Constraint-generating dependencies

  • Marianne Baudinet
  • Jan Chomicki
  • Pierre Wolper
Contributed Papers Constraints and Dependencies
Part of the Lecture Notes in Computer Science book series (LNCS, volume 893)

Abstract

Traditionally, dependency theory has been developed for uninterpreted data. Specifically, the only assumption that is made about the data domains is that data values can be compared for equality. However, data is often interpreted and there can be advantages in considering it as such, for instance obtaining more compact representations as done in constraint databases. This paper considers dependency theory in the context of interpreted data. Specifically, it studies constraint-generating dependencies. These are a generalization of equality-generating dependencies where equality requirements are replaced by constraints on an interpreted domain. The main technical results in the paper are a general decision procedure for the implication and consistency problems for constraint-generating dependencies, and complexity results for specific classes of such dependencies over given domains. The decision procedure proceeds by reducing the dependency problem to a decision problem for the constraint theory of interest, and is applicable as soon as the underlying constraint theory is decidable. The complexity results are, in some cases, directly lifted from the constraint theory; in other cases, optimal complexity bounds are obtained by taking into account the specific form of the constraint decision problem obtained by reducing the dependency implication problem.

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Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Marianne Baudinet
    • 1
  • Jan Chomicki
    • 2
  • Pierre Wolper
    • 3
  1. 1.InformatiqueUniversité Libre de BruxellesBrusselsBelgium
  2. 2.Dept of Computing and Information SciencesKansas State UniversityManhattanUSA
  3. 3.Institut MontefioreUniversité de LiègeLiège Sart-TilmanBelgium

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