Given a Binary Tree, the task is to find the maximum of all the XOR value of all the nodes in the path from the root to leaf.
Examples:
Input: 2 / \ 1 4 / \ 10 8 Output: 11 Explanation: All the paths are: 2-1-10 XOR-VALUE = 9 2-1-8 XOR-VALUE = 11 2-4 XOR-VALUE = 6 Input: 2 / \ 1 4 / \ / \ 10 8 5 10 Output: 12
Approach:
- To solve the question mentioned above we have to traverse the tree recursively using pre-order traversal. For each node keep calculating the XOR of the path from root till the current node.
XOR of current node’s path = (XOR of the path till the parent) ^ (current node value)
- If the node is a leaf node that is left and the right child for the current nodes are NULL then we compute the max-Xor, as
max-Xor = max(max-Xor, cur-Xor).
Below is the implementation of the above approach:
C++
// C++ program to compute the // Max-Xor value of path from // the root to leaf of a Binary tree #include <bits/stdc++.h> using namespace std; // Binary tree node struct Node { int data; struct Node *left, *right; }; // Function to create a new node struct Node* newNode( int data) { struct Node* newNode = new Node; newNode->data = data; newNode->left = newNode->right = NULL; return (newNode); } // Function calculate the // value of max-xor void Solve(Node* root, int xr, int & max_xor) { // Updating the xor value // with the xor of the // path from root to // the node xr = xr ^ root->data; // Check if node is leaf node if (root->left == NULL && root->right == NULL) { max_xor = max(max_xor, xr); return ; } // Check if the left // node exist in the tree if (root->left != NULL) { Solve(root->left, xr, max_xor); } // Check if the right node // exist in the tree if (root->right != NULL) { Solve(root->right, xr, max_xor); } return ; } // Function to find the // required count int findMaxXor(Node* root) { int xr = 0, max_xor = 0; // Recursively traverse // the tree and compute // the max_xor Solve(root, xr, max_xor); // Return the result return max_xor; } // Driver code int main( void ) { // Create the binary tree struct Node* root = newNode(2); root->left = newNode(1); root->right = newNode(4); root->left->left = newNode(10); root->left->right = newNode(8); root->right->left = newNode(5); root->right->right = newNode(10); cout << findMaxXor(root); return 0; } |
Java
// Java program to compute the // Max-Xor value of path from // the root to leaf of a Binary tree class GFG { // Binary tree node static class Node { int data = 0 ; Node left = null , right = null ; }; // Function to create a new node static Node newNode( int data) { Node newNode = new Node(); newNode.data = data; newNode.left = newNode.right = null ; return (newNode); } // Function calculate the // value of max-xor static int Solve(Node root, int xr, int max_xor) { // Updating the xor value // with the xor of the // path from root to // the node xr = xr ^ root.data; // Check if node is leaf node if (root.left == null && root.right == null ) { max_xor = Math.max(max_xor, xr); return max_xor; } // Check if the left // node exist in the tree if (root.left != null ) { max_xor = Solve(root.left, xr, max_xor); } // Check if the right node // exist in the tree if (root.right != null ) { max_xor = Solve(root.right, xr, max_xor); } return max_xor; } // Function to find the // required count static int findMaxXor(Node root) { int xr = 0 , max_xor = 0 ; // Recursively traverse // the tree and compute // the max_xor max_xor = Solve(root, xr, max_xor); // Return the result return max_xor; } // Driver code public static void main(String args[]) { // Create the binary tree Node root = newNode( 2 ); root.left = newNode( 1 ); root.right = newNode( 4 ); root.left.left = newNode( 10 ); root.left.right = newNode( 8 ); root.right.left = newNode( 5 ); root.right.right = newNode( 10 ); System.out.print(findMaxXor(root)); } } // This code is contributed by saurabh_jaiswal. |
Python3
