Skip to content
Related Articles

Related Articles

Distance of each node of a Binary Tree from the root node using BFS

View Discussion
Improve Article
Save Article
  • Last Updated : 21 Jun, 2021
View Discussion
Improve Article
Save Article

Given a Binary tree consisting of N nodes with values in the range [1, N], the task is to find the distance from the root node to every node of the tree.

Examples:

Input: 

                  1
                 /  \
                2   3 
               / \   \
             4   5   6

Output: 0 1 1 2 2 2 
Explanation: 
The distance from the root to node 1 is 0. 
The distance from the root to node 2 is 1. 
The distance from the root to node 3 is 1. 
The distance from the root to node 4 is 2. 
The distance from the root to node 5 is 2. 
The distance from the root to node 6 is 2.
 

Input: 

                  5
                 / \
               4    6
             /  \     
            3    7
          / \     
        1    2

Output: 3 3 2 1 0 1 2

 
 

Approach: The problem can be solved using BFS technique. The idea is to use the fact that the distance from the root to a node is equal to the level of that node in the binary tree. Follow the steps below to solve the problem:

  • Initialize a queue, say Q, to store the nodes at each level of the tree.
  • Initialize an array, say dist[], where dist[i] stores the distance from the root node to ith of the tree.
  • Traverse the tree using BFS. For every ith node encountered, update dist[i] to the level of that node in the binary tree.
  • Finally, print the dist[] array.

Below is the implementation of the above approach:

C++




// C++ program to implement
// the above approach
 
#include <bits/stdc++.h>
using namespace std;
struct Node {
 
    // Stores data value
    // of the node
    int data;
 
    // Stores left subtree
    // of a node
    Node* left;
 
    // Stores right subtree
    // of a node
    Node* right;
 
    Node(int x)
    {
 
        data = x;
        left = right = NULL;
    }
};
 
void findDistance(Node* root, int N)
{
 
    // Store nodes at each level
    // of the binary tree
    queue<Node*> Q;
 
    // Insert root into Q
    Q.push(root);
 
    // Stores level of a node
    int level = 0;
 
    // dist[i]: Stores the distance
    // from root node to node i
    int dist[N + 1];
 
    // Traverse tree using BFS
    while (!Q.empty()) {
 
        // Stores count of nodes
        // at current level
        int M = Q.size();
 
        // Traverse the nodes at
        // current level
        for (int i = 0; i < M; i++) {
 
            // Stores front element
            // of the queue
            root = Q.front();
 
            // Pop front element
            // of the queue
            Q.pop();
 
            // Stores the distance from
            // root node to current node
            dist[root->data] = level;
 
            if (root->left) {
 
                // Push left subtree
                Q.push(root->left);
            }
 
            if (root->right) {
 
                // Push right subtree
                Q.push(root->right);
            }
        }
 
        // Update level
        level += 1;
    }
 
    for (int i = 1; i <= N; i++) {
 
        cout << dist[i] << " ";
    }
}
 
// Driver Code
int main()
{
 
    int N = 7;
    Node* root = new Node(5);
    root->left = new Node(4);
    root->right = new Node(6);
    root->left->left = new Node(3);
    root->left->right = new Node(7);
    root->left->left->left = new Node(1);
    root->left->left->right = new Node(2);
    findDistance(root, N);
}

Java




// Java program to implement
// the above approach
import java.util.*;
 
class GFG
{
static class Node
{
 
    // Stores data value
    // of the node
    int data;
 
    // Stores left subtree
    // of a node
    Node left;
 
    // Stores right subtree
    // of a node
    Node right;
    Node(int x)
    {
        data = x;
        left = right = null;
    }
};
 
static void findDistance(Node root, int N)
{
 
    // Store nodes at each level
    // of the binary tree
    Queue<Node> Q = new LinkedList<>();
 
    // Insert root into Q
    Q.add(root);
 
    // Stores level of a node
    int level = 0;
 
    // dist[i]: Stores the distance
    // from root node to node i
    int []dist = new int[N + 1];
 
    // Traverse tree using BFS
    while (!Q.isEmpty())
    {
 
        // Stores count of nodes
        // at current level
        int M = Q.size();
 
        // Traverse the nodes at
        // current level
        for (int i = 0; i < M; i++)
        {
 
            // Stores front element
            // of the queue
            root = Q.peek();
 
            // Pop front element
            // of the queue
            Q.remove();
 
            // Stores the distance from
            // root node to current node
            dist[root.data] = level;
 
            if (root.left != null)
            {
 
                // Push left subtree
                Q.add(root.left);
            }
 
            if (root.right != null)
            {
 
                // Push right subtree
                Q.add(root.right);
            }
        }
 
        // Update level
        level += 1;
    }
 
    for (int i = 1; i <= N; i++)
    {
        System.out.print(dist[i] + " ");
    }
}
 
// Driver Code
public static void main(String[] args)
{
 
    int N = 7;
    Node root = new Node(5);
    root.left = new Node(4);
    root.right = new Node(6);
    root.left.left = new Node(3);
    root.left.right = new Node(7);
    root.left.left.left = new Node(1);
    root.left.left.right = new Node(2);
    findDistance(root, N);
}
}
 
// This code is contributed by shikhasingrajput

Python3




# Python3 program to implement
# the above approach
class Node:
     
    def __init__(self, data):
         
