335 research outputs found

    SMT Solving Modulo Tableau and Rewriting Theories

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    International audienceWe propose an automated theorem prover that combines an SMT solver with tableau calculus and rewriting. Tableau inference rules are used to unfold propositional content into clauses while atomic formulas are handled using satisfiability decision procedures as in traditional SMT solvers. To deal with quantified first order formulas, we use metavariables and perform rigid unification modulo equalities and rewriting, for which we introduce an algorithm based on superposition, but where all clauses contain a single atomic formula. Rewriting is introduced along the lines of deduction modulo theory, where axioms are turned into rewrite rules over both terms and propositions. Finally, we assess our approach over a benchmark of problems in the set theory of the B method

    05431 Abstracts Collection -- Deduction and Applications

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    From 23.10.05 to 28.10.05, the Dagstuhl Seminar 05431 ``Deduction and Applications\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    The hyper Tableaux calculus with equality and an application to finite model computation

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    In most theorem proving applications, a proper treatment of equational theories or equality is mandatory. In this article we show how to integrate a modern treatment of equality in the hyper tableau calculus. It is based on splitting of positive clauses and an adapted version of the superposition inference rule, where equations used for superposition are drawn (only) from a set of positive unit clauses, and superposition inferences into positive literals is restricted into (positive) unit clauses only. The calculus also features a generic, semantically justified simplification rule which covers many redundancy elimination techniques known from superposition theorem proving. Our main results are soundness and completeness of the calculus, but we also show how to apply the calculus for finite model computation, and we briefly describe the implementation

    Proof search without backtracking for free variable tableaux [online]

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    SMT Solving Modulo Tableau and Rewriting Theories

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    International audienceWe propose an automated theorem prover that combines an SMT solver with tableau calculus and rewriting. Tableau inference rules are used to unfold propositional content into clauses while atomic formulas are handled using satisfiability decision procedures as in traditional SMT solvers. To deal with quantified first order formulas, we use metavariables and perform rigid unification modulo equalities and rewriting, for which we introduce an algorithm based on superposition, but where all clauses contain a single atomic formula. Rewriting is introduced along the lines of deduction modulo theory, where axioms are turned into rewrite rules over both terms and propositions. Finally, we assess our approach over a benchmark of problems in the set theory of the B method

    Improved verification methods for concurrent systems

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    Embodied memory Shadow and index in Family Ties by Eulalia Valldosera

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    The 4th Conference of PhD Students in Computer Science

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    Seventh Biennial Report : June 2003 - March 2005

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    Cardinality Constrained Optimization Problems

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    In this thesis, we examine optimization problems with a constraint that allows for only a certain number of variables to be nonzero. This constraint, which is called a cardinality constraint, has received considerable attention in a number of areas such as machine learning, statistics, computational finance, and operations management. Despite their practical needs, most optimization problems with a cardinality constraints are hard to solve due to their nonconvexity. We focus on constructing tight convex relaxations to such problems
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