Paper Info
Title
Practical lower and upper bounds for the Shortest Linear Superstring.
Abstract
Given a set P of words, the Shortest Linear Superstring (SLS) problem is an optimisation problem that asks for a superstring of P of minimal length. SLS has applications in data compression, where a superstring is a compact representation of P, and in bioinformatics where it models the first step of genome assembly. Unfortunately SLS is hard to solve (NP-hard) and to closely approximate (MAX-SNP-hard). If numerous polynomial time approximation algorithms have been devised, few articles report on their practical performance. We lack knowledge about how closely an approximate superstring can be from an optimal one in practice. Here, we exhibit a linear time algorithm that reports an upper and a lower bound on the length of an optimal superstring. The upper bound is the length of an approximate superstring. This algorithm can be used to evaluate beforehand whether one can get an approximate superstring whose length is close to the optimum for a given instance. Experimental results suggest that its approximation performance is orders of magnitude better than previously reported practical values. Moreover, the proposed algorithm remainso efficient even on large instances and can serve to explore in practice the approximability of SLS.
Year
Venue
Field
2018
SEA
Superstring theory,Orders of magnitude (numbers),Discrete mathematics,Text compression,Computer science,Upper and lower bounds,Oceanography,Data compression,Time complexity,Polynomial time approximation algorithm
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Bastien Cazaux1106.65
Samuel Juhel200.34
E Rivals3136.29