1.
Introduction
2.
Why is Quick Sort preferred for Arrays?
3.
Why is Merge-Sort preferred for Linked Lists?
4.
4.1.
Is merge sort preferred for arrays over linked lists?
4.2.
When should I use quick sort?
4.3.
Why is quick sort usually about as fast as merge sort when is merge sort most certain to outperform quick sort?
4.4.
What is the difference between quick sort and merge sort?
4.5.
What are the disadvantages of merge sort?
5.
Conclusion
Last Updated: Mar 27, 2024

# Why is Quick Sort preferred for Arrays and Merge Sort for Linked Lists?

Mehak Goel
Data structures & algorithms (Beginner to Intermediate)
Free guided path
13 chapters
99+ problems

## Introduction

Both quicksort and mergesort algorithms are based on the divide and conquer approach. The quick sort is an internal sorting algorithm where the data is sorted in the main memory. In contrast, merge sort is an external sorting algorithm in which the data cannot be stored in the main memory and thus requires an  Auxiliary memory for Sorting the algorithm.

In quick sort, the arrays are divided into any ratio as there is no compulsion to divide them into equal parts. Whereas in merge sort, the array is divided into two halves only.

Merge sort is more stable than quick sort, as two elements having equal values appear in the same order in the sorted output as they were in the unsorted input. Quick sort becomes unstable for this scenario. But we can make it stable by making some changes in the code.

The worst-case complexity of quick sort is O(n^2), as there is a need for many comparisons in the worst condition. In merge sort, worst and average cases have the same complexities O(n*log n).

## Why is Quick Sort preferred for Arrays?

No other sorting algorithm performs better than Quick sort on Arrays because of the following reasons:

• Quick sort is an in-place sorting algorithm, i.e. which means it does not require any additional space, whereas Merge sort does, which can be rather costly. In merge sort, the allocation and deallocation of the excess space increase the execution time of the algorithm.

• The locality of reference is one of the critical reasons for quick sort’s efficiency. It allows the computer system to access memory locations close to each other, which is faster than memory locations distributed throughout the memory, as in the case of merge sort.

• Quick sort is most commonly implemented using a randomized version with anticipated time complexity of O(NlogN). Although the worst case is possible in the randomized version, it does not occur for a specific pattern (such as a sorted array). Hence the randomized quick sort works well in practice.

Recommended Topic, Floyds Algorithm

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## Why is Merge-Sort preferred for Linked Lists?

No other sorting algorithm performs better than Merge Sort on Linked Lists because of the following reasons:

• If we have to access an ith index in a linked list using quicksort, we will have to travel every node from the head node to the ith node as we do not have a contiguous memory block. As a result, the cost of quicksort rises. Whereas merge sort sequentially accesses data, therefore the need for random access is low.

• It might happen that the nodes in linked lists may not be present in nearby memory locations, therefore Merge Sort is preferred.

• Unlike arrays, in linked lists, we can insert elements in the middle in O(1) extra space and O(1) time complexities if we are given a reference/pointer to the previous node. As a result, we can implement the merge operation in the merge sort without using any additional space.

• Merge sort is preferred when stable sorting is needed. Stable Sorting means the order of elements with the same value remains the same after the elements have been sorted. This is significant as elements will have auxiliary data that is additional data associated with the element. Quick Sort is an unstable sorting algorithm, whereas Merge Sort is a stable method. Although Quick Sort can be adjusted to become a stable sorting algorithm, such modifications are inefficient and should not be employed.

You can also read Difference Between Array List and Linked List here.

### Is merge sort preferred for arrays over linked lists?

Merge sort is preferred for linked lists over arrays. In the case of a linked list, the insert operation takes only O(1) time and space complexity which implies that we can implement the merge operation in constant time.

### When should I use quick sort?

The sorting algorithm is used for information searching, and as Quicksort is the fastest algorithm, so it is widely used as a better way of searching. It is used everywhere where a stable sort is not needed. Quicksort is a cache-friendly algorithm as it has a good locality of reference when used for arrays.

### Why is quick sort usually about as fast as merge sort when is merge sort most certain to outperform quick sort?

The quick sort is faster than merge sort in many cases because of reduced overhead but because of how quicksort accesses data, which is a lot more cache-friendly than standard mergesort.

### What is the difference between quick sort and merge sort?

The major difference between quicksort and merge sort is that the merge sort sorts the array by dividing it into two subarrays again and again until a single element is left. In contrast, quicksort sorts them by comparing each element with an element called a pivot.

### What are the disadvantages of merge sort?

Disadvantages of using the merge sort algorithm are:
Requires extra space to store subarrays.
Slow for small arrays.
The algorithm does the whole process even if the array is already sorted.

## Conclusion

The blog discussed the main reasons behind using quick sort for arrays and merge sort for linked lists. We hope you have understood them in detail.

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To learn more about arrays and linked lists, check out our articles on them. You can also practice these Data Structures using our free guided path.

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