Resumo

NXUMALO, Madoda; KOURIE, Derrick G.; CLEOPHAS, Loek  e  WATSON, Bruce W.. An assessment of algorithms for deriving failure deterministic finite automata. SACJ [online]. 2017, vol.29, n.1, pp.43-68. ISSN 2313-7835.  https://doi.org/10.18489/sacj.v29i1.456.

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.

Palavras-chave : Failure deterministic finite automata; random automata.

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