Computer Science

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The Computer Science Department at Montana State University supports the Mission of the College of Engineering and the University through its teaching, research, and service activities. The Department educates undergraduate and graduate students in the principles and practices of computer science, preparing them for computing careers and for a lifetime of learning.

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    The longest letter-duplicated subsequence and related problems
    (Springer Science and Business Media LLC, 2024-07) Lai, Wenfeng; Liyanage, Adiesha; Zhu, Binhai; Zou, Peng
    Motivated by computing duplication patterns in sequences, a new problem called the longest letter-duplicated subsequence (LLDS) is proposed. Given a sequence S of length n, a letter- duplicated subsequence is a subsequence of S in the form of x d1 1 x d2 2 . . . x d k k with x i ∈ , x j = x j+1 and di ≥ 2 for all i in [k] and j in [k − 1]. A linear time algorithm for computing a longest letter-duplicated subsequence (LLDS) of S can be easily obtained. In this paper, we focus on two variants of this problem: (1) ‘all-appearance’ version, i.e., all letters in must appear in the solution, and (2) the weighted version. For the former, we obtain dichotomous results: We prove that, when each letter appears in S at least 4 times, the problem and a relaxed version on feasibility testing (FT) are both NP-hard. The reduction is from (3+, 1, 2−)- SAT, where all 3-clauses (i.e., containing 3 lals) are monotone (i.e., containing only positive literals) and all 2-clauses contain only negative literals. We then show that when each letter appears in S at most 3 times, then the problem admits an O(n) time algorithm. Finally, we consider the weighted version, where the weight of a block x di i (di ≥ 2) could be any positive function which might not grow with di . We give a non-trivial O(n2) time dynamic programming algorithm for this version, i.e., computing an LD-subsequence of S whose weight is maximized.
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