Abstract domains in constraint programming

Constraint Programming aims at solving hard combinatorial problems, with a computation time increasing in practice exponentially. The methods are today efficient enough to solve large industrial problems, in a generic framework. However, solvers are dedicated to a single variable type: integer or re...

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Bibliographic Details
Main Author: Pelleau, Marie (Author)
Format: Book
Language:English
Published: London, UK Kidlington, Oxford, UK ISTE Press Elsevier 2015
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040 |a UPNM  |b eng  |c UPNM  |e rda 
090 |a QA 76.612  |b .P45 2015 
100 1 |a Pelleau, Marie  |e author 
245 1 0 |a Abstract domains in constraint programming  |c Marie Pelleau 
264 1 |a London, UK  |b ISTE Press  |a Kidlington, Oxford, UK  |b Elsevier  |c 2015 
300 |a xvi, 160 pages  |b illustrations  |c 24 cm 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
504 |a Includes bibliographical references and index 
505 0 |a State of the art -- Abstract interpretation for the constraints -- Octagons -- Octagonal solving -- An abstract solver: absolute 
520 |a Constraint Programming aims at solving hard combinatorial problems, with a computation time increasing in practice exponentially. The methods are today efficient enough to solve large industrial problems, in a generic framework. However, solvers are dedicated to a single variable type: integer or real. Solving mixed problems relies on ad hoc transformations. In another field, Abstract Interpretation offers tools to prove program properties, by studying an abstraction of their concrete semantics, that is, the set of possible values of the variables during an execution. Various representations for these abstractions have been proposed. They are called abstract domains. Abstract domains can mix any type of variables, and even represent relations between the variables. In this work, we define abstract domains for Constraint Programming, so as to build a generic solving method, dealing with both integer and real variables. We also study the octagons abstract domain, already defined in Abstract Interpretation. Guiding the search by the octagonal relations, we obtain good results on a continuous benchmark. We also define our solving method using Abstract Interpretation techniques, in order to include existing abstract domains. Our solver, AbSolute, is able to solve mixed problems and use relational domains. 
592 |a IN/11537  |b 11/3/16  |c RM308.51  |h Innowawasan 
650 0 |a Constraint programming (Computer science) 
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