Extraction and Implication of Path Constraints

Abstract

We consider semistructured data as rooted edge-labeled directed graphs, and path inclusion constraints on these graphs. In this paper, we give a new decision algorithm for the implication problem of a constraint p ≼ q by a set of constraints p i ≼ u i where p, q, and the p i ’s are regular path expressions and the u i ’s are non-empty paths, improving in this particular case, the more general algorithms of S. Abiteboul and V. Vianu, and Alechina et al. Moreover, in the case of a set of word equalities u i ≡ v i , we give a more efficient decision algorithm for the implication of a word equality u ≡ v, improving the more general algorithm of P. Buneman et al., and we prove that, in this case, the implication problem for non-deterministic models or for (complete) deterministic models are equivalent.KeywordsRegular ExpressionDecision AlgorithmRegular LanguageBoundedness PropertyPath ConstraintThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.