On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection

Detalhes bibliográficos
Autor(a) principal: Bastos, R
Data de Publicação: 2016
Outros Autores: Broda, S, António Machiavelo, Nelma Moreira, Rogério Reis
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://hdl.handle.net/10216/90771
Resumo: Extended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. (c) IFIP International Federation for Information Processing 2016.
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spelling On the State Complexity of Partial Derivative Automata For Regular Expressions with IntersectionCiência de computadores, Ciências da computação e da informaçãoComputer science, Computer and information sciencesExtended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. (c) IFIP International Federation for Information Processing 2016.20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/90771eng10.1007/978-3-319-41114-9_4Bastos, RBroda, SAntónio MachiaveloNelma MoreiraRogério Reisinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-27T19:31:58Zoai:repositorio-aberto.up.pt:10216/90771Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T23:22:18.803261Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
title On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
spellingShingle On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
Bastos, R
Ciência de computadores, Ciências da computação e da informação
Computer science, Computer and information sciences
title_short On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
title_full On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
title_fullStr On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
title_full_unstemmed On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
title_sort On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
author Bastos, R
author_facet Bastos, R
Broda, S
António Machiavelo
Nelma Moreira
Rogério Reis
author_role author
author2 Broda, S
António Machiavelo
Nelma Moreira
Rogério Reis
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Bastos, R
Broda, S
António Machiavelo
Nelma Moreira
Rogério Reis
dc.subject.por.fl_str_mv Ciência de computadores, Ciências da computação e da informação
Computer science, Computer and information sciences
topic Ciência de computadores, Ciências da computação e da informação
Computer science, Computer and information sciences
description Extended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. (c) IFIP International Federation for Information Processing 2016.
publishDate 2016
dc.date.none.fl_str_mv 2016
2016-01-01T00:00:00Z
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dc.relation.none.fl_str_mv 10.1007/978-3-319-41114-9_4
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