,86], the Concurrency Workbench [21,22], Aldebaran [38,39], Squiggles [4], TAV [45], the ACP-tool [105], the Branching-tool [48], Winston [82], MEC [2], CIRCAL [78], PVE [36,37] and the Pisa Tool [54,56]. The typical approach used by these tools is to generate the state space of the system under investigation and then to apply an algorithm to decide on the behavioral equivalences of processes on it, or a model checking algorithm to see whether the system satisfies given properties.…”

Section: Description Of the Toolsmentioning

confidence: 99%

Automatic verification of distributed systems: The process algebra approach

Inverardi

Priami

1996

Form Method Syst Des

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“…In these cases, the transition relation has proven to be an excellent means to mechanize Process Algebra manipulations [14], [10] and the proof of Temporal Logic properties [3]. For these reasons, it is extremely important to have efficient ways to build it and to use it.…”

Section: Discussionmentioning

confidence: 99%

“…This second approach, although the image computation algorithm is not as simple as the one for the transition relation, allowed a major breakthrough in terms of efficiency and applicability. The transition function is less general than the transition relation, as the former must be deterministic, the latter, though implemented by BDDs, easily supports non-determinism, used for example with Process Algebras [3], [14], [10]. Moreover, whereas pre-image computation is immediate for the transition relation, it is more awkward for transition functions.…”

Section: Introductionmentioning

confidence: 99%

Advancements in symbolic traversal techniques

Cabodi

Camurati

Lecture Notes in Computer Science

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Abstract. Symbolic state space traversal techniques are one of the most notable achievements in the fields of formal verification and of automated synthesis. Transition functions and transition relations are two alternative approaches. In terms of efficiency, transition functions have proven to be superior, although the transition relation is much more expressive. This paper brings the transition relation back to a new life, profiting from recent advancements in the fields of boolean function representation, simplification, and image computation represented by BDDs and by the generalized cofactor operator. A theoretical result allows us to considerably simplify both the process of building the transition relation and of traversing the state space. Experimental results show that performances similar to those of the transition function are obtained.

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Generating BDDs for symbolic model checking in CCS

Cited by 34 publications

References 4 publications

Two-layer symbolic representation for stochastic models with phase-type distributed events

Two-layer symbolic representation for stochastic models with phase-type distributed events

Automatic verification of distributed systems: The process algebra approach

Advancements in symbolic traversal techniques

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