In this paper, we describe a new method for constructing minimal, deterministic, acyclic finitestate automata from a set of strings. Traditional methods consist of two phases: the first to construct a trie, the second one to minimize it. Our approach is to construct a minimal automaton in a single phase by adding new strings one by one and minimizing the resulting automaton on-thefly. We present a general algorithm as well as a specialization that relies upon the lexicographical ordering of the input strings. Our method is fast and significantly lowers memory requirements in comparison to other methods.
In this paper, we present a new Deterministic Finite Automata (DFA) minimization algorithm. The algorithm is incremental -it may be halted at any time, yielding a partially-minimized automaton. All of the other (known) minimization algorithms have intermediate results which are not useable for partial minimization. Since the first algorithm is easily understood but inefficient, we consider three practical and effective optimizations. The first two optimizations do not affect the asymptotic worst-case running time -though they perform well on a large class of automata. The third optimization yields an quadratic-time algorithm which is competitive with the previously known ones.
Abstract. This paper is a follow-up to Jan Daciuk's experiments on space-efficient finite state automata representation that can be used directly for traversals in main memory [4]. We investigate several techniques of reducing the memory footprint of minimal automata, mainly exploiting the fact that transition labels and transition pointer offset values are not evenly distributed and so are suitable for compression. We achieve a size gain of around 20-30% compared to the original representation given in [4]. This result is comparable to the state-of-the-art dictionary compression techniques like the LZ-trie [10] method, but remains memory and CPU efficient during construction.
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