Heap Sort in C++
What is heap sort in C++?
Heap Sort in C++ – A heap is a complete binary tree which is represented using array or sequential representation. It is one of the efficient algorithm for sorting given data in logical order.
In this sorting algorithm a tree structure called heap is used where a heap is a type of binary tree. An ordered balanced binary tree is called a Min-heap, where the value at the root of any subtree is less than or equal to the value of either of its children. An ordered balanced binary tree is called a max heap where the value at the root of any subtree is more than or equal to the value of either of its children. In this article, we will learn more about heap sort in C++

What is heap sort in C++?
A heap is a complete binary tree which is represented using array or sequential representation. It is one of the efficient algorithm for sorting given data in logical order.
In this sorting algorithm a tree structure called heap is used where a heap is a type of binary tree. An ordered balanced binary tree is called a Min-heap, where the value at the root of any subtree is less than or equal to the value of either of its children. An ordered balanced binary tree is called a max heap where the value at the root of any subtree is more than or equal to the value of either of its children. In this article, we will learn more about heap sort in C++
Working of heap sort in C++
To sort any list into a logical order following steps are followed :-
- Convert the list into heap.
- Now convert this heap into max heap.
- As the heap is converted to max heap largest element in the list is stored in the root of the heap, replace it with the last item of the heap.
- Now delete this node and reduce the size of heap by 1.
- Follow these steps until the list is sorted.
How to convert given list into heap ?
Let say, the index of any element in the list is i, the element in the index 2i+1 will become the left child and element in 2i+2 index will become the right child. And we want to find out the parent of any element then we can find it by finding the lower bound which is given by (i-1)/2 .


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Algorithm for heap sort in C++
MAX-HEAPIFY(A,i)
1- i<-left[i]
2- r<-right[i]
3- if l<heap-size[A]and A[l]>A[i]
4- then largest<-1
5- else largest<-i
6- if r<heap-size[A] and A[r]>A[largest]
7- then largest<-r
8- if largest!=i
9- then exchange A[i]<->A[largest]
10- MAX-HEAPIFY[A,largest]
HEAP-SORT(A)
1- BUILD-MAX-HEAP(A)
2- for i<-length[A] down to 2
3- do exchange A[1]<-> heap-size[A]-1
4- heap-size[A]<-heap-size[A]-1
5- MAX-HEAPIFY(A,1)
BUILD-MAX-HEAP(A)
1- heap-size[A]<-length[A]
2- for i<-(length[A]/2) down to 1 do
3- MAX-HEAPIFY(A,i)
Program for heap sort in C++
#include<iostream> using namespace std; void heapify(int arr[], int n, int i) { int largest = i; int l = 2*i + 1; int r = 2*i + 2; //If left child is larger than root if (l < n && arr[l] > arr[largest]) largest = l; //If right child largest if (r < n && arr[r] > arr[largest]) largest = r; //If root is nor largest if (largest != i) { swap(arr[i], arr[largest]); //Recursively heapifying the sub-tree heapify(arr, n, largest); } } void heapSort(int arr[], int n) { for (int i = n / 2 - 1; i >= 0; i--) heapify(arr, n, i); //One by one extract an element from heap for (int i=n-1; i>=0; i--) { //Moving current root to end swap(arr[0], arr[i]); //Calling max heapify on the reduced heap heapify(arr, i, 0); } } //Function to print array void display(int arr[], int n) { for (int i = 0; i < n; i++) { cout << arr[i] << "\t"; } cout << "\n"; } int main() { int arr[] = {1, 14, 3, 7, 0}; int n = sizeof(arr)/sizeof(arr[0]); cout << "Unsorted array \n"; display(arr, n); heapSort(arr, n); cout << "Sorted array \n"; display(arr, n); }
Output: Unsorted array 1 14 3 7 0 Sorted array 0 1 3 7 14
Time and Space Complexity for Heap Sort in C++
Time Complexity of Heap Sort
Heap Sort works by first building a max heap from the input, then repeatedly removing the largest element and placing it at the end of the array.
Let n be the number of elements.
- Best Case: O(n log n)
Even if the array is already sorted, Heap Sort still builds a heap and sorts all elements. - Average Case: O(n log n)
On average, it takes log n time to adjust the heap for each of the n elements. - Worst Case: O(n log n)
Even in the worst case, Heap Sort performs log n operations for each element.
Space Complexity of Heap Sort
Heap Sort is an in-place algorithm, which means it does not use extra space for sorting (other than a few variables).
- Space Complexity: O(1)
It sorts the array using constant extra space.

