A sorting algorithm is one of the important parts of the data structure. Sorting is the way of arranging the group of items in a specified way. Whenever we discuss faster sorting algorithms, the QuickSort comes into play. This is one of the most popular sorting techniques as per execution time is concerned. This is comparatively a better choice for any developer or coder due to its performance. The Quick Sort works on the divide and conquers rule. That means it divides the list into two and then two lists further divided into 4 recursively and so on. In this article, we will see how the quick sort works with example code as well. Also, we will see how it is faster as compared to other various sorting algorithms. We will see the various component of this Quick Sort Algorithm.
Operations in Quick Sort
- Partitioning of a list: Division or the array list using the divide and conquer. This is the first step we can say in this sorting technique. For this, we need to a Pivot element (middle element or close to the middle element).
- Swapping Items: This is the main purpose of any sorting algorithm to come to the desire list as an output. This is a mechanism to sort replace the value from one to another. For example, A = 10; B = 20; If someone asks to swap then the value of A will be 20 and the B will be 10.
- Recursive Operation: This plays a great role in Quick Sort. Doing things, again and again, is not that possible and reliable without having the recursive function. This is something a function call itself (same function) to get the job done. This plays a great role where we perform any task again and again with the same approach and in the same context.
Comparison of Sorting Algorithm
|Sorting Algorithm||Time Complexity|
|Best Case||Average Case||Worst Case|
|Merge Sort||Ω(N log N)||Θ(N log N)||O(N log N)|
|Heap Sort||Ω(N log N)||Θ(N log N)||O(N log N)|
|Quick Sort||Ω(N log N)||Θ(N log N)||O(N2)|
As we can see in the list the QUICK sort is faster than the Bubble Sort, Selection Sort, Insertion Sort comparatively.
Step 1: To get the Pivot element – In any Divide and Conquer the selecting right Pivot plays a vital role. So, usually, we try to get the middle element of the array as a Pivot element. This is the element from where we divide the single array into the peace of two to process the sorting.
Step 2: Start left pointers as a first element of the input array.
Step 3: Start right pointers as a last element of the input array.
Step 4: Now, we compare elements at the left pointer with the selected pivot element and we swap the value if required as per the business requirements. Then we compare the right pointer with the Pivot element.
Step 5: Move both to their next. All of the above steps follow again and again using a recursive approach.