Count number of nodes in a complete Binary Tree
Given the root of a Complete Binary Tree consisting of N nodes, the task is to find the total number of nodes in the given Binary Tree.
Examples:
Input:
Output: 7
Input:
Output: 5
Naive Approach: The simple approach to solving the given tree is to perform the DFS Traversal on the given tree and count the number of nodes in it. After traversal, print the total count of nodes obtained.
C++
// C++ program for the above approach #include <bits/stdc++.h> using namespace std; // Structure of a Tree Node class node { public : int data; node* left; node* right; }; // Function to get the count of nodes // in complete binary tree int totalNodes(node* root) { if (root == NULL) return 0; int l = totalNodes(root->left); int r = totalNodes(root->right); return 1 + l + r; } // Helper function to allocate a new node // with the given data node* newNode( int data) { node* Node = new node(); Node->data = data; Node->left = NULL; Node->right = NULL; return (Node); } // Driver Code int main() { node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->left->right = newNode(5); root->right->left = newNode(9); root->right->right = newNode(8); root->left->left->left = newNode(6); root->left->left->right = newNode(7); cout << totalNodes(root); return 0; } |
Java
// Java program for the above approach import java.io.*; class GFG { // tree node static class node { public int data; public node left, right; public node(){ data = 0 ; left = right = null ; } } // Function to get the count of nodes // in complete binary tree static int totalNodes(node root) { if (root == null ) return 0 ; int l = totalNodes(root.left); int r = totalNodes(root.right); return 1 + l + r; } // Helper function to allocate a new node // with the given data static node newNode( int data) { node temp = new node(); temp.data = data; temp.left = temp.right = null ; return temp; } // Driver Code public static void main(String args[]) { node root = newNode( 1 ); root.left = newNode( 2 ); root.right = newNode( 3 ); root.left.left = newNode( 4 ); root.left.right = newNode( 5 ); root.right.left = newNode( 9 ); root.right.right = newNode( 8 ); root.left.left.left = newNode( 6 ); root.left.left.right = newNode( 7 ); System.out.println(totalNodes(root)); } } // This code is contributed by poojaagarwal2. |
Python
# Python program for the above approach # Structure of a Tree Node class node: def __init__( self , data): self .left = None self .right = None self .data = data # Function to get the count of nodes # in complete binary tree def totalNodes(root): # Base case if (root = = None ): return 0 # Find the left height and the # right heights l = totalNodes(root.left) r = totalNodes(root.right) return 1 + l + r # Helper Function to allocate a new node # with the given data def newNode(data): Node = node(data) return Node # Driver code root = newNode( 1 ) root.left = newNode( 2 ) root.right = newNode( 3 ) root.left.left = newNode( 4 ) root.left.right = newNode( 5 ) root.right.left = newNode( 9 ) root.right.right = newNode( 8 ) root.left.left.left = newNode( 6 ) root.left.left.right = newNode( 7 ) print (totalNodes(root)) # This code is contributed by Yash Agarwal(yashagarwal2852002) |
Javascript
<script> //JavaScript code for the above approach // Structure of a Tree Node class Node { constructor(data) { this .data = data; this .left = null ; this .right = null ; } } // Function to get the count of nodes // in complete binary tree function totalNodes(root) { if (root === null ) { return 0; } let l = totalNodes(root.left); let r = totalNodes(root.right); return 1 + l + r; } // Helper function to allocate a new node // with the given data function newNode(data) { return new Node(data); } // Driver Code let root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.left.right = newNode(5); root.right.left = newNode(9); root.right.right = newNode(8); root.left.left.left = newNode(6); root.left.left.right = newNode(7); document.write(totalNodes(root)); // This code is contributed by Potta Lokesh </script> |
C#
//C# code for the above approach using System; class GFG { // tree node public class node { public int data; public node left, right; public node() { data = 0; left = right = null ; } } // Function to get the count of nodes // in complete binary tree static int totalNodes(node root) { if (root == null ) return 0; int l = totalNodes(root.left); int r = totalNodes(root.right); return 1 + l + r; } // Helper function to allocate a new node // with the given data static node newNode( int data) { node temp = new node(); temp.data = data; temp.left = temp.right = null ; return temp; } // Driver Code static void Main( string [] args) { node root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.left.right = newNode(5); root.right.left = newNode(9); root.right.right = newNode(8); root.left.left.left = newNode(6); root.left.left.right = newNode(7); Console.WriteLine(totalNodes(root)); } } |
9
Time Complexity: O(N) as in traversal all the nodes are visited
Reason:
- Recurrence Relation: T(N) = 2*T(N/2) + O(1)
- Solve via Master’s Theorem, you will get O(N) as Time.
Auxiliary Space: O(h) = O(log N) as height of CBT is LogN
Reason:
- Recursion Stack Space (which takes elements up to the height of the tree)
- As you will go left, left till the corner leaf node. All of these stay in the stack on top of one another.
