DFA minimization: Double reversal versus split minimization algorithms

Garcia, Pedro Castillo; López, Damián; Parga, Manuel Vázquez de

doi:10.1016/j.tcs.2015.04.002

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…A taxonomy of the most important finite state minimization algorithms and a presentation of the known algorithms solving this problem, including some new ones, can be found in [34]. In [35], the authors show the relationship between the two most widely used approaches for the minimization of deterministic finite automata: minimization by splitting partitions and minimization by double reversal.…”

Section: Related Workmentioning

confidence: 99%

MergedTrie: Efficient textual indexing

Ferrández

Peral

2019

PLoS ONE

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The accessing and processing of textual information (i.e. the storing and querying of a set of strings) is especially important for many current applications (e.g. information retrieval and social networks), especially when working in the fields of Big Data or IoT, which require the handling of very large string dictionaries. Typical data structures for textual indexing are Hash Tables and some variants of Tries such as the Double Trie (DT). In this paper, we propose an extension of the DT that we have called MergedTrie . It improves the DT compression by merging both Tries into a single and by segmenting the indexed term into two fixed length parts in order to balance the new Trie. Thus, a higher overlapping of both prefixes and suffixes is obtained. Moreover, we propose a new implementation of Tries that achieves better compression rates than the Double-Array representation usually chosen for implementing Tries. Our proposal also overcomes the limitation of static implementations that does not allow insertions and updates in their compact representations. Finally, our MergedTrie implementation experimentally improves the efficiency of the Hash Tables, the DTs, the Double-Array, the Crit-bit, the Directed Acyclic Word Graphs (DAWG), and the Acyclic Deterministic Finite Automata (ADFA) data structures, requiring less space than the original text to be indexed.

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Section: Related Workmentioning

confidence: 99%

MergedTrie: Efficient textual indexing

Ferrández

Peral

2019

PLoS ONE

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Coalgebraic Minimization of Automata by Initiality and Finality

Rot

2016

Electronic Notes in Theoretical Computer Science

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International audienceDeterministic automata can be minimized by partition refinement (Moore's algorithm, Hopcroft's algorithm) or by reversal and determinization (Brzozowski's algorithm). In the coalgebraic perspective, the first approach can be phrased in terms of a minimization construction along the final sequence of a functor, whereas a crucial part of the second approach is based on a reachability construction along the initial sequence of another functor. We employ this coalgebraic perspective to establish a precise relationship between the two approaches to minimization, and show how they can be combined. Part of these results are extended to an approach for language equivalence of a general class of systems with branching, such as non-deterministic automata

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DFA minimization: Double reversal versus split minimization algorithms

Cited by 2 publications

References 7 publications

MergedTrie: Efficient textual indexing

MergedTrie: Efficient textual indexing

Coalgebraic Minimization of Automata by Initiality and Finality

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