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72
Counterexampleguided Abstraction Refinement
, 2000
"... We present an automatic iterative abstractionrefinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symb ..."
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Cited by 663 (62 self)
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We present an automatic iterative abstractionrefinement methodology in which the initial abstract model is generated by an automatic analysis of the control structures in the program to be verified. Abstract models may admit erroneous (or "spurious") counterexamples. We devise new symbolic techniques which analyze such counterexamples and refine the abstract model correspondingly.
Lazy theorem proving for bounded model checking over infinite domains
, 2002
"... Abstract. We investigate the combination of propositional SAT checkers with domainspecific theorem provers as a foundation for bounded model checking over infinite domains. Given a program M over an infinite state type, a linear temporal logic formula ' with domainspecific constraints over pr ..."
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Cited by 81 (11 self)
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Abstract. We investigate the combination of propositional SAT checkers with domainspecific theorem provers as a foundation for bounded model checking over infinite domains. Given a program M over an infinite state type, a linear temporal logic formula ' with domainspecific constraints over program states, and an upper bound k, our procedure determines if there is a falsifying path of length k to the hypothesis that M satisfies the specification '. This problem can be reduced to the satisfiability of Boolean constraint formulas. Our verification engine for these kinds of formulas is lazy in that propositional abstractions of Boolean constraint formulas are incrementally refined by generating lemmas on demand from an automated analysis of spurious counterexamples using theorem proving. We exemplify bounded model checking for timed automata and for RTL level descriptions, and investigate the lazy integration of SAT solving and theorem proving. 1 Introduction Model checking decides the problem of whether a system satisfies a temporal logic property by exploring the underlying state space. It applies primarily to finitestate systems but also to certain infinitestate systems, and the state space can be represented in symbolic or explicit form. Symbolic model checking has traditionally employed a boolean representation of state sets using binary decision diagrams (BDD) [4] as a way of checking temporal properties, whereas explicitstate model checkers enumerate the set of reachable states of the system.
Automated Abstraction Refinement for Model Checking Large State Spaces Using SAT Based Conflict Analysis
 IN PROCEEDINGS OF FMCAD
, 2002
"... We introduce a SAT based auto338m abstraction refinement framework for model checking systems with several thomGG4 state variables in the com o influenceo f the specificatio8 The abstractmo del iscoK060mEN8 by designating a large numbero f state variables as invisible. In co trast to previoN wo rk ..."
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Cited by 71 (12 self)
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We introduce a SAT based auto338m abstraction refinement framework for model checking systems with several thomGG4 state variables in the com o influenceo f the specificatio8 The abstractmo del iscoK060mEN8 by designating a large numbero f state variables as invisible. In co trast to previoN wo rk where invisible variables were treated as free inputs we describe a co06NGmEG7430m mo0 advantageo3 approF h in which the abstract transitio relatio isappro ximated by pre89889L6728 invisible variables during imageco8087FmEG0 The abstract co4 terexamplesorexamp fro mo delchecking the abstract mo del are symbo lically simulatedo the coG0K8K system using a stateoGNK7Kmo SAT checker. Ifno co43FK3 co4 terexample isfo640 a subseto f the invisible variables is reintro duced into the systemand thepro cess is repeated. The main co tributio o f this paper are two new algo37FmE fo identifying the relevant variablesto be reintro duced. Thesealgo78NNm mogo7 the SAT checking phase inom4F to analyze the impacto individual variables. Ourmetho d is co48NFF fo safetypro erties (AG p) in the sense that  perfoN06G0 permitting  a pro erty is either verifiedo dispro ved by aco4GKKm co4 terexample. Experimental results are givento demoGGmE40 the power of our method on realworld designs.
Relative Completeness of Abstraction Refinement for Software Model Checking
, 2002
"... Automated methods for an undecidable class of verification problems cannot be complete (terminate for every correct program). We therefore consider a new kind of quality measure for such methods, which is completeness relative to a (powerful but unrealistic) oraclebased method. More precisely, we a ..."
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Cited by 61 (5 self)
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Automated methods for an undecidable class of verification problems cannot be complete (terminate for every correct program). We therefore consider a new kind of quality measure for such methods, which is completeness relative to a (powerful but unrealistic) oraclebased method. More precisely, we ask whether an often implemented method known as "software model checking with abstraction refinement" is complete relative to fixpoint iteration with "oracleguided" widening. We show that whenever backward fixpoint iteration with oracleguided widening succeeds in proving a property' (for some sequence of widenings determined by the oracle) then software model checking with a particular form of backward refinement will succeed in proving'. Intuitively, this means that the use of fixpoint iteration over abstractions and a particular backwards refinement of the abstractions has the effect of exploring the entire state space of all possible sequences of widenings.
