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Discrete Mathematics & Theoretical Computer Science
Article . 2013 . Peer-reviewed
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Derivatives of approximate regular expressions

Authors: Champarnaud, Jean-Marc; Jeanne, Hadrien; Mignot, Ludovic;

Derivatives of approximate regular expressions

Abstract

Automata, Logic and Semantics Our aim is to construct a finite automaton recognizing the set of words that are at a bounded distance from some word of a given regular language. We define new regular operators, the similarity operators, based on a generalization of the notion of distance and we introduce the family of regular expressions extended to similarity operators, that we call AREs (Approximate Regular Expressions). We set formulae to compute the Brzozowski derivatives and the Antimirov derivatives of an ARE, which allows us to give a solution to the ARE membership problem and to provide the construction of two recognizers for the language denoted by an ARE. As far as we know, the family of approximative regular expressions is introduced for the first time in this paper. Classical approximate regular expression matching algorithms are approximate matching algorithms on regular expressions. Our approach is rather to process an exact matching on approximate regular expressions.

Country
France
Keywords

FOS: Computer and information sciences, [INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM], Formal Languages and Automata Theory (cs.FL), [INFO]Computer Science [cs], Computer Science - Formal Languages and Automata Theory, [INFO] Computer Science [cs], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Published in a Diamond OA journal