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Deletion Operations on Deterministic Families of Automata

  • Joey Eremondi
  • Oscar H. Ibarra
  • Ian McQuillan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9076)

Abstract

Many different deletion operations are investigated applied to languages accepted by one-way and two-way deterministic reversal-bounded multicounter machines as well as finite automata. Operations studied include the prefix, suffix, infix and outfix operations, as well as left and right quotient with languages from different families. It is often expected that language families defined from deterministic machines will not be closed under deletion operations. However, here, it is shown that one-way deterministic reversal-bounded multicounter languages are closed under right quotient with languages from many different language families; even those defined by nondeterministic machines such as the context-free languages, or languages accepted by nondeterministic pushdown machines augmented by any number of reversal-bounded counters. Also, it is shown that when starting with one-way deterministic machines with one counter that makes only one reversal, taking the left quotient with languages from many different language families, again including those defined by nondeterministic machines such as the context-free languages, yields only one-way deterministic reversal-bounded multicounter languages (by increasing the number of counters). However, if there are even just two more reversals on the counter, or a second 1-reversal-bounded counter, taking the left quotient (or even just the suffix operation) yields languages that can neither be accepted by deterministic reversal-bounded multicounter machines, nor by 2-way nondeterministic machines with one reversal-bounded counter. A number of other results with deletion operations are also shown.

Keywords

Regular Language Finite Automaton Language Family Deterministic Finite Automaton Input Tape 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Joey Eremondi
    • 1
  • Oscar H. Ibarra
    • 2
  • Ian McQuillan
    • 3
  1. 1.Department of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands
  2. 2.Department of Computer ScienceUniversity of CaliforniaSanta BarbaraUSA
  3. 3.Department of Computer ScienceUniversity of SaskatchewanSaskatoonCanada

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