Efficient Approach: The above approach can also be optimized by the fact that:
A complete binary tree can have at most (2h + 1 – 1) nodes in total where h is the height of the tree (This happens when all the levels are completely filled).
By this logic, in the first case, compare the left sub-tree height with the right sub-tree height. If they are equal it is a full tree, then the answer will be 2^height – 1. Otherwise, If they aren’t equal, recursively call for the left sub-tree and the right sub-tree to count the number of nodes. Follow the steps below to solve the problem:
- Define a function left_height(root) and find the left height of the given Tree by traversing in the root’s left direction and store it in a variable, say leftHeight.
- Define a function right_height(root) and find the right height of the given Tree by traversing in the root’s right direction and store it in a variable, say rightHeight.
- Find the left and the right height of the given Tree for the current root value and if it is equal then return the value of (2height – 1) as the resultant count of nodes.
- Otherwise, recursively call for the function for the left and right sub-trees and return the sum of them + 1 as the resultant count of nodes.
Below is the implementation of the above approach.
C++
// C++ program for the above approach #include <bits/stdc++.h> using namespace std; // Structure of a Tree Node class node { public : int data; node* left; node* right; }; node* newNode( int data); // Function to get the left height of // the binary tree int left_height(node* node) { int ht = 0; while (node) { ht++; node = node->left; } // Return the left height obtained return ht; } // Function to get the right height // of the binary tree int right_height(node* node) { int ht = 0; while (node) { ht++; node = node->right; } // Return the right height obtained return ht; } // Function to get the count of nodes // in complete binary tree int TotalNodes(node* root) { // Base Case if (root == NULL) return 0; // Find the left height and the // right heights int lh = left_height(root); int rh = right_height(root); // If left and right heights are // equal return 2^height(1<<height) -1 if (lh == rh) return (1 << lh) - 1; // Otherwise, recursive call return 1 + TotalNodes(root->left) + TotalNodes(root->right); } // Helper function to allocate a new node // with the given data node* newNode( int data) { node* Node = new node(); Node->data = data; Node->left = NULL; Node->right = NULL; return (Node); } // Driver Code int main() { node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->left->right = newNode(5); root->right->left = newNode(9); root->right->right = newNode(8); root->left->left->left = newNode(6); root->left->left->right = newNode(7); cout << TotalNodes(root); return 0; } // This code is contributed by aditya kumar (adityakumar129) |
C
// C program for the above approach #include <stdio.h> #include <stdlib.h> // Structure of a Tree Node typedef struct node { int data; struct node* left; struct node* right; }node; // Helper function to allocate a new node // with the given data node* newNode( int data) { node * Node = (node *) malloc ( sizeof (node)); Node->data = data; Node->left = NULL; Node->right = NULL; return (Node); } // Function to get the left height of // the binary tree int left_height(node* node) { int ht = 0; while (node) { ht++; node = node->left; } // Return the left height obtained return ht; } // Function to get the right height // of the binary tree int right_height(node* node) { int ht = 0; while (node) { ht++; node = node->right; } // Return the right height obtained return ht; } // Function to get the count of nodes // in complete binary tree int TotalNodes(node* root) { // Base Case if (root == NULL) return 0; // Find the left height and the // right heights int lh = left_height(root); int rh = right_height(root); // If left and right heights are // equal return 2^height(1<<height) -1 if (lh == rh) return (1 << lh) - 1; // Otherwise, recursive call return 1 + TotalNodes(root->left) + TotalNodes(root->right); } // Driver Code int main() { node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->left->right = newNode(5); root->right->left = newNode(9); root->right->right = newNode(8); root->left->left->left = newNode(6); root->left->left->right = newNode(7); printf ( "%d" ,TotalNodes(root)); return 0; } // This code is contributed by aditya kumar (adityakumar129) |
Java
// Java program for the above approach import java.util.*; class GFG{ // Structure of a Tree Node static class node { int data; node left; node right; }; // Function to get the left height of // the binary tree static int left_height(node node) { int ht = 0 ; while (node!= null ) { ht++; node = node.left; } // Return the left height obtained return ht; } // Function to get the right height // of the binary tree static int right_height(node node) { int ht = 0 ; while (node!= null ) { ht++; node = node.right; } // Return the right height obtained return ht; } // Function to get the count of nodes // in complete binary tree static int TotalNodes(node root) { // Base Case if (root == null ) return 0 ; // Find the left height and the // right heights int lh = left_height(root); int rh = right_height(root); // If left and right heights are // equal return 2^height(1<<height) -1 if (lh == rh) return ( 1 << lh) - 1 ; // Otherwise, recursive call return 1 + TotalNodes(root.left) + TotalNodes(root.right); } // Helper function to allocate a new node // with the given data static node newNode( int data) { node Node = new node(); Node.data = data; Node.left = null ; Node.right = null ; return (Node); } // Driver Code public static void main(String[] args) { node root = newNode( 1 ); root.left = newNode( 2 ); root.right = newNode( 3 ); root.left.left = newNode( 4 ); root.left.right = newNode( 5 ); root.right.left = newNode( 9 ); root.right.right = newNode( 8 ); root.left.left.left = newNode( 6 ); root.left.left.right = newNode( 7 ); System.out.print(TotalNodes(root)); } } // This code is contributed by shikhasingrajput |
