Ten Years of Saturation: A Petri Net Perspective

Ciardo, Gianfranco; Zhao, Yiwen; Jin, Xiaoqing

doi:10.1007/978-3-642-29072-5_3

Cited by 20 publications

(15 citation statements)

References 42 publications

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“…The algorithm divides the global next state function N into smaller parts: N = e∈E N e , where E is the set of events in the high level model. The granularity of the decomposition can be chosen arbitrarily [5].…”

Section: Saturationmentioning

confidence: 99%

“…The global relation can be expressed by the symbolic next state relations of the events: R(s, s ) = e∈E R e (s, s ). Applying N e to a given set of states represented by S results in N e (S) = RelProd(R e , S), where RelProd is RelProd(R, S) = {s |∃s ∈ S, (s, s ) ∈ R} [5]. The smaller the partitions, the less computation they need, but there is a minimum imposed by the high-level formalism.…”

Section: Saturationmentioning

confidence: 99%

“…We used the models 2 of Dining Philosophers (DPhil-N , [5]), Flexible Manufacturing System (FMS-N , [5]), Tower of Hanoi (Hanoi-N , [11]), an assembly line using Kanban method (Kanban-N , [5]), the Round Robin protocol (RR-N , [3]), and the Slotted Ring protocol (SR-N , [3]). …”

Section: Measurements On Benchmark Modelsmentioning

confidence: 99%

See 2 more Smart Citations

Improving Saturation-based Bounded Model Checking

2016

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Formal verification is becoming a fundamental step in assuring the correctness of safety-critical systems. Since these systems are often asynchronous and even distributed, their verification requires methods that can deal with huge or even infinite state spaces. Model checking is one of the current techniques to analyse the behaviour of systems, as part of the verification process.In this paper a symbolic bounded model checking algorithm is presented that relies on efficient saturation-based methods. The previous approaches are extended with new bounded state space exploration strategies. In addition, constrained saturation is also introduced to improve the efficiency of bounded model checking. Our measurements confirm that these approaches do not only offer a solution to deal with infinite state spaces, but in many cases they even outperform the original methods.

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Section: Saturationmentioning

confidence: 99%

Section: Saturationmentioning

confidence: 99%

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Improving Saturation-based Bounded Model Checking

2016

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“…The FMS model [3] represents a flexible manufacturing system. The parameter of the model determines the size of the state space, while the structure of the net is fixed.…”

Section: Comparison To Other Tools and Algorithmsmentioning

confidence: 99%

“…The results show that our algorithm outperforms both saturation and the SARA tool. The Kanban model [3] illustrates a production scheduling method. The parameter determines the size of the state space.…”

Section: Comparison To Other Tools and Algorithmsmentioning

confidence: 99%

New Search Strategies for the Petri Net CEGAR Approach

Hajdu

Vörös

Bartha

2015

Application and Theory of Petri Nets and Concurrency

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Abstract. Petri nets are a successful formal method for the modeling and verification of asynchronous, concurrent and distributed systems. Reachability analysis can provide important information about the behavior of the model. However, reachability analysis is a computationally hard problem, especially when the state space is infinite. Abstractionbased techniques are often applied to overcome complexity. In this paper we analyze an algorithm, which uses counterexample guided abstraction refinement. This algorithm proved its efficiency on the model checking contest. We examine the algorithm from a theoretical and practical point of view. On the theoretical side, we show that the algorithm cannot decide reachability for relatively simple instances. We propose a new iteration strategy to explore the invariant space, which extends the set of decidable problems. We also give proofs on the theoretical limits of our approach. On the practical side, we examine different search strategies and we present our new, complex strategy with superior performance compared to traditional strategies. Measurements show that our new contributions perform well for traditional benchmark models as well.

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i $$_\mathrm {Rank}$$ : A Variable Order Metric for DEDS Subject to Linear Invariants

Amparore

Ciardo

Donatelli

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

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Finding good variable orders for decision diagrams is essential for their effective use. We consider Multiway Decision Diagrams (MDDs) encoding a set of fixed-size vectors satisfying a set of linear invariants. Two critical applications of this problem are encoding the state space of a discrete-event discrete state system (DEDS) and encoding all solutions to a set of integer constraints. After studying the relations between the MDD structure and the constraints imposed by the linear invariants, we define i Rank , a new variable order metric that exploits the knowledge embedded in these invariants. We evaluate i Rank against other previously proposed metrics on a benchmark of 40 different DEDS and show that it is a better predictor of the MDD size and it is better at driving heuristics for the generation of good variable orders.

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Ten Years of Saturation: A Petri Net Perspective

Cited by 20 publications

References 42 publications

Improving Saturation-based Bounded Model Checking

Improving Saturation-based Bounded Model Checking

New Search Strategies for the Petri Net CEGAR Approach

i $$_\mathrm {Rank}$$ : A Variable Order Metric for DEDS Subject to Linear Invariants

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