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Nondeterministic Streaming String Transducers

  • Rajeev Alur
  • Jyotirmoy V. Deshmukh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6756)

Abstract

We introduce nondeterministic streaming string transducers (nssts) – a new computational model that can implement MSO-definable relations between strings. An nsst makes a single left-to-right pass on the input string and uses a finite set of string variables to compute the output. In each step, it reads one input symbol, and updates its string variables in parallel with a copyless assignment. We show that nsst are closed under sequential composition and that their expressive power coincides with that of nondeterministic MSO-definable transductions. Further, we identify the class of functional nssts; such an nsst allows nondeterministic transitions, but for every successful run on a given input generates the same output string. We show that deciding functionality of an arbitrary nsst is decidable with pspace complexity, while the equivalence problem for functional nssts is pspace-complete. We also show that checking if the set of outputs of an nsst is contained within the set of outputs of a finite number of dssts is decidable in pspace.

Keywords

Expressive Power Equivalence Problem Sequential Composition Input String Input Symbol 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Rajeev Alur
    • 1
  • Jyotirmoy V. Deshmukh
    • 1
  1. 1.Dept. of Computer and Information ScienceUniversity of PennsylvaniaUSA

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