Technique for Mitigating Time Complexity

Abstract

Ordered data may be handled rapidly, however unstructured data may require additional time to get results. Sorting is employed for data organization. This is a fundamental requirement for most applications, and this step enhances performance. Sorting is a necessity in various computer applications, such as databases. Over time, computer scientists have produced novel sorting strategies aimed at improving certain parameters, as well as enhanced variants of current sorting methods. The primary aim has consistently been to minimize the execution time and memory usage of sorting algorithms. As digital content proliferates daily, it significantly motivates academics to develop novel time-space efficient sorting algorithms. This work delineates preprocessing options for quicksort and insertion sort to enhance their performance. The major purpose of utilizing these preprocessings is to make input data more suited for sorting algorithm, as most sorting function performs extraordinary for a specific type of input, such as insertion sort works better on nearly sorted data. The efficiency of existing sorting algorithms has been evaluated against new preprocessing procedures. The outcomes with the offered techniques surpass the results of the original sorting methods. It additionally aids in transforming the worst-case scenario into the ordinary case. This approach can lower the complexity of numerous algorithms; therefore, it is highly significant.