Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

Comparative Study of Two Divide and Conquer Sorting Algorithms: Modified Quick Sort and Merge Sort

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Ibtehal Mishal, Rasha AL-Khatib, Razan Hiasat

Ibtehal Mishal, Rasha AL-Khatib and Razan Hiasat. Comparative Study of Two Divide and Conquer Sorting Algorithms: Modified Quick Sort and Merge Sort. International Journal of Computer Applications 183(31):28-33, October 2021. BibTeX

	author = {Ibtehal Mishal and Rasha AL-Khatib and Razan Hiasat},
	title = {Comparative Study of Two Divide and Conquer Sorting Algorithms: Modified Quick Sort and Merge Sort},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2021},
	volume = {183},
	number = {31},
	month = {Oct},
	year = {2021},
	issn = {0975-8887},
	pages = {28-33},
	numpages = {6},
	url = {},
	doi = {10.5120/ijca2021921702},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Divide and conquer is a well-known technique for sorting algorithms. Such include Quick sort and Merge sort sorting algorithms. These two algorithms have been extensively used for sorting. However, discovering the most efficient sorting algorithm among the two has always been a contentious problem. Most of the existing research have compared quick sort and merge sort, this study intends to compare the intelligent Quick Sort algorithm based on a dynamic pivot selection technique “modified quicksort” and the merge sort. Using machine-dependent factors such as computational and employed machine-independent internal/external sorting factors, memory usage, stability, algorithm complexity: best, average, and worst cases. This study intends to contribute to this discussion using both machine-dependent and independent factors. Results obtained revealed that in terms of computational speed using an array of small sizes, the classical Quicksort algorithm is almost fast, meanwhile, the Merge sort algorithm is faster with an array of large sizes, However, modified quicksort is the fastest available option in all sizes. Also, the best case for both merge sort and classical quick sort complexity is O(nlogn), but the modified quicksort best case is O(n) which happened when the array is already sorted while the three sorts are of O(nlogn) average case, and the worst case for classical quicksort is O(


  1. Ashima. (n.d.). G. Implementation and Application of Bubble sort in D Array" International Journal for Scientific Research.
  2. Dalhoum1, A. l. (n.d.). Enhancing QuickSort Algorithm using a Dynamic Pivot Selection Technique.
  3. Kazim. (n.d.). A. A Comparative Study of Well Known Sorting Algorithms. International Journal of Advanced Research in Computer.
  4. Kumar, A. (n.d.). Merge Sort Algorithm.
  5. Mandeep. (n.d.). Why Quicksort is better than Mergesort? Retrieved May 14, 2019, from Geeksforgeeks: http://
  6. Sorting and Efficient Searching. Lecture Note. Unpublished. 2008
  7. third international conference on computing and network communications (coconet’19) comparative study of two divide and conquer sorting algorithms: quicksort and mergesort.
  8. A Comparative Analysis of Sorting Algorithms on Integer and Character Arrays Ahmed M. Aliyu, Dr. P. B. Zirra
  9. Optimizing Complexity of Quick Sort Md. Sabir Hossain Snaholata Mondal Rahma Simin Ali Mohammad Hasan.


Computer Science, Software engineering, Sorting algorithms, Computational Mathematics