Python3
# Python program for the above approach # Structure of a Tree Node class node: def __init__( self , key): self .left = None self .right = None self .val = key # Function to get the left height of # the binary tree def left_height(node): ht = 0 while (node): ht + = 1 node = node.left # Return the left height obtained return ht # Function to get the right height # of the binary tree def right_height(node): ht = 0 while (node): ht + = 1 node = node.right # Return the right height obtained return ht # Function to get the count of nodes # in complete binary tree def TotalNodes(root): # Base case if (root = = None ): return 0 # Find the left height and the # right heights lh = left_height(root) rh = right_height(root) # If left and right heights are # equal return 2^height(1<<height) -1 if (lh = = rh): return ( 1 << lh) - 1 # Otherwise, recursive call return 1 + TotalNodes(root.left) + TotalNodes(root.right) # Driver code root = node( 1 ) root.left = node( 2 ) root.right = node( 3 ) root.left.left = node( 4 ) root.left.right = node( 5 ) root.right.left = node( 9 ) root.right.right = node( 8 ) root.left.left.left = node( 6 ) root.left.left.right = node( 7 ) print (TotalNodes(root)) # This code is contributed by parthmanchanda81 |
C#
// C# program for the above approach using System; public class GFG{ // Structure of a Tree Node class node { public int data; public node left; public node right; }; // Function to get the left height of // the binary tree static int left_height(node node) { int ht = 0; while (node != null ) { ht++; node = node.left; } // Return the left height obtained return ht; } // Function to get the right height // of the binary tree static int right_height(node node) { int ht = 0; while (node != null ) { ht++; node = node.right; } // Return the right height obtained return ht; } // Function to get the count of nodes // in complete binary tree static int TotalNodes(node root) { // Base Case if (root == null ) return 0; // Find the left height and the // right heights int lh = left_height(root); int rh = right_height(root); // If left and right heights are // equal return 2^height(1<<height) -1 if (lh == rh) return (1 << lh) - 1; // Otherwise, recursive call return 1 + TotalNodes(root.left) + TotalNodes(root.right); } // Helper function to allocate a new node // with the given data static node newNode( int data) { node Node = new node(); Node.data = data; Node.left = null ; Node.right = null ; return (Node); } // Driver Code public static void Main(String[] args) { node root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.left.right = newNode(5); root.right.left = newNode(9); root.right.right = newNode(8); root.left.left.left = newNode(6); root.left.left.right = newNode(7); Console.Write(TotalNodes(root)); } } // This code is contributed by shikhasingrajput |
Javascript
<script> // JavaScript Program to implement // the above approach // Structure of a Tree Node class Node { constructor(data) { this .data = data; this .left = null ; this .right = null ; } }; // Function to get the left height of // the binary tree function left_height(node) { let ht = 0; while (node) { ht++; node = node.left; } // Return the left height obtained return ht; } // Function to get the right height // of the binary tree function right_height(node) { let ht = 0; while (node) { ht++; node = node.right; } // Return the right height obtained return ht; } // Function to get the count of nodes // in complete binary tree function TotalNodes(root) { // Base Case if (root == null ) return 0; // Find the left height and the // right heights let lh = left_height(root); let rh = right_height(root); // If left and right heights are // equal return 2^height(1<<height) -1 if (lh == rh) return (1 << lh) - 1; // Otherwise, recursive call return 1 + TotalNodes(root.left) + TotalNodes(root.right); } // Helper function to allocate a new node // with the given data // Driver Code let root = new Node(1); root.left = new Node(2); root.right = new Node(3); root.left.left = new Node(4); root.left.right = new Node(5); root.right.left = new Node(9); root.right.right = new Node(8); root.left.left.left = new Node(6); root.left.left.right = new Node(7); document.write(TotalNodes(root)); // This code is contributed by Potta Lokesh </script> |
9
Time Complexity: O((log N)2)
- Calculating the height of a tree with x nodes takes (log x) time.
- Here, we are traversing through the height of the tree.
- For each node, height calculation takes logarithmic time.
- As the number of nodes is N, we are traversing log(N) nodes and calculating the height for each of them.
- So the total complexity is (log N * log N) = (log N)2.
Auxiliary Space: O(log N) because of Recursion Stack Space (which takes elements upto the maximum depth of a node in the tree)
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