Integrating Datalog and Constraint Solving

LP is a common formalism for the field of databases and CSP, both at the theoretical level and the implementation level in the form of Datalog and CLP. In the past, close correspondences have been made between both fields at the theoretical level. Yet correspondence at the implementation level has been much less explored. In this article we work towards relating them at the implementation level. Concretely, we show how to derive the efficient Leapfrog Triejoin execution algorithm of Datalog from a generic CP execution scheme.Comment: Proceedings of the 13th International Colloquium on Implementation of Constraint LOgic Programming Systems (CICLOPS 2013), Istanbul, Turkey, August 25, 201

Branching: the Essence of Constraint Solving

This paper focuses on the branching process for solving any constraint satisfaction problem (CSP). A parametrised schema is proposed that (with suitable instantiations of the parameters) can solve CSP's on both finite and infinite domains. The paper presents a formal specification of the schema and a statement of a number of interesting properties that, subject to certain conditions, are satisfied by any instances of the schema. It is also shown that the operational procedures of many constraint systems including cooperative systems) satisfy these conditions. Moreover, the schema is also used to solve the same CSP in different ways by means of different instantiations of its parameters.Comment: 18 pages, 2 figures, Proceedings ERCIM Workshop on Constraints (Prague, June 2001

A Multicore Tool for Constraint Solving

*** To appear in IJCAI 2015 proceedings *** In Constraint Programming (CP), a portfolio solver uses a variety of different solvers for solving a given Constraint Satisfaction / Optimization Problem. In this paper we introduce sunny-cp2: the first parallel CP portfolio solver that enables a dynamic, cooperative, and simultaneous execution of its solvers in a multicore setting. It incorporates state-of-the-art solvers, providing also a usable and configurable framework. Empirical results are very promising. sunny-cp2 can even outperform the performance of the oracle solver which always selects the best solver of the portfolio for a given problem

CTL+FO Verification as Constraint Solving

Expressing program correctness often requires relating program data throughout (different branches of) an execution. Such properties can be represented using CTL+FO, a logic that allows mixing temporal and first-order quantification. Verifying that a program satisfies a CTL+FO property is a challenging problem that requires both temporal and data reasoning. Temporal quantifiers require discovery of invariants and ranking functions, while first-order quantifiers demand instantiation techniques. In this paper, we present a constraint-based method for proving CTL+FO properties automatically. Our method makes the interplay between the temporal and first-order quantification explicit in a constraint encoding that combines recursion and existential quantification. By integrating this constraint encoding with an off-the-shelf solver we obtain an automatic verifier for CTL+FO