Bounded Model Checking with QBF

Dershowitz, Nachum; Hanna, Ziyad; Katz, Jacob

doi:10.1007/11499107_32

Cited by 58 publications

(42 citation statements)

References 28 publications

(34 reference statements)

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“…In [26], a QBF-based BMC encoding is given, which introduces two universal state variables, and hence Θ(b) universal bits. A k-induction formulation using QBF is given in [27], which uses k universal bits to traverse the ILA time-frames using a forced one-hot encoding.…”

Section: Previous Workmentioning

confidence: 99%

“…A robust QBF-based solution for VLSI CAD problems requires a succinct problem translation into a QBF instance, coupled with an effective solver. To this end, a few QBF encodings for formal verification problems have been investigated [26], [27] but experiments indicate that memory savings over SAT come at the expense of run-time performance.…”

Section: • H Mangassarian Is With the Department Of Electrical And Cmentioning

confidence: 99%

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Robust QBF Encodings for Sequential Circuits with Applications to Verification, Debug, and Test

Mangassarian

Veneris

Benedetti

2010

IEEE Trans. Comput.

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Abstract-Formal CAD tools operate on mathematical models describing the sequential behavior of a VLSI design. With the growing size and state-space of modern digital hardware designs, the conciseness of this mathematical model is of paramount importance in extending the scalability of those tools, provided that the compression does not come at the cost of reduced performance. Quantified Boolean Formula satisfiability (QBF) is a powerful generalization of Boolean satisfiability (SAT). It also belongs to the same complexity class as many CAD problems dealing with sequential circuits, which makes it a natural candidate for encoding such problems. This work proposes a succinct QBF encoding for modeling sequential circuit behavior. The encoding is parametrized and further compression is achieved using time-frame windowing. Comprehensive hardware constructions are used to illustrate the proposed encodings. Three notable CAD problems, namely bounded model checking, design debugging and sequential test pattern generation, are encoded as QBF instances to demonstrate the robustness and practicality of the proposed approach. Extensive experiments on OpenCore circuits show memory reductions in the order of 90% and demonstrate competitive run-times compared to state-of-the-art SAT techniques. Furthermore, the number of solved instances is increased by 16%. Admittedly, this work encourages further research in the use of QBF in CAD for VLSI.

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Section: Previous Workmentioning

confidence: 99%

Section: • H Mangassarian Is With the Department Of Electrical And Cmentioning

confidence: 99%

Robust QBF Encodings for Sequential Circuits with Applications to Verification, Debug, and Test

Mangassarian

Veneris

Benedetti

2010

IEEE Trans. Comput.

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show abstract

“…Recent activity in this area [10,16] suggest though, that this too does not perform as well as SAT solvers.…”

Section: Related Workmentioning

confidence: 99%

Bounded Model Checking with Description Logic Reasoning

Ben-David

Trefler

Weddell

Lecture Notes in Computer Science

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Abstract. Model checking is a technique for verifying that a finite-state concurrent system is correct with respect to its specification. In bounded model checking (BMC), the system is unfolded until a given depth, and translated into a CNF formula. A SAT solver is then applied to the CNF formula, to find a satisfying assignment. Such a satisfying assignment, if found, demonstrates an error in the model of the concurrent system. Description Logic (DL) is a family of knowledge representation formalisms, for which reasoning is based on tableaux techniques. We show how Description Logic can serve as a natural setting for representing and solving a BMC problem. We formulate a bounded model checking problem as a consistency problem in the DL dialect ALCI. Our formulation results in a compact representation of the model, one that is linear in the size of the model description, and does not involve any unfolding of the model. Experimental results, using the DL reasoner FaCT++, significantly improve on a previous approach that used DL reasoning for model checking.

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“…QBF [36,19] is an important research area with many applications [28,33,6,31,21,16,24,5,30]. Progress has been impressive in recent years, but in practice QBF solvers lack the generic applicability on PSPACE hard problems as SAT solvers on NP hard problems.…”

Section: Introductionmentioning

confidence: 99%

Nenofex: Expanding NNF for QBF Solving

Lonsing

Biere

Theory and Applications of Satisfiability Testing – SAT 2008

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Abstract. The topic of this paper is Nenofex, a solver for quantified boolean formulae (QBF) in negation normal form (NNF), which relies on expansion as the core technique for eliminating variables. In contrast to eliminating existentially quantified variables by resolution on CNF, which causes the formula size to increase quadratically in the worst case, expansion on NNF is involved with only a linear increase of the formula size. This property motivates the use of NNF instead of CNF combined with expansion. In Nenofex, a formula in NNF is represented as a tree with structural restrictions in order to keep its size small and distances from nodes to the root short. Expansions of variables are scheduled based on estimated expansion cost. The variable with the smallest estimated cost is expanded first. In order to remove redundancy from the formula, limited versions of two approaches from the domain of circuit optimization have been integrated. Experimental results on latest benchmarks show that Nenofex indeed exceeds a given memory limit less frequently than a resolution-based QBF solver for CNF, but also that there is the need for runtime-related improvements.

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Bounded Model Checking with QBF

Cited by 58 publications

References 28 publications

Robust QBF Encodings for Sequential Circuits with Applications to Verification, Debug, and Test

Robust QBF Encodings for Sequential Circuits with Applications to Verification, Debug, and Test

Bounded Model Checking with Description Logic Reasoning

Nenofex: Expanding NNF for QBF Solving

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