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When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.STACS.2017.34
URN: urn:nbn:de:0030-drops-69997
URL: http://drops.dagstuhl.de/opus/volltexte/2017/6999/
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Gallot, Paul ; Muscholl, Anca ; Puppis, Gabriele ; Salvati, Sylvain

On the Decomposition of Finite-Valued Streaming String Transducers

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LIPIcs-STACS-2017-34.pdf (0.6 MB)


Abstract

We prove the following decomposition theorem: every 1-register streaming string transducer that associates a uniformly bounded number of outputs with each input can be effectively decomposed as a finite union of functional 1-register streaming string transducers. This theorem relies on a combinatorial result by Kortelainen concerning word equations with iterated factors. Our result implies the decidability of the equivalence problem for the considered class of transducers. This can be seen as a first step towards proving a more general decomposition theorem for streaming string transducers with multiple registers.

BibTeX - Entry

@InProceedings{gallot_et_al:LIPIcs:2017:6999,
  author =	{Paul Gallot and Anca Muscholl and Gabriele Puppis and Sylvain Salvati},
  title =	{{On the Decomposition of Finite-Valued Streaming String Transducers}},
  booktitle =	{34th Symposium on Theoretical Aspects of Computer Science (STACS 2017)},
  pages =	{34:1--34:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-028-6},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{66},
  editor =	{Heribert Vollmer and Brigitte Vallée},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/6999},
  URN =		{urn:nbn:de:0030-drops-69997},
  doi =		{10.4230/LIPIcs.STACS.2017.34},
  annote =	{Keywords: Streaming Transducers, finite valuedness, equivalence}
}

Keywords: Streaming Transducers, finite valuedness, equivalence
Seminar: 34th Symposium on Theoretical Aspects of Computer Science (STACS 2017)
Issue Date: 2017
Date of publication: 24.02.2017


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