Constraint-Generating Dependencies

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 constraintgenerating 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 This work was supported by NATO Collaborative Research Grant CRG 940110 and by NSF Grant IRI-9110581. Dept. of Computer Science, Howard Hall, West Long Branch, NJ 07764, USA, Email: [email protected]. Institut Montefiore, B28, 4000 Liège Sart-Tilman, Belgium, Email: [email protected].