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The State Complexity of Lexicographically Smallest Words and Computing Successors
Given a regular language L over an ordered alphabet [Formula: see text], the set of lexicographically smallest (resp., largest) words of each length is itself regular. Moreover, there exists an unambiguous finite-state transducer that, on a given word [Formula: see text], outputs the length-lexicogr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247871/ http://dx.doi.org/10.1007/978-3-030-48516-0_7 |
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author | Fleischer, Lukas Shallit, Jeffrey |
author_facet | Fleischer, Lukas Shallit, Jeffrey |
author_sort | Fleischer, Lukas |
collection | PubMed |
description | Given a regular language L over an ordered alphabet [Formula: see text], the set of lexicographically smallest (resp., largest) words of each length is itself regular. Moreover, there exists an unambiguous finite-state transducer that, on a given word [Formula: see text], outputs the length-lexicographically smallest word larger than w (henceforth called the L-successor of w). In both cases, naïve constructions result in an exponential blowup in the number of states. We prove that if L is recognized by a DFA with n states, then [Formula: see text] states are sufficient for a DFA to recognize the subset S(L) of L composed of its lexicographically smallest words. We give a matching lower bound that holds even if S(L) is represented as an NFA. We then show that the same upper and lower bounds hold for an unambiguous finite-state transducer that computes L-successors. |
format | Online Article Text |
id | pubmed-7247871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72478712020-05-26 The State Complexity of Lexicographically Smallest Words and Computing Successors Fleischer, Lukas Shallit, Jeffrey Developments in Language Theory Article Given a regular language L over an ordered alphabet [Formula: see text], the set of lexicographically smallest (resp., largest) words of each length is itself regular. Moreover, there exists an unambiguous finite-state transducer that, on a given word [Formula: see text], outputs the length-lexicographically smallest word larger than w (henceforth called the L-successor of w). In both cases, naïve constructions result in an exponential blowup in the number of states. We prove that if L is recognized by a DFA with n states, then [Formula: see text] states are sufficient for a DFA to recognize the subset S(L) of L composed of its lexicographically smallest words. We give a matching lower bound that holds even if S(L) is represented as an NFA. We then show that the same upper and lower bounds hold for an unambiguous finite-state transducer that computes L-successors. 2020-05-26 /pmc/articles/PMC7247871/ http://dx.doi.org/10.1007/978-3-030-48516-0_7 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Fleischer, Lukas Shallit, Jeffrey The State Complexity of Lexicographically Smallest Words and Computing Successors |
title | The State Complexity of Lexicographically Smallest Words and Computing Successors |
title_full | The State Complexity of Lexicographically Smallest Words and Computing Successors |
title_fullStr | The State Complexity of Lexicographically Smallest Words and Computing Successors |
title_full_unstemmed | The State Complexity of Lexicographically Smallest Words and Computing Successors |
title_short | The State Complexity of Lexicographically Smallest Words and Computing Successors |
title_sort | state complexity of lexicographically smallest words and computing successors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7247871/ http://dx.doi.org/10.1007/978-3-030-48516-0_7 |
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