000 04054cam a2200457Ii 4500
001 ocn909525346
003 OCoLC
005 20190328114811.0
006 m o d
007 cr cnu---unuuu
008 150520s2015 enk ob 001 0 eng d
040 _aOPELS
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019 _a910446832
_a961628022
_a968063401
_a969066512
020 _a9780081004647
_q(electronic bk.)
020 _a0081004648
_q(electronic bk.)
020 _z9781785480102
020 _z1785480103
035 _a(OCoLC)909525346
_z(OCoLC)910446832
_z(OCoLC)961628022
_z(OCoLC)968063401
_z(OCoLC)969066512
050 4 _aQA76.612
072 7 _aCOM
_x051000
_2bisacsh
082 0 4 _a005.1/16
_223
100 1 _aPelleau, Marie,
_eauthor.
245 1 0 _aAbstract domains in constraint programming /
_h[electronic resource]
_cMarie Pelleau.
264 1 _aLondon, UK :
_bISTE Press ;
_aKidlington, Oxford, UK :
_bElsevier,
_c2015.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_2rda
520 _aConstraint 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 _aOnline resource; title from PDF title page (ScienceDirect, viewed May 20, 2015).
505 0 _aFront 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 _a4.2. 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.
504 _aIncludes bibliographical references and index.
650 0 _aConstraint programming (Computer science)
650 7 _aCOMPUTERS
_xProgramming
_xGeneral.
_2bisacsh
650 7 _aConstraint programming (Computer science)
_2fast
_0(OCoLC)fst00875873
655 4 _aElectronic books.
776 0 8 _iPrint version:
_z9780081004647
_w(OCoLC)909525346
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/book/9781785480102
999 _c247087
_d247087