Enhancement of Rabin-Karp Algorithmusing XOR Filter

Purpose–Thestudy aims to enhance the Rabin-Karp Algorithm that underlinesthe problem encountered wherein the algorithm’s runtimeperformanceis affected due tothe continuous rapid growth of data. Method–Application of XOR Filter in the enhancement of the Rabin-Karp Algorithm is constructed to the given patterns to check for any pattern absences that will be removed from the data input. Then the updated patterns will be utilized in the string-matching process. Results–The modified method displayed significant improvements in different input data sizes and patterns. After conducting runtime tests, it surpasses the improved algorithm using Bloom Filter by 9%, and a rate of 47.53% runtime performance compared to the traditional Rabin-Karp Algorithm. Conclusion–The integration of the XOR Filter into the Rabin-Karp Algorithm, demonstrates a statistically significant runtime improvement. Moreover, itshows an effective scalability with larger datasets, proving its practical suitability for applications or scenarios that handleextensive datasets. Recommendations–Future researchers are encouragedto exploreother alternative t