Quiz Time

Question 1.Which of the following sorting algorithms in its typical implementation gives best performance when applied on a sorted array?
- Quick Sort
- Heap Sort
- Insertion Sort
- Merge

Question 2. What is the time complexity of Build Heap operation. Which is used to create a max(or min) binary heap from a given array.?
- O(n)
- O(log n)
- O(nlog n)
- None of the above
BUILD-HEAP(A)
heapsize := size(A);
for i := floor(heapsize/2) downto 1
do HEAPIFY(A, i);
end for
END
Although the worst case complexity looks like O(nLogn), upper bound of time complexity is O(n).
Ans: A

Quiz Time
Question 1.Which of the following sorting algorithms in its typical implementation gives best performance when applied on a sorted array?
- Quick Sort
- Heap Sort
- Insertion Sort
- Merge
Question 2. What is the time complexity of Build Heap operation. Which is used to create a max(or min) binary heap from a given array.?
- O(n)
- O(log n)
- O(nlog n)
- None of the above
BUILD-HEAP(A)
heapsize := size(A);
for i := floor(heapsize/2) downto 1
do HEAPIFY(A, i);
end for
END
Although the worst case complexity looks like O(nLogn), upper bound of time complexity is O(n).
Ans: A
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Heap Sort Program in C
Heap Sort in C
A heap is a complete binary tree which is represented using array or sequential representation.
It is a special balanced binary tree data structure where root node is compared with its children and arranged accordingly.Normally in max heap parent node is always has a value greater then child node.
The worst and Average complexity of heap sort is O(n log2 n).
- From the given array, build the initial max heap.
- Interchange the root element with the last element.
- Use repetitive downward operation from root node to rebuild the heap of size one less than the starting.

Algorithm of Heap Sort
MAX-HEAPIFY(A,i)
1- i<-left[i]
2- r<-right[i]
3- if l<heap-size[A]and A[l]>A[i]
4- then largest<-1
5- else largest<-i
6- if r<heap-size[A] and A[r]>A[largest]
7- then largest<-r
8- if largest!=i
9- then exchange A[i]<->A[largest]
10- MAX-HEAPIFY[A,largest]
HEAP-SORT(A)
1- BUILD-MAX-HEAP(A)
2- for i<-length[A] down to 2
3- do exchange A[1]<-> heap-size[A]-1
4- heap-size[A]<-heap-size[A]-1
5- MAX-HEAPIFY(A,1)
BUILD-MAX-HEAP(A)
1- heap-size[A]<-length[A]
2- for i<-(length[A]/2) down to 1 do
3- MAX-HEAPIFY(A,i)
Implementation of Heap Sort
As we know that heap sort is based on the tree structure.
so we will take an example of heap sort with the based on tree.
Originally the given array is :[6,14,3,25,2,10,20,7,6]
First we call Build-max heap
heap size[A]=9
so,i=4 to 1, call MAX HEAPIFY (A,i)
i.e., first we call MAX HEAPIFY (A,4)
A[l]=7, A[i]=A[4] = 25,A[r] = 6
l<- left[4] = 8
r<-right[4] = 9
8<9 and 7>25 (false)
Then,largest <-4
9<9 and 6>25(false)
Then,largest = 4
A[i]<-> A[4]
Now call MAX HEAPIFY (A,2)


the A[length] =9
So, i=A/2 = 9/2 =4
i=4
since the parent node is greater than its child node.
If it is parent node is greater than child node then the parent node replace with the lesser child node.
similarly for i=3,2,1 we get the following heap tree.


Now call MAX HEAPIFY
Now we will replace the root node to last child In this photo is shown by replace 25 to 6.
Now call MAX HEAPIFY
Now we will replace the root node to last child In this photo is shown by replace 20 to 6.

Again call MAX HEAPIFY,
we get exchange A[14] and A[3] which is shown by a image.

Again call MAX HEAPIFY,
we get exchange A[10] and A[3] which is shown by a image.

Similarly,call MAX HEAPIFY
we’ll interchange A[7] and A[2]. which is shown by this image.

Similarly,call MAX HEAPIFY
we’ll interchange A[6] and A[3]. which is shown by this image.


Similarly,call MAX HEAPIFY
we’ll interchange A[6] and A[2]. which is shown by this image.
Final,call MAX HEAPIFY
we’ll interchange A[3] and A[2]. which is shown by this image.
and finally array will be sorted.
C Code of Heap Sort
#include<stdio.h> // including library files int temp; void heapify(int arr[], int size, int i)//declaring functions { int max = i; int left = 2*i + 1; int right = 2*i + 2; if (left < size && arr[left] >arr[max]) max= left; if (right < size && arr[right] > arr[max]) max= right; if (max!= i) { // performing sorting logic by using temporary variable temp = arr[i]; arr[i]= arr[max]; arr[max] = temp; heapify(arr, size, max); } } void heapSort(int arr[], int size)// providing definition to heap sort { int i; for (i = size / 2 - 1; i >= 0; i--) heapify(arr, size, i); for (i=size-1; i>=0; i--) { // swaping logic temp = arr[0]; arr[0]= arr[i]; arr[i] = temp; heapify(arr, i, 0); } } void main() // defining main() { int arr[] = {58, 134, 3, 67, 32, 89, 15, 10,78, 9}; // array initializing with their elements. int i; int size = sizeof(arr)/sizeof(arr[0]); heapSort(arr, size); printf("printing sorted elements\n"); // printing the sorted array for (i=0; i<size; ++i) printf("%d ",arr[i]); }
Output
printing sorted elements 3 9 10 15 32 58 67 78 89 134
Sorting
Sorting algorithms are easy to learn but are really important for college semester exams and companies offering package between 3 – 6 LPA would ask direct searching questions in online test/ interviews.

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