Average complexity of Moore's and Hopcroft's algorithms

In this paper we prove that for the uniform distribution on complete deterministic automata, the average time complexity of Moore's state minimization algorithm is O(nloglogn), where n is the number of states in the input automata and the number of letters in the alphabet is fixed. Then, an unusual family of implementations of Hopcroft's algorithm is characterized, for which the algorithm will be proved to be always faster than Moore's algorithm. Finally, we present experimental results on the usual implementations of Hopcroft's algorithm.

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