2000
DOI: 10.1145/347636.383378
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Finding bugs with a constraint solver

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Cited by 64 publications
(93 citation statements)
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“…The experiments show that our approach does work in practice for non-trivial data structures, and with time and space requirements which are as good as or better than those for the previous more specialized versions [25,14] and related approaches with similar goals [31,24,13,17].…”
Section: Implementation and Evaluationmentioning
confidence: 84%
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“…The experiments show that our approach does work in practice for non-trivial data structures, and with time and space requirements which are as good as or better than those for the previous more specialized versions [25,14] and related approaches with similar goals [31,24,13,17].…”
Section: Implementation and Evaluationmentioning
confidence: 84%
“…The constraint solver Alloy has been used to verify properties about bounded initial segments of computation sequences [24]. While this is not a complete decision procedure even for straight-line code, it finds many errors and can produce counterexamples.…”
Section: Related Workmentioning
confidence: 99%
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“…However, many large instances of SAT generated from real life problems can be successfully solved by heuristic SAT solvers. For example, SAT solvers find application in AI planning [2], circuit testing [3], software verification [4], microprocessor verification [5], model checking [6], etc. This has motivated research in efficient heuristic SAT solvers.…”
Section: Introductionmentioning
confidence: 99%
“…Stochastic methods are likely to be adopted in AI planning [2] and FPGA routing [13], where instances are likely to be satisfiable and proving unsatisfiability is not required. However, for many other domains, particularly some verification problems [4,6], the primary task is to prove unsatisfiability of the instances. Hence, complete SAT solvers are required in these cases.…”
Section: Introductionmentioning
confidence: 99%