Comparative Analysis of five Sorting Algorithms on the basis of Best Case, Average Case, and Worst Case
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| Author | Mohsin Khan, Samina Shaheen, Furqan Aziz Qureshi |
| ISSN | 2306-708X |
| On Pages | 1-10 |
| Volume No. | 3 |
| Issue No. | 1 |
| Issue Date | ------- |
| Publishing Date | ------ |
| Keywords | Cryptograhy, Symmetric & Asymmetric |
Abstract
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, 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. All six algorithms are analyzed, implemented, tested, compared and concluded that which algorithm is best for small, average, and large data sets, with all three constraints (best case, average case, and worst case).
Key words: Bubble Sort, Selection Sort, Quick Sort, Merge Sort, Optimized Bubble Sort, Enhanced selection Sort, Complexity
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