Application of a greedy heuristic to the shortest common superstring problem (SCS).
Application of a greedy heuristic to the shortest common superstring problem (SCS): Given a set of strings, find the
shortest string such that every input string is a substring of the generated string. This problem has applications in data
compression and in DNA sequencing. Since SCS is NP-hard, fast heuristics are important.
The input (stdin) will consist of the following:
a. A line with n (number of strings). n ≤ 100.
b. n lines, each including a single string with no more than 50 symbols.
Before doing other processing, your program should verify that none of the input strings is a substring of any other input
string. If this condition is violated, an error message and termination should result. There is no loss of generality in
making this assumption, but it avoids a few tedious situations.
The “standard” greedy technique is conceptually simple. Given a set of strings, determine an ordered pair of strings
X=UV and Y=VW that maximizes |V|. Next, replace X and Y with UVW. Apply this technique until one string remains.
(This algorithm has been conjectured as producing a superstring that is no more than twice as long as the SCS.)
Your program should only compute the maximum overlap for each ordered pair of strings once and, in spite of the simple
description, will not need to compute any other overlaps. Instead, you may view the problem as approximating a longest
Hamiltonian path in a weighted, directed graph: each vertex corresponds to a string and the weight on each edge (X,Y) is
the maximum overlap.
The greedy technique corresponds to concatenating paths, but only at the endpoints. Care is needed to avoid cycles.