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Predicate learning and selective theory deduction for a difference logic solver
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MathSAT: Tight Integration of SAT and Mathematical Decision Procedures
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SMT(CLU): a step toward scalability in system verification
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Encoding RTL Constructs for MathSAT: a Preliminary Report
Electronic Notes in Theoretical Computer Science (ENTCS)
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Bounded model checking of analog and mixed-signal circuits using an SMT solver
ATVA'07 Proceedings of the 5th international conference on Automated technology for verification and analysis
Randomized constraint solvers: a comparative study
Innovations in Systems and Software Engineering
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ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Finding first-order minimal unsatisfiable cores with a heuristic depth-first-search algorithm
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
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Decision procedures for SAT, SAT modulo theories and beyond. the barcelogictools
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Deciding separation logic formulae by SAT and incremental negative cycle elimination
LPAR'05 Proceedings of the 12th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
Compositional verification of asynchronous processes via constraint solving
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DPLL(T) with exhaustive theory propagation and its application to difference logic
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Efficient satisfiability modulo theories via delayed theory combination
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
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From propositional satisfiability to satisfiability modulo theories
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Lemma learning in SMT on linear constraints
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A progressive simplifier for satisfiability modulo theories
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SDSAT: tight integration of small domain encoding and lazy approaches in a separation logic solver
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Formal verification of code motion techniques using data-flow-driven equivalence checking
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special section on verification challenges in the concurrent world
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In this paper we present a new decision procedure for the satisfiability of Linear Arithmetic Logic (LAL), i.e. boolean combinations of propositional variables and linear constraints over numerical variables. Our approach is based on the well known integration of a propositional SAT procedure with theory deciders, enhanced in the following ways. First, our procedure relies on an incremental solver for linear arithmetic, that is able to exploit the fact that it is repeatedly called to analyze sequences of increasingly large sets of constraints. Reasoning in the theory of LA interacts with the boolean top level by means of a stack-based interface, that enables the top level to add constraints, set points of backtracking, and backjump, without restarting the procedure from scratch at every call. Sets of inconsistent constraints are found and used to drive backjumping and learning at the boolean level, and theory atoms that are consequences of the current partial assignment are inferred. Second, the solver is layered: a satisfying assignment is constructed by reasoning at different levels of abstractions (logic of equality, real values, and integer solutions). Cheaper, more abstract solvers are called first, and unsatisfiability at higher levels is used to prune the search. In addition, theory reasoning is partitioned in different clusters, and tightly integrated with boolean reasoning. We demonstrate the effectiveness of our approach by means of a thorough experimental evaluation: our approach is competitive with and often superior to several state-of-the-art decision procedures.