Symbolic Reachability Analysis Based on SAT-Solvers

Abstract. This paper focuses on developing efficient inference techniques for improving conjunctive normal form (CNF) Boolean satisfiability (SAT) solvers. We analyze a variant of hyper binary resolution from various perspectives: We show that it can simulate the circuit-level technique of structural hashing and how it can be realized efficiently using so called tree-based lookahead. Experiments show that our implementation improves the performance of state-of-the-art CNFlevel SAT techniques on combinational equivalent checking instances.

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“…It is an integral part of many algorithms for manipulating different data structures representing circuits [8,9,10,11,12].…”

Section: Structural Hashing On the Cnf-level Via Hbrmentioning

confidence: 99%

Revisiting Hyper Binary Resolution

Heule

Järvisalo

Biere

2013

Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems

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“…Given two propositional formulas f 1 and f 2 and a set of propositional variables V ⊆ var(f 1 )∩var(f 2 ), we write f 1 ≡ V f 2 when the set of models of f 1 projected onto V is equal to the set of models of f 2 projected onto V . We graphically represent such formulas by means of direct acyclic graphs that avoid sub-formula replications (known as RBC and extensions thereof, see [1]). Yet, propositional solvers often require a conjunctive normal form (CNF) to work.…”

Section: Notationmentioning

confidence: 99%

Incremental Compilation-to-SAT Procedures

Benedetti

Bernardini

2005

Theory and Applications of Satisfiability Testing

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Abstract. We focus on incremental compilation-to-SAT procedures (iCTS), a promising way to push the standard CTS approaches beyond their limits. We propose the first comprehensive framework that encompasses all the aspects of an incremental decision procedure, from the encoding to the incremental solver. We apply our guidelines to a real-world CTS approach (Bounded Model Checking) and show how to modify both the generation mechanism of a real BMC tool (NuSMV) and the solving engine of a public-domain SAT solver (SIM). Related approaches and experimental results are discussed as well.

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“…Their performance is less sensitive to the problem sizes and they do not suffer from space explosion. As a result, various researchers have developed routines for performing Bounded Model Checking (BMC) using SAT [5][6][7][8]. Unlike symbolic model checking, BMC focuses on finding bugs of a bounded Fig.…”

Section: Introductionmentioning

confidence: 99%

Efficient Distributed SAT and SAT-Based Distributed Bounded Model Checking

Ganai¹,

Gupta²,

Yang³

et al. 2003

Lecture Notes in Computer Science

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Abstract. SAT-based Bounded Model Checking (BMC), though a robust and scalable verification approach, still is computationally intensive, requiring large memory and time. Interestingly, with the recent development of improved SAT solvers, it is frequently the memory limitation of a single server rather than time that becomes a bottleneck for doing deeper BMC search. Distributing computing requirements of BMC over a network of workstations can overcome the memory limitation of a single server, albeit at increased communication cost. In this paper, we present: a) a method for distributed-SAT over a network of workstations using a Master/Client model where each Client worsktation has an exclusive partition of the SAT problem and uses knowledge of partition topology to communicate with other Clients, b) a method for distributing SATbased BMC using the distributed-SAT. For the sake of scalability, at no point in the BMC computation does a single workstation have all the information. We experimented on a network of heterogenous workstations interconnected with a standard Ethernet LAN. To illustrate, on an industrial design with ~13K FFs and ~0.5M gates, the non-disributed BMC on a single workstation (with 4 Gb memory) ran out of memroy after reaching a depth of 120; on the otherhand, our SAT-based distributed BMC over 5 similar workstations was able to go upto 323 steps with a communication overhead of only 30%.

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Symbolic Reachability Analysis Based on SAT-Solvers

Cited by 118 publications

References 13 publications

Revisiting Hyper Binary Resolution

Revisiting Hyper Binary Resolution

Incremental Compilation-to-SAT Procedures

Efficient Distributed SAT and SAT-Based Distributed Bounded Model Checking

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