RuleBase: an industry-oriented formal verification tool

Beer, Ilan; Ben-David, Shoham; Eisner, Cindy; Landver, Avner

doi:10.1109/dac.1996.545656

Cited by 60 publications

(66 citation statements)

References 12 publications

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“…We implemented the translation from conjunctive partitioned transition relation to partial disjunctive partitioned transition relation in the IBM model checker RuleBase [1]. We compared reachability analysis using conjunctive partitions with reachability analysis using partial disjunctive partitions on models that were translated from software programs.…”

Section: Resultsmentioning

confidence: 99%

“…Thus, the value pc = 7, which is related to this statement, will be in more than one disjunctive partition. If we had used dep pcs x (pc) the state {pc = 7; i = 2} would have been both in the partition of a [2] and a [1]. As a result, after conjuncting the disjunctive partition of a [1] withȳ =ȳ it would have contained another transition, that does not exist in the original model and changes only pc and not a [1] or a [2].…”

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

“…The RuleBase model checker [1] uses ordered conjunctive partitioning, and previous work showed its application to general purpose software [5,6]. In this paper, we show how disjunctive partitioning can be used to increase the efficiency of symbolic model checking for software.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, after conjuncting the disjunctive partition of a [1] withȳ =ȳ it would have contained another transition, that does not exist in the original model and changes only pc and not a [1] or a [2]. This transition would have been entered to the disjunctive partition of a [1] because a [2] is inȳ. The quantification that appears in por R x (pc, x,ȳ, x , pc ) is discussed in detail later.…”

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

“…If we had used dep pcs x (pc) the state {pc = 7; i = 2} would have been both in the partition of a [2] and a [1]. As a result, after conjuncting the disjunctive partition of a [1] withȳ =ȳ it would have contained another transition, that does not exist in the original model and changes only pc and not a [1] or a [2]. This transition would have been entered to the disjunctive partition of a [1] because a [2] is inȳ.…”

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

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Efficient Symbolic Model Checking of Software Using Partial Disjunctive Partitioning

Barner

Rabinovitz

2003

Lecture Notes in Computer Science

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Abstract. This paper presents a method for taking advantage of the efficiency of symbolic model checking using disjunctive partitions, while keeping the number and the size of the partitions small. We define a restricted form of a Kripke structure, called an or-structure, for which it is possible to generate small disjunctive partitions. By changing the image and pre-image procedures, we keep even smaller partial disjunctive partitions in memory. In addition, we show how to translate a (software) program to an or-structure, in order to enable efficient symbolic model checking of the program using its disjunctive partitions. We build one disjunctive partition for each state variable in the model directly from the conjunctive partition of the same variable and independently of all other partitions. This method can be integrated easily into existing model checkers, without changing their input language, and while still taking advantage of reduction algorithms which prefer conjunctive partitions.

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Section: Resultsmentioning

confidence: 99%

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

Section: Intersect the Quantification Of X From Dep Statesmentioning

confidence: 99%

See 3 more Smart Citations

Efficient Symbolic Model Checking of Software Using Partial Disjunctive Partitioning

Barner

Rabinovitz

2003

Lecture Notes in Computer Science

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Tuning SAT Checkers for Bounded Model Checking

Shtrichman

2000

Lecture Notes in Computer Science

115

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Bounded Model Checking based on SAT methods has recently been introduced as a complementary technique to BDD-based Symbolic Model Checking. The basic idea is to search for a counter example in executions whose length is bounded by some integer k. The BMC problem can be efficiently reduced to a propositional satisfiability problem, and can therefore be solved by SAT methods rather than BDDs. SAT procedures are based on general-purpose heuristics that are designed for any propositional formula. We show that the unique characteristics of BMC formulas can be exploited for a variety of optimizations in the SAT checking procedure. Experiments with these optimizations on real designs proved their efficiency in many of the hard test cases, comparing to both the standard SAT procedure and a BDD-based model checker.

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Achieving Scalability in Parallel Reachability Analysis of Very Large Circuits

Heyman

Grumberg

Schuster

2000

Computer Aided Verification

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This paper presents a scalable method for parallel symbolic reachability analysis on a distributed-memory environment of workstations. Our method makes use of an adaptive partitioning algorithm which achieves high reduction of space requirements. The memory balance is maintained by dynamically repartitioning the state space throughout the computation. A compact BDD representation allows coordination by shipping BDDs from one machine to another, where different variable orders are allowed. The algorithm uses a distributed termination protocol with none of the memory modules preserving a complete image of the set of reachable states. No external storage is used on the disk; rather, we make use of the network which is much faster. We implemented our method on a standard, loosely-connected environment of workstations, using a high-performance model checker. Our initial performance evaluation using several large circuits shows that our method can handle models that are too large to fit in the memory of a single node. The efficiency of the partitioning algorithm is linear in the number of workstations employed, with a 40-60% efficiency. A corresponding decrease of space requirements is measured throughout the reachability analysis. Our results show that the relatively-slow network does not become a bottleneck, and that computation time is kept reasonably small.

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RuleBase: an industry-oriented formal verification tool

Cited by 60 publications

References 12 publications

Efficient Symbolic Model Checking of Software Using Partial Disjunctive Partitioning

Efficient Symbolic Model Checking of Software Using Partial Disjunctive Partitioning

Tuning SAT Checkers for Bounded Model Checking

Achieving Scalability in Parallel Reachability Analysis of Very Large Circuits

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