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Abstract domains in constraint progr...

Pelleau, Marie,

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Abstract domains in constraint programming

Record Type:	Electronic resources : Monograph/item
Title/Author:	Abstract domains in constraint programming/ Marie Pelleau.
Author:	Pelleau, Marie,
Published:	London, UK :ISTE Press ; : 2015.,
Description:	1 online resource.
[NT 15003449]:	Front Cover; Abstract Domains in Constraint Programming; Dedication; Copyright; Contents; Preface; Introduction; I.1. Context; I.2. Problematic; I.3. Outline of the book; I.4. Contributions; Chapter 1: State of the Art; 1.1. Abstract Interpretation; 1.2. Constraint Programming; 1.3. Synthesis; Chapter 2: Abstract Interpretation for the Constraints; 2.1. Introduction; 2.2. Unified Components; 2.3. Unified Solving; 2.4. Conclusion; Chapter 3: Octagons; 3.1. Definitions; 3.2. Representations; 3.3. Abstract Domain Components; 3.4. Abstract Domains; Chapter 4: Octagonal Solving; 4.1. Octagonal CSP.
[NT 15003449]:	4.2. Octagonal Consistency and Propagation4.3. Octagonal Solver; 4.4. Experimental Results; 4.5. Conclusion; Chapter 5: An Abstract Solver: AbSolute; 5.1. Abstract Solving Method; 5.2. The AbSolute Solver; 5.3. Conclusion; Conclusion and Perspectives; C.1. Conclusion; C.2. Perspectives; Bibliography; Index.
Subject:	Constraint programming (Computer science) -
Online resource:	https://www.sciencedirect.com/science/book/9781785480102
ISBN:	9780081004647 (electronic bk.)

Abstract domains in constraint programming
Pelleau, Marie,

Abstract domains in constraint programming[electronic resource] /Marie Pelleau. - London, UK :ISTE Press ;2015. - 1 online resource.

Includes bibliographical references and index.

Front Cover; Abstract Domains in Constraint Programming; Dedication; Copyright; Contents; Preface; Introduction; I.1. Context; I.2. Problematic; I.3. Outline of the book; I.4. Contributions; Chapter 1: State of the Art; 1.1. Abstract Interpretation; 1.2. Constraint Programming; 1.3. Synthesis; Chapter 2: Abstract Interpretation for the Constraints; 2.1. Introduction; 2.2. Unified Components; 2.3. Unified Solving; 2.4. Conclusion; Chapter 3: Octagons; 3.1. Definitions; 3.2. Representations; 3.3. Abstract Domain Components; 3.4. Abstract Domains; Chapter 4: Octagonal Solving; 4.1. Octagonal CSP.

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.

ISBN: 9780081004647 (electronic bk.)Subjects--Topical Terms:

672805
Constraint programming (Computer science)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA76.612

Dewey Class. No.: 005.1/16

Abstract domains in constraint programming
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245 1 0 $a Abstract domains in constraint programming $h [electronic resource] / $c Marie Pelleau.
260 $a London, UK : $b ISTE Press ; $a Kidlington, Oxford, UK : $b Elsevier, $c 2015.
300 $a 1 online resource.
504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Abstract Domains in Constraint Programming; Dedication; Copyright; Contents; Preface; Introduction; I.1. Context; I.2. Problematic; I.3. Outline of the book; I.4. Contributions; Chapter 1: State of the Art; 1.1. Abstract Interpretation; 1.2. Constraint Programming; 1.3. Synthesis; Chapter 2: Abstract Interpretation for the Constraints; 2.1. Introduction; 2.2. Unified Components; 2.3. Unified Solving; 2.4. Conclusion; Chapter 3: Octagons; 3.1. Definitions; 3.2. Representations; 3.3. Abstract Domain Components; 3.4. Abstract Domains; Chapter 4: Octagonal Solving; 4.1. Octagonal CSP.
505 8 $a 4.2. Octagonal Consistency and Propagation4.3. Octagonal Solver; 4.4. Experimental Results; 4.5. Conclusion; Chapter 5: An Abstract Solver: AbSolute; 5.1. Abstract Solving Method; 5.2. The AbSolute Solver; 5.3. Conclusion; Conclusion and Perspectives; C.1. Conclusion; C.2. Perspectives; Bibliography; Index.
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.
588 0 $a Online resource; title from PDF title page (ScienceDirect, viewed May 20, 2015).
650 0 $a Constraint programming (Computer science) $3 672805
655 4 $a Electronic books. $2 lcsh $3 542853
856 4 0 $u https://www.sciencedirect.com/science/book/9781785480102