Property testing and its connection to learning and approximation
Journal of the ACM (JACM)
Robust Characterizations of Polynomials withApplications to Program Testing
SIAM Journal on Computing
Typechecking Top-Down Uniform Unranked Tree Transducers
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Data Exchange: Semantics and Query Answering
ICDT '03 Proceedings of the 9th International Conference on Database Theory
On the Resemblance and Containment of Documents
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Approximate Satisfiability and Equivalence
LICS '06 Proceedings of the 21st Annual IEEE Symposium on Logic in Computer Science
ICDT'07 Proceedings of the 11th international conference on Database Theory
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We consider documents as words and trees on some alphabet Σ and study how to compare them with some regular schemas on an alphabet Σ驴. Given an input document I, we decide if it may be transformed into a document J which is 驴-close to some target schema T: we show that this approximate decision problem can be efficiently solved. In the simple case where the transformation is the identity, we describe an approximate algorithm which decides if I is close to a target regular schema (DTD). This property is testable, i.e. can be solved in time independent of the size of the input document, by just sampling I. In the general case, the Structural Consistency decides if there is a transducer $\mathcal {T}$ with at most m states such that I is 驴-close to I驴 and his image $\mathcal {T}(I')$ is both close to T and of size comparable to the size of I. We show that Structural Consistency is also testable, i.e. can be solved by sampling I.