In this paper, we introduce two efficient algorithms in practice for computing the length of a longest common subsequence of two strings, using automata technique, in sequential and parallel ways. For two input strings of lengths m and n with m ≤ n, the parallel algorithm uses k processors (k ≤ m) and costs time complexity O(n) in the worst case, where k is an upper estimate of the length of a longest common subsequence of the two strings. These results are based on the Knapsack Shaking approach proposed by P. T. Huy et al. in 2002. Experimental results show that for the alphabet of size 256, our sequential and parallel algorithms are about 65.85 and 3.41m times faster than the standard dynamic programming algorithm proposed by Wagner and Fisher in 1974, respectively
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