Efficient Proof Engines for Bounded Model Checking of Hybrid Systems

Fränzle, Martin; Herde, Christian

doi:10.1016/j.entcs.2004.08.061

Cited by 26 publications

(19 citation statements)

References 9 publications

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“…In addition to the eager dependency check for linear constraints above, we use HySAT [9] as a decision procedure for the equivalence of nodes in FO-AIGs (representing boolean combinations of linear constraints). If two nodes are proven to be equivalent (taking the linear constraints into account), then these nodes can be merged, leading to a compaction of the representation or leading to the detection of a fixpoint in the model checking computation.…”

Section: Methods Dealing With the Interaction Of The Boolean And The mentioning

confidence: 99%

“…HySAT [9] is a bounded model checker for linear hybrid systems. It combines Davis-Putnam style SAT solving techniques with linear programming, and implements state of the art optimizations such at nonchronological backjumping, conflict driven learning and lazy clause evaluation.…”

Section: Related Workmentioning

confidence: 99%

“…Of central importance is the ability to perform a subsumption check on our hybrid state-set representation in order to detect whether a fixpoint has been reached during model checking. HySAT [9] is one of the tools we use for that purpose. However, a key point of our approach is the idea to avoid expensive applications of decision procedures as much as possible.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Verification of Hybrid Systems with Large Discrete State Space

Damm

Disch

Hungar

et al. 2006

Automated Technology for Verification and Analysis

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Abstract.We address the problem of model checking hybrid systems which exhibit nontrivial discrete behavior and thus cannot be treated by considering the discrete states one by one, as most currently available verification tools do. Our procedure relies on a deep integration of several techniques and tools. An extension of AND-Inverter-Graphs (AIGs) with first-order constraints serves as a compact representation format for sets of configurations which are composed of continuous regions and discrete states. Boolean reasoning on the AIGs is complemented by firstorder reasoning in various forms and on various levels. These include implication checks for simple constraints, test vector generation for fast inequality checks of boolean combinations of constraints, and an exact subsumption check for representations of two configurations.These techniques are integrated within a model checker for universal CTL. Technically, it deals with discrete-time hybrid systems with linear differentials. The paper presents the approach, its prototype implementation, and first experimental data.

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Section: Methods Dealing With the Interaction Of The Boolean And The mentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic Verification of Hybrid Systems with Large Discrete State Space

Damm

Disch

Hungar

et al. 2006

Automated Technology for Verification and Analysis

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“…Otherwise, if the abstraction has a solution, then the LP-solver checks whether there is a corresponding solution in the real domain. I.e., the LP-solver collects all those real constraints whose abstraction variables are true and the negation of all those whose abstraction variables are false, and checks whether they are together satisfiable using a Simplex-based approach similar to [21]. If yes, then we have found a solution for the concrete problem.…”

Section: Lp-sat-checkingmentioning

confidence: 98%

“…In the discrete case the check is carried out by a SAT-solver, i.e., a Boolean satisfiability checker, whereas in the mixed discrete-continuous case of hybrid and timed automata the check is usually done by combining a SAT-and an LP-solver (Linear Programming, see Section 5.2). Some popular solver are, e.g., ZChaff [28], BerkMin [23], MiniSAT [20], HySat [21],MathSAT [5], CVC Lite [8], and ICS [16]. Our approach, as introduced in the following sections, is not restricted to any fixed application domain.…”

Section: Introductionmentioning

confidence: 99%

Bounded Model Checking with Parametric Data Structures

Ábrahám

Herbstritt

Becker

et al. 2007

Electronic Notes in Theoretical Computer Science

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Bounded Model Checking (BMC) is a successful refutation method to detect errors in not only circuits and other binary systems but also in systems with more complex domains like timed automata or linear hybrid automata. Counterexamples of a fixed length are described by formulas in a decidable logic, and checked for satisfiability by a suitable solver.In an earlier paper we analyzed how BMC of linear hybrid automata can be accelerated already by appropriate encoding of counterexamples as formulas and by selective conflict learning. In this paper we introduce parametric datatypes for the internal solver structure that, taking advantage of the symmetry of BMC problems, remarkably reduce the memory requirements of the solver.

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Stochastic Reachability Analysis of Hybrid Systems

Bujorianu

2012

Communications and Control Engineering

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Efficient Proof Engines for Bounded Model Checking of Hybrid Systems

Cited by 26 publications

References 9 publications

Automatic Verification of Hybrid Systems with Large Discrete State Space

Automatic Verification of Hybrid Systems with Large Discrete State Space

Bounded Model Checking with Parametric Data Structures

Stochastic Reachability Analysis of Hybrid Systems

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