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Theoretical Computer Science
Volume 143, Issue 2, 12 June 1995, Pages 285-308
 
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doi:10.1016/0304-3975(94)00111-U    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1995 Published by Elsevier Science B.V.

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Deterministic top-down tree transducers with iterated look-ahead

Giora Slutzki and Sándor VágvölgyiCorresponding Author Contact Information, 1

Department of Computer Science, Iowa State University, Ames, IA 50011, USA

Communicated by A. Salomaa 
Available online 22 December 1999.

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Abstract

It is known that by iterating the look-ahead tree languages for deterministic top-down tree automata, more and more powerful recognizing devices are obtained. Let DR0 = DR, where DR is the class of all tree languages recognizable by deterministic top-down tree automata, and let, for n greater-or-equal, slanted 1, DRn be the class of all tree languages recognizable by deterministic top-down tree automata with DRn−1 look-ahead. Then DR0 subset ofDR1 subset of DR2 subset of…. Slutzki and Vágvölgyi (1993) showed that the composition powers of the class of all deterministic top-down tree transformations with deterministic top-down look-ahead (DTTDR) form a proper hierarchy, i.e. (DTTDR)n subset of(DTTDR)n + 1 for n greater-or-equal, slanted 0. Along the proof they studied the notion of the deterministic top-down tree transducer with DRn look-ahead (dttDRn) and showed that (DTTDR)n + 1 subset of or equal to DTTDRn (n greater-or-equal, slanted 0), where DTTDRn stands for the class of all tree transformations induced by dttDRn'S. Our aim is to show the reversed inclusion, i.e. DTTDRn subset of or equal to (DTTDR)n + 1 (n greater-or-equal, slanted 0). This implies a precise characterization DTTDRn = (DTTDR)n + 1 (n greater-or-equal, slanted 0), and implies that the classes DTTDRn (ngreater-or-equal, slanted 0) form a proper hierarchy.

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