Optimal-Hash Exact String Matching Algorithms

TL;DR

This paper introduces optimized hash-based string matching algorithms that improve speed for short patterns on large alphabets by ensuring unique hash values for pattern q-grams.

Contribution

It presents a novel approach to select minimal q-gram lengths for hashing, enhancing the efficiency of existing string matching algorithms.

Findings

Faster matching for short patterns on large alphabets.

Unique hash values for pattern q-grams improve algorithm performance.

New algorithms outperform previous HASH family methods.

Abstract

String matching is the problem of finding all the occurrences of a pattern in a text. We propose improved versions of the fast family of string matching algorithms based on hashing $q$-grams. The improvement consists of considering minimal values $q$ such that each $q$-grams of the pattern has a unique hash value. The new algorithms are fastest than algorithm of the HASH family for short patterns on large size alphabets.