Document Type
Technical Report
Publication Date
7-14-1994
Technical Report Number
PCS-TR94-214
Abstract
Given a collection of strings S={s_1,...,s_n} over an alphabet Sigma, a superstring alpha of S is a string containing each s_i as a substring, that is, for each i, 1<=i<=n, alpha contains a block of |s_i| consecutive characters that match s_i exactly. The shortest superstring problem is the problem of finding a superstring alpha of minimum length. The shortest superstring problem has applications in both computational biology and data compression. The problem is NP-hard [GallantMS80]; in fact, it was recently shown to be MAX SNP-hard [BlumJLTY91]. Given the importance of the applications, several heuristics and approximation algorithms have been proposed. Constant factor approximation algorithms have been given in [BlumJLTY91] (factor of 3), [TengY93] (factor of 2-8/9), [CzumajGPR94] (factor of 2-5/6) and [KosarajuPS94] (factor of 2-50/63). Informally, the key to any algorithm for the shortest superstring problem is to identify sets of strings with large amounts of similarity, or overlap. While the previous algorithms and their analyses have grown increasingly sophisticated, they reveal remarkably little about the structure of strings with large amounts of overlap. In this sense, they are solving a more general problem than the one at hand. In this paper, we study the structure of strings with large amounts of overlap and use our understanding to give an algorithm that finds a superstring whose length is no more than 2-3/4 times that of the optimal superstring. We prove several interesting properties about short periodic strings, allowing us to answer questions of the following form: given a string with some periodic structure, characterize all the possible periodic strings that can have a large amount of overlap with the first string.
Dartmouth Digital Commons Citation
Armen, Chris and Stein, Clifford, "A 2-3/4-Approximation Algorithm for the Shortest Superstring Problem" (1994). Computer Science Technical Report PCS-TR94-214. https://digitalcommons.dartmouth.edu/cs_tr/99