# Python3 program to compute the # Max-Xor value of path from # the root to leaf of a Binary tree # Binary tree node class Node: # Function to create a new node def __init__( self , data): self .data = data self .left = None self .right = None # Function calculate the # value of max-xor def Solve(root, xr, max_xor): # Updating the xor value # with the xor of the # path from root to # the node xr = xr ^ root.data # Check if node is leaf node if (root.left = = None and root.right = = None ): max_xor[ 0 ] = max (max_xor[ 0 ], xr) # Check if the left # node exist in the tree if root.left ! = None : Solve(root.left, xr, max_xor) # Check if the right node # exist in the tree if root.right ! = None : Solve(root.right, xr, max_xor) return # Function to find the # required count def findMaxXor(root): xr, max_xor = 0 , [ 0 ] # Recursively traverse # the tree and compute # the max_xor Solve(root, xr, max_xor) # Return the result return max_xor[ 0 ] # Driver code # Create the binary tree root = Node( 2 ) root.left = Node( 1 ) root.right = Node( 4 ) root.left.left = Node( 10 ) root.left.right = Node( 8 ) root.right.left = Node( 5 ) root.right.right = Node( 10 ) print (findMaxXor(root)) # This code is contributed by Shivam Singh |
C#
// C# code for the above approach using System; namespace GFG { // Binary tree node class Node { public int data = 0; public Node left = null , right = null ; } class GFG { // Function to create a new node static Node newNode( int data) { Node newNode = new Node(); newNode.data = data; newNode.left = newNode.right = null ; return (newNode); } // Function calculate the // value of max-xor static int Solve(Node root, int xr, int max_xor) { // Updating the xor value // with the xor of the // path from root to // the node xr = xr ^ root.data; // Check if node is leaf node if (root.left == null && root.right == null ) { max_xor = Math.Max(max_xor, xr); return max_xor; } // Check if the left // node exist in the tree if (root.left != null ) { max_xor = Solve(root.left, xr, max_xor); } // Check if the right node // exist in the tree if (root.right != null ) { max_xor = Solve(root.right, xr, max_xor); } return max_xor; } // Function to find the // required count static int findMaxXor(Node root) { int xr = 0, max_xor = 0; // Recursively traverse // the tree and compute // the max_xor max_xor = Solve(root, xr, max_xor); // Return the result return max_xor; } // Driver code static void Main( string [] args) { // Create the binary tree Node root = newNode(2); root.left = newNode(1); root.right = newNode(4); root.left.left = newNode(10); root.left.right = newNode(8); root.right.left = newNode(5); root.right.right = newNode(10); Console.WriteLine(findMaxXor(root)); } } } // This code is contributed by Potta Lokesh |
Javascript
<script> // JavaScript program to compute the // Max-Xor value of path from // the root to leaf of a Binary tree // Binary tree node class Node { constructor() { this .data = 0; this .left = null ; this .right = null ; } }; // Function to create a new node function newNode(data) { var newNode = new Node; newNode.data = data; newNode.left = newNode.right = null ; return (newNode); } // Function calculate the // value of Math.max-xor function Solve(root, xr, max_xor) { // Updating the xor value // with the xor of the // path from root to // the node xr = xr ^ root.data; // Check if node is leaf node if (root.left == null && root.right == null ) { max_xor = Math.max(max_xor, xr); return max_xor; } // Check if the left // node exist in the tree if (root.left != null ) { max_xor = Solve(root.left, xr, max_xor); } // Check if the right node // exist in the tree if (root.right != null ) { max_xor = Solve(root.right, xr, max_xor); } return max_xor; } // Function to find the // required count function findMaxXor(root) { var xr = 0, max_xor = 0; // Recursively traverse // the tree and compute // the max_xor max_xor = Solve(root, xr, max_xor); // Return the result return max_xor; } // Driver code // Create the binary tree var root = newNode(2); root.left = newNode(1); root.right = newNode(4); root.left.left = newNode(10); root.left.right = newNode(8); root.right.left = newNode(5); root.right.right = newNode(10); document.write( findMaxXor(root)); </script> |
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Time Complexity: We are iterating over each node only once, therefore it will take O(N) time where N is the number of nodes in the Binary tree.
Auxiliary Space Complexity: The Auxiliary Space complexity will be O(1), as there is no extra space used
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