Saturation: An Efficient Iteration Strategy for Symbolic State—Space Generation

Ciardo, Gianfranco; Lüttgen, Gerald; Siminiceanu, Radu

doi:10.1007/3-540-45319-9_23

Cited by 103 publications

(123 citation statements)

References 21 publications

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“…Table 1 shows runtimes and total memory requirements using W workstations for sequential S m A r T (SEQ) [11] and the original S m A r T N ow (DISTR) [5], and the percentage change w.r.t. DISTR for the naïve (NAÏVE), the history-based (HIST) [6] and the pattern-length-adjusted (LENGTH) or weighted-score-adjusted (SCORE) speculative firing predictions [7]; 'd'means that dynamic memory load balancing is triggered and 's' means that, in addition, memory swapping occurs.…”

Section: Resultsmentioning

confidence: 99%

“…Results in [11][12][13] consistently show that Saturation outperforms breadth-first symbolic state-space generation by several orders of magnitude in both memory and time, making it arguably the most efficient state-space generation algorithm for globally asynchronous locally synchronous discrete event systems. Thus, it makes sense to attempt its parallelization, while parallelizing the less efficient breadth-first approach would not offset the enormous speedups and memory reductions of Saturation.…”

Section: Saturation-based Fixpoint Iteration Strategymentioning

confidence: 94%

“…For N , we adopt a Kronecker representation inspired by work on Markov chains [3], possible if the model is Kronecker consistent [10,11]. Each N e is conjunctively decomposed into K local nextstate functions N k,e , for K ≥k ≥1, satisfying, in any state…”

Section: Symbolic Encoding Of Nmentioning

confidence: 99%

“…In addition to efficiently representing N , the Kronecker encoding allows us to recognize event locality [10,22] and employ Saturation [11]. We say that event e is independent of level k if N k,e = I, the identity matrix.…”

Section: Saturation-based Fixpoint Iteration Strategymentioning

confidence: 99%

See 3 more Smart Citations

Speculative Image Computation for Distributed Symbolic Reachability Analysis

Chung

Ciardo

2009

Journal of Logic and Computation

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The Saturation-style fixpoint iteration strategy for symbolic reachability analysis is particularly effective for globally asynchronous locally synchronous discrete-state systems. However, its inherently sequential nature makes it difficult to parallelize Saturation on a network workstations (NOW). We then propose the idea of using idle workstation time to perform speculative image computations. Since an unrestrained prediction may make excessive use of computational resources, we introduce a history-based approach to dynamically recognize image computation (event firing) patterns and explore only firings that conform to these patterns. In addition, we employ an implicit encoding for the patterns, so that the actual image computation history can be efficiently preserved. Experiments not only show that image speculation works on a realistic model, but also indicate that the use of an implicit encoding together with two heuristics results in a better informed speculation.

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Section: Resultsmentioning

confidence: 99%

Section: Saturation-based Fixpoint Iteration Strategymentioning

confidence: 94%

Section: Symbolic Encoding Of Nmentioning

confidence: 99%

Section: Saturation-based Fixpoint Iteration Strategymentioning

confidence: 99%

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Speculative Image Computation for Distributed Symbolic Reachability Analysis

Chung

Ciardo

2009

Journal of Logic and Computation

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“…We also compared our approach to the well-known saturation-based model checking algorithm [2], [14]. The results can be seen in Table 1, where TO refers to an unacceptable run-time (> 600 seconds), ERR means a run-time exception and NS implies that the algorithm terminated, but could not solve the problem.…”

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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Symbolic Model Checking for Avionics

Gnesi

Margaria

2012

Formal Methods for Industrial Critical Systems

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Saturation: An Efficient Iteration Strategy for Symbolic State—Space Generation

Cited by 103 publications

References 21 publications

Speculative Image Computation for Distributed Symbolic Reachability Analysis

Speculative Image Computation for Distributed Symbolic Reachability Analysis

New Search Strategies for the Petri Net CEGAR Approach

Symbolic Model Checking for Avionics

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