An Efficient Hybrid Exact String Matching Algorithm to Minimize the Number of Attempts and Character Comparisons

Abstract

String matching fundamentally is a classical problem of finding occurrence(s) of a pattern string within another string or body of text. String matching problems can be traced into intrusion detection in network, detecting plagiarism, information security, pattern recognition, document matching, text mining, speech analysis, application in bioinformatics and other diversified fields. Two important factors of string matching which are also the challenges of this paper are “number of attempts” and “number of character comparisons”. With these challenges of string matching, we have proposed a hybrid algorithm which is named as MAC (Minimum number of Attempts and Character Comparisons) algorithm. We have integrated the concepts of Berry-Ravindran (BR) algorithm and index based shifting approach with our new search technique to build our MAC algorithm. We have evaluated the MAC algorithm to analyze the performance for English text alongside biological data (DNA sequence and Protein sequence). The performance of MAC algorithm has turned out to be better than Maximum-Shift (MS) algorithm and Index Based Shifting (IBS) algorithm. The performance of the MAC algorithm is proficient for exact string matching for both small and large size of pattern length comparing with some existing algorithm to solve the string matching problem.