The complexity of languages generated by attribute grammars
SIAM Journal on Computing
Attribute grammars: definitions, systems and bibliography
Attribute grammars: definitions, systems and bibliography
Deforestation: transforming programs to eliminate trees
Proceedings of the Second European Symposium on Programming
Science of Computer Programming
Decidability of the finiteness of ranges of tree transductions
Information and Computation
Macro tree transducers, attribute grammars, and MSO definable tree translations
Information and Computation
Typechecking for XML transformers
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A Web Odyssey: from Codd to XML
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Syntax-Directed Semantics: Formal Models Based on Tree Transducers
Syntax-Directed Semantics: Formal Models Based on Tree Transducers
Output string languages of compositions of deterministic macro tree transducers
Journal of Computer and System Sciences
Benefits of Tree Transducers for Optimizing Functional Programs
Proceedings of the 18th Conference on Foundations of Software Technology and Theoretical Computer Science
Information Processing Letters
Journal of Computer and System Sciences
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Macro tree transducers can simulate most models of tree transducers (e.g., top-down and bottom-up tree transducers, attribute grammars, and pebble tree transducers which, in turn, can simulate all known models of XML transformers). The string languages generated by compositions of macro tree transducers (obtained by reading the leaves of the output trees) form a large class which contains, e.g., the IO hierarchy and the EDT0L control hierarchy. Consider an arbitrary composition 驴 of (deterministic) macro tree transducers. How difficult is it, for a given input tree s, to compute the translation t = 驴 (s)? It is shown that this problem can be solved (on a RAM) in time linear in the sum of the sizes of s and t. Moreover, the problem to determine, for a given t of size n, whether or not there is an input tree s such that t = 驴 (s) is in DSPACE(n); this means that output languages of compositions of macro tree transducers are deterministic context-sensitive. The involved technique of compressing intermediate results of the composition, also gives a new proof of the fact that the finiteness problem for 驴's range is decidable.