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Article: Comparing different sorting algorithms

Description

In this article, we will compare different sorting algorithms. A table will be used to present the results. All the algorithms were implemented in Java.

List of contents

Table of results

Algorithm Best case Average case Worst case Space complexity Stable Comparisons Swaps Time (ms)
Bubble sort O(n) O(n^2) O(n^2) O(1) Yes 0.000000 0.000000 0.000000
Insertion sort O(n) O(n^2) O(n^2) O(1) Yes 0.000000 0.000000 0.000000
Selection sort O(n^2) O(n^2) O(n^2) O(1) No 0.000000 0.000000 0.000000
Merge sort O(n log(n)) O(n log(n)) O(n log(n)) O(n) Yes 0.000000 0.000000 0.000000
Quick sort O(n log(n)) O(n log(n)) O(n^2) O(log(n)) No 0.000000 0.000000 0.000000
Heap sort O(n log(n)) O(n log(n)) O(n log(n)) O(1) No 0.000000 0.000000 0.000000
Counting sort O(n + k) O(n + k) O(n + k) O(n + k) Yes 0.000000 0.000000 0.000000

Important notes

  • The table will be updated as new algorithms are added.

  • Stable: When two or more elements have the same value, the algorithm does not change the order of the elements.

  • Comparisons: Refers to the total of comparisons made by the algorithm to sort the array.

  • Swaps: Refers to the total of swaps made by the algorithm to sort the array.

  • Time: Refers to the total time taken by the algorithm to sort the array.

  • All the algorithms were tested with the same array of ten thousand elements. The array was generated with random numbers. The tests were performed on a computer with the following specifications:

    System Model: Nitro AN515-54 || Processor: Intel(R) Core(TM) i5-9300H CPU @ 2.40GHz, 2400 Mhz, 4 Core(s), 8 Logical Processor(s) || OS Name: Microsoft Windows 11 Home Single Language || Available Physical Memory: 7,93 GB

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