Typechecking for XML transformers
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
POPL '03 Proceedings of the 30th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
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ACM Transactions on Internet Technology (TOIT)
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ACM Transactions on Internet Technology (TOIT)
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
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Journal of Functional Programming
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VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Proceedings of the 13th ACM SIGPLAN international conference on Functional programming
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CIAA '08 Proceedings of the 13th international conference on Implementation and Applications of Automata
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Proceedings of the 12th International Conference on Database Theory
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ESOP'08/ETAPS'08 Proceedings of the Theory and practice of software, 17th European conference on Programming languages and systems
Exact XML type checking in polynomial time
ICDT'07 Proceedings of the 11th international conference on Database Theory
Mechanizing the metatheory of mini-XQuery
CPP'11 Proceedings of the First international conference on Certified Programs and Proofs
Almost-linear inclusion for XML regular expression types
ACM Transactions on Database Systems (TODS)
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A key feature of XQuery is its type system. Any language expression is statically typed and its type is used during program type-checking. In XQuery, types of input data and functions are defined in terms of regular expression types, but it is quite easy to write queries that generate non-regular languages. As a consequence, any type system for XQuery has to rely on a type inference process that approximates the (possibly non-regular) output type of a query with a regular type. This approximation process, while mandatory and unavoidable, may significantly decrease the precision of the inferred types. In this paper we will analyze the precision and the complexity of the W3C type inference algorithm. By defining an abstract model for the core of XQuery and for its type language (miniXQuery), we will identify the critical issues in the inference process and the sources of precision loss. We will also propose an alternative type inference system, used in the microXQ+ language, and show that in most cases it is more precise without any performance penalties. Finally, we will identify relevant classes of input types for which inference precision can be dramatically improved.