An assessment of algorithms for deriving failure deterministic finite automata

Failure deterministic finite automata (FDFAs) represent regular languages more compactly than deterministic finite automata (DFAs). Four algorithms that convert arbitrary DFAs to language-equivalent FDFAs are empirically investigated. Three are concrete variants of a previously published abstract al...

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Veröffentlicht in:South African computer journal = Suid-Afrikaanse rekenaartydskrif Jg. 29; H. 1; S. 43 - 68
Hauptverfasser: Nxumalo, Madoda, Kourie, Derrick G., Cleophas, Loek, Watson, Bruce W.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Makhanda South African Computer Society (SAICSIT) 01.07.2017
South African Institute of Computer Scientists and Information Technologists
Schlagworte:
Algorithms
Failure deterministic finite automata
Random automata
ISSN:1015-7999, 2313-7835
Online-Zugang:Volltext
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Zusammenfassung:Failure deterministic finite automata (FDFAs) represent regular languages more compactly than deterministic finite automata (DFAs). Four algorithms that convert arbitrary DFAs to language-equivalent FDFAs are empirically investigated. Three are concrete variants of a previously published abstract algorithm, the DFA-Homomorphic Algorithm (DHA). The fourth builds a maximal spanning tree from the DFA to derive what it calls a delayed input DFA. A first suite of test data consists of DFAs that recognise randomised sets of finite length keywords. Since the classical Aho-Corasick algorithm builds an optimal FDFA from such a set (and only from such a set), it provides benchmark FDFAs against which the performance of the general algorithms can be compared. A second suite of test data consists of random DFAs generated by a specially designed algorithm that also builds language-equivalent FDFAs, some of which may have non-divergent cycles. These random FDFAs provide (not necessarily tight) lower bounds for assessing the effectiveness of the four general FDFA generating algorithms.
Bibliographie:ObjectType-Article-1
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ISSN:1015-7999
2313-7835
DOI:10.18489/sacj.v29i1.456