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Computing Maximal Repeating Subsequences in a String

Mingyang Gong, Adiesha Liyanage, Braeden Sopp, Binhai Zhu

TL;DR

The study of computing a maximal (not necessarily maximum) repeating pattern in a single input string, where the corresponding problems have been studied, is initiated, greatly improving the O(n^2) bound for computing the longest square subsequence of $S$.

Abstract

In this paper we initiate the study of computing a maximal (not necessarily maximum) repeating pattern in a single input string, where the corresponding problems have been studied (e.g., a maximal common subsequence) only in two or more input strings by Hirota and Sakai starting 2019. Given an input string $S$ of length $n$, we can compute a maximal square subsequence of $S$ in $O(n\log n)$ time, greatly improving the $O(n^2)$ bound for computing the longest square subsequence of $S$. For a maximal $k$-repeating subsequence, our bound is $O(f(k)n\log n)$, where \(f(k)\) is a computable function such that $f(k) < k\cdot 4^k$. This greatly improves the $O(n^{2k-1})$ bound for computing a longest $k$-repeating subsequence of $S$, for $k\geq 3$. Both results hold for the constrained case, i.e., when the solution must contain a subsequence $X$ of $S$, though with higher running times.

Computing Maximal Repeating Subsequences in a String

TL;DR

The study of computing a maximal (not necessarily maximum) repeating pattern in a single input string, where the corresponding problems have been studied, is initiated, greatly improving the O(n^2) bound for computing the longest square subsequence of .

Abstract

In this paper we initiate the study of computing a maximal (not necessarily maximum) repeating pattern in a single input string, where the corresponding problems have been studied (e.g., a maximal common subsequence) only in two or more input strings by Hirota and Sakai starting 2019. Given an input string of length , we can compute a maximal square subsequence of in time, greatly improving the bound for computing the longest square subsequence of . For a maximal -repeating subsequence, our bound is , where \(f(k)\) is a computable function such that . This greatly improves the bound for computing a longest -repeating subsequence of , for . Both results hold for the constrained case, i.e., when the solution must contain a subsequence of , though with higher running times.
Paper Structure (13 sections, 14 theorems, 6 equations, 1 figure, 4 algorithms)

This paper contains 13 sections, 14 theorems, 6 equations, 1 figure, 4 algorithms.

Key Result

Lemma 3.1

Given any sequence $Z$, $Y$ is a subsequence of $Z$ if and only if $YY$ is a subsequence of $ZZ$.

Figures (1)

  • Figure 1: A flowchart of the algorithm.

Theorems & Definitions (24)

  • Definition 2.1
  • Example 1
  • Lemma 3.1
  • Lemma 3.2
  • Lemma 3.3
  • Lemma 3.4
  • Definition 3.1: Leftmost anchor with a position $i_t$
  • Example 2
  • Example 3
  • Lemma 3.5
  • ...and 14 more