Time taken by QuickSort, in general, can be written as following.

T(n) = T(k) + T(n-k-1) + theta(n)

The first two terms are for two recursive calls, the last term is for the partition process. k is the number of elements which are smaller than pivot.

The time taken by QuickSort depends upon the input array and partition strategy. Following are three cases.

* Worst Case:* The worst case occurs when the partition process always picks greatest or smallest element as pivot. If we consider above partition strategy where last element is always picked as pivot, the worst case would occur when the array is already sorted in increasing or decreasing order. Following is recurrence for worst case.

T(n) = T(0) + T(n-1) + theta(n) which is equivalent to T(n) = T(n-1) + theta(n)

The solution of above recurrence is theta(n2).

* Best Case:* The best case occurs when the partition process always picks the middle element as pivot. Following is recurrence for best case.

T(n) = 2T(n/2) + theta(n)

The solution of above recurrence is theta(nLogn). It can be solved using case 2 of Master Theorem.

**Average Case:**

To do average case analysis, we need to consider all possible permutation of array and calculate time taken by every permutation which doesn’t look easy.

We can get an idea of average case by considering the case when partition puts O(n/9) elements in one set and O(9n/10) elements in other set. Following is recurrence for this case.

T(n) = T(n/9) + T(9n/10) + theta(n)

Solution of above recurrence is also O(nLogn)

Although the worst case time complexity of QuickSort is O(n2) which is more than many other sorting algorithms like Merge Sort and Heap Sort, QuickSort is faster in practice, because its inner loop can be efficiently implemented on most architectures, and in most real-world data. QuickSort can be implemented in different ways by changing the choice of pivot, so that the worst case rarely occurs for a given type of data. However, merge sort is generally considered better when data is huge and stored in external storage.

**Is QuickSort** **stable****?**

The default implementation is not stable. However any sorting algorithm can be made stable by considering indexes as comparison parameter.

**Is QuickSort** **In-place****?**

As per the broad definition of in-place algorithm it qualifies as an in-place sorting algorithm as it uses extra space only for storing recursive function calls but not for manipulating the input.

**What is 3-Way QuickSort?**

In simple QuickSort algorithm, we select an element as pivot, partition the array around pivot and recur for subarrays on left and right of pivot.

Consider an array which has many redundant elements. For example, {1, 4, 2, 4, 2, 4, 1, 2, 4, 1, 2, 2, 2, 2, 4, 1, 4, 4, 4}. If 4 is picked as pivot in Simple QuickSort, we fix only one 4 and recursively process remaining occurrences. In 3 Way QuickSort, an array arr[l…r] is divided in 3 parts:

a) arr[l…i] elements less than pivot.

b) arr[i+1…j-1] elements equal to pivot.

c) arr[j…r] elements greater than pivot.