Completeness and Complexity of Bounded Model Checking

Clarke, Edmund M.; Kroening, Daniel; Ouaknine, Joël; Strichman, Ofer

doi:10.1007/978-3-540-24622-0_9

Cited by 85 publications

(89 citation statements)

References 10 publications

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“…Both of these are achieved while maintaining the efficiency of the original encoding [18]. Additionally, our encoding is able to prove properties of full PLTL with smaller bounds than previous methods for LTL [8,9], as these papers employ a method for translating generalised Büchi automata to standard (non-generalised) Büchi automata in a way which does not preserve the minimal length of counterexamples. We have implemented our method in the NuSMV model checker [19] and present promising experimental results.…”

Section: Introductionmentioning

confidence: 95%

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Incremental and Complete Bounded Model Checking for Full PLTL

Heljanko¹,

Junttila²,

Latvala³

2005

Computer Aided Verification

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Abstract. Bounded model checking is an efficient method for finding bugs in system designs. The major drawback of the basic method is that it cannot prove properties, only disprove them. Recently, some progress has been made towards proving properties of LTL. We present an incremental and complete bounded model checking method for the full linear temporal logic with past (PLTL). Compared to previous works, our method both improves and extends current results in many ways: (i) our encoding is incremental, resulting in improvements in performance, (ii) we can prove non-existence of a counterexample at shallower depths in many cases, and (iii) we support full PLTL. We have implemented our method in the NuSMV2 model checker and report encouraging experimental results.

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Section: Introductionmentioning

confidence: 95%

“…Clarke et al [8] show how the completeness threshold can be computed for general LTL properties by computing the recurrence diameter of the product of the system and a Büchi automaton. Awedh and Somenzi [9] apply the same approach, but they use a refined method for calculating the completeness threshold.…”

Section: Introductionmentioning

confidence: 99%

Incremental and Complete Bounded Model Checking for Full PLTL

Heljanko¹,

Junttila²,

Latvala³

2005

Computer Aided Verification

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“…Bounded Semantics of LTL [4], [5], [8], [9] Let AP be a set of atomic propositions., ranged over by p, q, · · ·. Then LTL formulas over AP are defined recursively as follows: atomic propositions are LTL formulas; and if φ 1 and φ 2 are LTL formulas so are Xφ (neXt),…”

Section: Bounded Ltl Model Checkingmentioning

confidence: 99%

“…As an application, we can discuss paths that satisfy/violate an LTL formula with the shortest length. BMC problems are typically solved by reducing SAT problems, therefore the complexity of BMC of this approach is determined using the number of propositional variables to appear in formula by SAT encoding [8], [9]. The translation results in O(k · | log(S )| + (k + 1) 2 · |φ|) variables, where S is the number of states in model M, k is the bound, and |φ| is the length of φ.…”

Section: Bounded Ltl Model Checkingmentioning

confidence: 99%

Automated Route Planning for Milk-Run Transport Logistics with the NuSMV Model Checker

Kitamura

Okamoto

2013

IEICE Trans. Inf. & Syst.

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SUMMARYIn this paper, we propose and implement an automated route planning framework for milk-run transport logistics by applying model checking techniques. First, we develop a formal specification framework for milk-run transport logistics. The framework adopts LTL (Linear Temporal Logic), a language based on temporal logics, as a specification language for users to be able to flexibly and formally specify complex delivery requirements for trucks. Then by applying the bounded semantics of LTL, the framework then defines the notion of "optimal truck routes", which mean truck routes on a given route map that satisfy given delivery requirements (specified by LTL) with the minimum cost. We implement the framework as an automated route planner using the NuSMV model checker, a state-of-the-art bounded model checker. The automated route planner, given route map and delivery requirements, automatically finds optimal trucks routes on the route map satisfying the given delivery requirements. The feasibility of the implementation design is investigated by analysing its computational complexity and by showing experimental results.

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“…There is a bound (called completeness threshold ) such that the absence of flaws within the completeness threshold implies the satisfiability of the property [1,5]. One often uses over-approximations of the completeness threshold in practice since computing the exact value is hard.…”

Section: Introductionmentioning

confidence: 99%

Proving ∀μ-Calculus Properties with SAT-Based Model Checking

Wang

2005

Formal Techniques for Networked and Distributed Systems - FORTE 2005

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Abstract. In this paper, we present a complete bounded model checking algorithm for the universal fragment of µ-calculus. The new algorithm checks the completeness of bounded proof of each property on the fly and does not depend on prior knowledge of the completeness thresholds. The key is to combine both local and bounded model checking techniques and use SAT solvers to perform local model checking on finite Kripke structures. Our proof-theoretic approach works for any property in the specification logic and is more general than previous work on specific properties. We report experimental results to compare our algorithm with the conventional BDD-based algorithm.

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Completeness and Complexity of Bounded Model Checking

Cited by 85 publications

References 10 publications

Incremental and Complete Bounded Model Checking for Full PLTL

Incremental and Complete Bounded Model Checking for Full PLTL

Automated Route Planning for Milk-Run Transport Logistics with the NuSMV Model Checker

Proving ∀μ-Calculus Properties with SAT-Based Model Checking

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