Symbolic Model Checking without BDDs
TACAS '99 Proceedings of the 5th International Conference on Tools and Algorithms for Construction and Analysis of Systems
Proceedings of the 31st ACM SIGPLAN-SIGACT symposium on Principles of programming languages
LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
SYNERGY: a new algorithm for property checking
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Widening operators for powerset domains
International Journal on Software Tools for Technology Transfer (STTT) - A View from Formal Methods 2003 (pp 301-354); Special Section on Recent Advances in Hardware Verification (pp 355-447)
Using counterexamples for improving the precision of reachability computation with polyhedra
CAV'07 Proceedings of the 19th international conference on Computer aided verification
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Automatically refining abstract interpretations
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
BOXES: a symbolic abstract domain of boxes
SAS'10 Proceedings of the 17th international conference on Static analysis
Efficient predicate abstraction of program summaries
NFM'11 Proceedings of the Third international conference on NASA Formal methods
CPACHECKER: a tool for configurable software verification
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Lazy abstraction with interpolants
CAV'06 Proceedings of the 18th international conference on Computer Aided Verification
From under-approximations to over-approximations and back
TACAS'12 Proceedings of the 18th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Competition on software verification
TACAS'12 Proceedings of the 18th international conference on Tools and Algorithms for the Construction and Analysis of Systems
UFO: a framework for abstractionand interpolation-based software verification
CAV'12 Proceedings of the 24th international conference on Computer Aided Verification
Explicit-State software model checking based on CEGAR and interpolation
FASE'13 Proceedings of the 16th international conference on Fundamental Approaches to Software Engineering
UFO: verification with interpolants and abstract interpretation
TACAS'13 Proceedings of the 19th international conference on Tools and Algorithms for the Construction and Analysis of Systems
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
Disjunctive interpolants for horn-clause verification
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
Automatic abstraction in SMT-Based unbounded software model checking
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
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Abstract interpretation (AI) is one of the most scalable automated approaches to program verification available today. To achieve efficiency, many steps of the analysis, e.g., joins and widening, lose precision. As a result, AI often produces false alarms, coming from the inability to find a safe inductive invariant even when it exists in a chosen abstract domain. To tackle this problem, we present Vinta, an iterative algorithm that uses Craig interpolants to refine and guide AI away from false alarms. Vinta is based on a novel refinement strategy that capitalizes on recent advances in SMT and interpolation-based verification to (a) find counterexamples to justify alarms produced by AI, and (b) to strengthen an invariant to exclude alarms that cannot be justified. The refinement process continues until either a safe inductive invariant is computed, a counterexample is found, or resources are exhausted. This strategy allows Vinta to recover precision lost in many AI steps, and even to compute inductive invariants that are inexpressible in the chosen abstract domain (e.g., by adding disjunctions and new terms). We have implemented Vinta and compared it against top verification tools from the recent software verification competition. Our results show that Vinta outperforms state-of-the-art verification tools.