Comparative Analysis of Five Sorting Algorithms on the Basis of Best Case, Average Case, and Worst Case
Sorting is one of the fundamental issues in computer science. Sorting problem gain more popularity, as efficient sorting is more important to optimize other algorithms e.g. searching algorithms. A number of sorting algorithms has been proposed with different constraints e.g. number of iterations (inner loop and outer loop), complexity, and CPU consuming problem. This paper presents a comparison of different sorting algorithms (sort, optimized sort, selection sort, quick sort, and merge sort) with different data sets (small data, medium data, and large data), with best case, average case, and worst case constraint.