        # Stores data value
        # of the node
        self.data = data
         
        # Stores left subtree
        # of a node
        self.left = None
         
        # Stores right subtree
        # of a node
        self.right = None
 
def findDistance(root, N):
     
    # Store nodes at each level
    # of the binary tree
    Q = []
     
    # Insert root into Q
    Q.append(root)
     
    # Stores level of a node
    level = 0
     
    # dist[i]: Stores the distance
    # from root node to node i
    dist = [0 for i in range(N + 1)]
     
    # Traverse tree using BFS
    while Q:
         
        # Stores count of nodes
        # at current level
        M = len(Q)
         
        # Traverse the nodes at
        # current level
        for i in range(0, M):
             
            # Stores front element
            # of the queue
            root = Q[0]
             
            # Pop front element
            # of the queue
            Q.pop(0)
             
            #  Stores the distance from
            # root node to current node
            dist[root.data] = level
             
            if root.left:
                 
                # Push left subtree
                Q.append(root.left)
            if root.right:
                 
                # Push right subtree
                Q.append(root.right)
                 
        # Update level
        level += 1
         
    for i in range(1, N + 1):
        print(dist[i], end = " ")
 
# Driver code
if __name__ == '__main__':
     
    N = 7
    root = Node(5)
    root.left = Node(4)
    root.right = Node(6)
    root.left.left = Node(3)
    root.left.right = Node(7)
    root.left.left.left = Node(1)
    root.left.left.right = Node(2)
     
    findDistance(root, N)
 
# This code is contributed by MuskanKalra1

C#




// C# program to implement
// the above approach
using System;
using System.Collections.Generic;
class GFG
{
  class Node
  {
 
    // Stores data value
    // of the node
    public int data;
 
    // Stores left subtree
    // of a node
    public Node left;
 
    // Stores right subtree
    // of a node
    public Node right;
    public Node(int x)
    {
      data = x;
      left = right = null;
    }
  };
 
  static void findDistance(Node root, int N)
  {
 
    // Store nodes at each level
    // of the binary tree
    Queue<Node> Q = new Queue<Node>();
 
    // Insert root into Q
    Q.Enqueue(root);
 
    // Stores level of a node
    int level = 0;
 
    // dist[i]: Stores the distance
    // from root node to node i
    int []dist = new int[N + 1];
 
    // Traverse tree using BFS
    while (Q.Count != 0)
    {
 
      // Stores count of nodes
      // at current level
      int M = Q.Count;
 
      // Traverse the nodes at
      // current level
      for (int i = 0; i < M; i++)
      {
 
        // Stores front element
        // of the queue
        root = Q.Peek();
 
        // Pop front element
        // of the queue
        Q.Dequeue();
 
        // Stores the distance from
        // root node to current node
        dist[root.data] = level;
 
        if (root.left != null)
        {
 
          // Push left subtree
          Q.Enqueue(root.left);
        }
 
        if (root.right != null)
        {
 
          // Push right subtree
          Q.Enqueue(root.right);
        }
      }
 
      // Update level
      level += 1;
    }
 
    for (int i = 1; i <= N; i++)
    {
      Console.Write(dist[i] + " ");
    }
  }
 
  // Driver Code
  public static void Main(String[] args)
  {
 
    int N = 7;
    Node root = new Node(5);
    root.left = new Node(4);
    root.right = new Node(6);
    root.left.left = new Node(3);
    root.left.right = new Node(7);
    root.left.left.left = new Node(1);
    root.left.left.right = new Node(2);
    findDistance(root, N);
  }
}
 
// This code is contributed by shikhasingrajput

Javascript




<script>
 
    // JavaScript program to implement the above approach
     
    // Structure of a tree node
    class Node
    {
        constructor(x) {
           this.left = null;
           this.right = null;
           this.data = x;
        }
    }
     
    function findDistance(root, N)
    {
 
        // Store nodes at each level
        // of the binary tree
        let Q = [];
 
        // Insert root into Q
        Q.push(root);
 
        // Stores level of a node
        let level = 0;
 
        // dist[i]: Stores the distance
        // from root node to node i
        let dist = new Array(N + 1);
 
        // Traverse tree using BFS
        while (Q.length > 0)
        {
 
            // Stores count of nodes
            // at current level
            let M = Q.length;
 
            // Traverse the nodes at
            // current level
            for (let i = 0; i < M; i++)
            {
 
                // Stores front element
                // of the queue
                root = Q[0];
 
                // Pop front element
                // of the queue
                Q.shift();
 
                // Stores the distance from
                // root node to current node
                dist[root.data] = level;
 
                if (root.left != null)
                {
 
                    // Push left subtree
                    Q.push(root.left);
                }
 
                if (root.right != null)
                {
 
                    // Push right subtree
                    Q.push(root.right);
                }
            }
 
            // Update level
            level += 1;
        }
 
        for (let i = 1; i <= N; i++)
        {
            document.write(dist[i] + " ");
        }
    }
     
    let N = 7;
    let root = new Node(5);
    root.left = new Node(4);
    root.right = new Node(6);
    root.left.left = new Node(3);
    root.left.right = new Node(7);
    root.left.left.left = new Node(1);
    root.left.left.right = new Node(2);
    findDistance(root, N);
 
</script>

Output: 

3 3 2 1 0 1 2

 

Time Complexity: O(N) 
Auxiliary Space: O(N)


My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!