A Symbolic Approach to Predicate Abstraction
 COMPUTERAIDED VERIFICATION (CAV 2003), LNCS 2725
, 2003
"... Predicate abstraction is a useful form of abstraction for the verification of transition systems with large or infinite state spaces. One of the main bottlenecks of this approach is the extremely large number of decision procedures calls that are required to construct the abstract state space. I ..."
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Cited by 60 (14 self)
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Predicate abstraction is a useful form of abstraction for the verification of transition systems with large or infinite state spaces. One of the main bottlenecks of this approach is the extremely large number of decision procedures calls that are required to construct the abstract state space. In this paper we propose the use of a symbolic decision procedure and its application for predicate abstraction. The advantage of the approach is that it reduces the number of calls to the decision procedure exponentially and also provides for reducing the recomputations inherent in the current approaches. We provide two implementations of the symbolic decision procedure: one based on BDDs which leverages the current advances in early quantification algorithms, and the other based on SATsolvers. We also demonstrate our approach with quantified predicates for verifying parameterized systems. We illustrate the effectiveness of this approach on benchmarks from the verification of microprocessors, communication protocols, parameterized systems, and Microsoft Windows device drivers.
CounterExample Based Predicate Discovery in Predicate Abstraction
 In Formal Methods in ComputerAided Design
, 2002
"... The application of predicate abstraction to parameterized systems requires the use of quantified predicates. These predicates cannot be found automatically by existing techniques and are tedious for the user to provide. In this work we demonstrate a method of discovering most of these predicates aut ..."
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Cited by 53 (2 self)
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The application of predicate abstraction to parameterized systems requires the use of quantified predicates. These predicates cannot be found automatically by existing techniques and are tedious for the user to provide. In this work we demonstrate a method of discovering most of these predicates automatically by analyzing spurious abstract counterexample traces. Since predicate discovery for unbounded state systems is an undecidable problem, it can fail on some problems.
Abstraction refinement for termination
 In Proceedings of the 12 th International Static Analysis Symposium
"... Abstract. Abstraction can often lead to spurious counterexamples. Counterexampleguided abstraction refinement is a method of strengthening abstractions based on the analysis of these spurious counterexamples. For invariance properties, a counterexample is a finite trace that violates the invariant; ..."
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Cited by 50 (12 self)
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Abstract. Abstraction can often lead to spurious counterexamples. Counterexampleguided abstraction refinement is a method of strengthening abstractions based on the analysis of these spurious counterexamples. For invariance properties, a counterexample is a finite trace that violates the invariant; it is spurious if it is possible in the abstraction but not in the original system. When proving termination or other liveness properties of infinitestate systems, a useful notion of spurious counterexamples has remained an open problem. For this reason, no counterexampleguided abstraction refinement algorithm was known for termination. In this paper, we address this problem and present the first known automatic counterexampleguided abstraction refinement algorithm for termination proofs. We exploit recent results on transition invariants and transition predicate abstraction. We identify two reasons for spuriousness: abstractions that are too coarse, and candidate transition invariants that are too strong. Our counterexampleguided abstraction refinement algorithm successively weakens candidate transition invariants and refines the abstraction. 1
Sat based abstractionrefinement using ILP and machine learning techniques
 In Proceedings of CAV
, 2002
"... ..."
Interpolantbased transition relation approximation
 In CAV 05: ComputerAided Verification, LNCS 3576
, 2005
"... Abstract. In predicate abstraction, exact image computation is problematic, requiring in the worst case an exponential number of calls to a decision procedure. For this reason, software model checkers typically use a weak approximation of the image. This can result in a failure to prove a property, ..."
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Cited by 41 (4 self)
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Abstract. In predicate abstraction, exact image computation is problematic, requiring in the worst case an exponential number of calls to a decision procedure. For this reason, software model checkers typically use a weak approximation of the image. This can result in a failure to prove a property, even given an adequate set of predicates. We present an interpolantbased method for strengthening the abstract transition relation in case of such failures. This approach guarantees convergence given an adequate set of predicates, without requiring an exact image computation. We show empirically that the method converges more rapidly than an earlier method based on counterexample analysis. 1