The Swap Matching Problem Revisited

TL;DR

This paper introduces a new graph-theoretic approach and efficient algorithms for the Swap Matching problem, improving solution methods by adapting classic algorithms to achieve linear time performance for certain pattern lengths.

Contribution

The paper presents a novel graph-theoretic model and two efficient algorithms based on shift-and, specifically optimized for patterns of length similar to machine word size.

Findings

Algorithms run in linear time for specific pattern lengths

New graph-theoretic model opens unexplored solution avenues

Efficient adaptations of classic shift-and algorithms

Abstract

In this paper, we revisit the much studied problem of Pattern Matching with Swaps (Swap Matching problem, for short). We first present a graph-theoretic model, which opens a new and so far unexplored avenue to solve the problem. Then, using the model, we devise two efficient algorithms to solve the swap matching problem. The resulting algorithms are adaptations of the classic shift-and algorithm. For patterns having length similar to the word-size of the target machine, both the algorithms run in linear time considering a fixed alphabet.