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  • 标题:Constraint Propagation and Explanation over Novel Types by Abstract Compilation
  • 本地全文:下载
  • 作者:Graeme Gange ; Peter J. Stuckey
  • 期刊名称:OASIcs : OpenAccess Series in Informatics
  • 电子版ISSN:2190-6807
  • 出版年度:2016
  • 卷号:52
  • 页码:1-14
  • DOI:10.4230/OASIcs.ICLP.2016.13
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:The appeal of constraint programming (CP) lies in compositionality - the ability to mix and match constraints as needed. However, this flexibility typically does not extend to the types of variables. Solvers usually support only a small set of pre-defined variable types, and extending this is not typically a simple exercise: not only must the solver engine be updated, but then the library of supported constraints must be re-implemented to support the new type. In this paper, we attempt to ease this second step. We describe a system for automatically deriving a native-code implementation of a global constraint (over novel variable types) from a declarative specification, complete with the ability to explain its propagation, a requirement if we want to make use of modern lazy clause generation CP solvers. We demonstrate this approach by adding support for wrapped-integer variables to chuffed, a lazy clause generation CP solver.
  • 关键词:constraint programming; program synthesis; program analysis
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