Deepest left leaf node in a binary tree
Last Updated : 07 Mar, 2023
Given a Binary Tree, find the deepest leaf node that is left child of its parent. For example, consider the following tree. The deepest left leaf node is the node with value 9.
1 / \ 2 3 / / \ 4 5 6 \ \ 7 8 / \ 9 10
The idea is to recursively traverse the given binary tree and while traversing, maintain “level” which will store the current node’s level in the tree. If current node is left leaf, then check if its level is more than the level of deepest left leaf seen so far. If level is more then update the result. If current node is not leaf, then recursively find maximum depth in left and right subtrees, and return maximum of the two depths.
Implementation:
C++ // A C++ program to find the deepest left leaf in a given binary tree #include <bits/stdc++.h> using namespace std; struct Node { int val; struct Node *left, *right; }; Node *newNode(int data) { Node *temp = new Node; temp->val = data; temp->left = temp->right = NULL; return temp; } // A utility function to find deepest leaf node. // lvl: level of current node. // maxlvl: pointer to the deepest left leaf node found so far // isLeft: A bool indicate that this node is left child of its parent // resPtr: Pointer to the result void deepestLeftLeafUtil(Node *root, int lvl, int *maxlvl, bool isLeft, Node **resPtr) { // Base case if (root == NULL) return; // Update result if this node is left leaf and its level is more // than the maxl level of the current result if (isLeft && !root->left && !root->right && lvl > *maxlvl) { *resPtr = root; *maxlvl = lvl; return; } // Recur for left and right subtrees deepestLeftLeafUtil(root->left, lvl+1, maxlvl, true, resPtr); deepestLeftLeafUtil(root->right, lvl+1, maxlvl, false, resPtr); } // A wrapper over deepestLeftLeafUtil(). Node* deepestLeftLeaf(Node *root) { int maxlevel = 0; Node *result = NULL; deepestLeftLeafUtil(root, 0, &maxlevel, false, &result); return result; } // Driver program to test above function int main() { Node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->right->left = newNode(5); root->right->right = newNode(6); root->right->left->right = newNode(7); root->right->right->right = newNode(8); root->right->left->right->left = newNode(9); root->right->right->right->right = newNode(10); Node *result = deepestLeftLeaf(root); if (result) cout << "The deepest left child is " << result->val; else cout << "There is no left leaf in the given tree"; return 0; }
Java // A Java program to find // the deepest left leaf // in a binary tree // A Binary Tree node class Node { int data; Node left, right; // Constructor public Node(int data) { this.data = data; left = right = null; } } // Class to evaluate pass // by reference class Level { // maxlevel: gives the // value of level of // maximum left leaf int maxlevel = 0; } class BinaryTree { Node root; // Node to store resultant // node after left traversal Node result; // A utility function to // find deepest leaf node. // lvl: level of current node. // isLeft: A bool indicate // that this node is left child void deepestLeftLeafUtil(Node node, int lvl, Level level, boolean isLeft) { // Base case if (node == null) return; // Update result if this node // is left leaf and its level // is more than the maxl level // of the current result if (isLeft != false && node.left == null && node.right == null && lvl > level.maxlevel) { result = node; level.maxlevel = lvl; } // Recur for left and right subtrees deepestLeftLeafUtil(node.left, lvl + 1, level, true); deepestLeftLeafUtil(node.right, lvl + 1, level, false); } // A wrapper over deepestLeftLeafUtil(). void deepestLeftLeaf(Node node) { Level level = new Level(); deepestLeftLeafUtil(node, 0, level, false); } // Driver program to test above functions public static void main(String[] args) { BinaryTree tree = new BinaryTree(); tree.root = new Node(1); tree.root.left = new Node(2); tree.root.right = new Node(3); tree.root.left.left = new Node(4); tree.root.right.left = new Node(5); tree.root.right.right = new Node(6); tree.root.right.left.right = new Node(7); tree.root.right.right.right = new Node(8); tree.root.right.left.right.left = new Node(9); tree.root.right.right.right.right = new Node(10); tree.deepestLeftLeaf(tree.root); if (tree.result != null) System.out.println("The deepest left child"+ " is " + tree.result.data); else System.out.println("There is no left leaf in"+ " the given tree"); } } // This code has been contributed by Mayank Jaiswal(mayank_24)
Python3 # Python program to find the deepest left leaf in a given # Binary tree # A binary tree node class Node: # Constructor to create a new node def __init__(self, val): self.val = val self.left = None self.right = None # A utility function to find deepest leaf node. # lvl: level of current node. # maxlvl: pointer to the deepest left leaf node found so far # isLeft: A bool indicate that this node is left child # of its parent # resPtr: Pointer to the result def deepestLeftLeafUtil(root, lvl, maxlvl, isLeft): # Base CAse if root is None: return # Update result if this node is left leaf and its # level is more than the max level of the current result if(isLeft is True): if (root.left == None and root.right == None): if lvl > maxlvl[0] : deepestLeftLeafUtil.resPtr = root maxlvl[0] = lvl return # Recur for left and right subtrees deepestLeftLeafUtil(root.left, lvl+1, maxlvl, True) deepestLeftLeafUtil(root.right, lvl+1, maxlvl, False) # A wrapper for left and right subtree def deepestLeftLeaf(root): maxlvl = [0] deepestLeftLeafUtil.resPtr = None deepestLeftLeafUtil(root, 0, maxlvl, False) return deepestLeftLeafUtil.resPtr # Driver program to test above function root = Node(1) root.left = Node(2) root.right = Node(3) root.left.left = Node(4) root.right.left = Node(5) root.right.right = Node(6) root.right.left.right = Node(7) root.right.right.right = Node(8) root.right.left.right.left = Node(9) root.right.right.right.right= Node(10) result = deepestLeftLeaf(root) if result is None: print ("There is not left leaf in the given tree") else: print ("The deepst left child is", result.val) # This code is contributed by Nikhil Kumar Singh(nickzuck_007)
C# using System; // A C# program to find // the deepest left leaf // in a binary tree // A Binary Tree node public class Node { public int data; public Node left, right; // Constructor public Node(int data) { this.data = data; left = right = null; } } // Class to evaluate pass // by reference public class Level { // maxlevel: gives the // value of level of // maximum left leaf public int maxlevel = 0; } public class BinaryTree { public Node root; // Node to store resultant // node after left traversal public Node result; // A utility function to // find deepest leaf node. // lvl: level of current node. // isLeft: A bool indicate // that this node is left child public virtual void deepestLeftLeafUtil(Node node, int lvl, Level level, bool isLeft) { // Base case if (node == null) { return; } // Update result if this node // is left leaf and its level // is more than the maxl level // of the current result if (isLeft != false && node.left == null && node.right == null && lvl > level.maxlevel) { result = node; level.maxlevel = lvl; } // Recur for left and right subtrees deepestLeftLeafUtil(node.left, lvl + 1, level, true); deepestLeftLeafUtil(node.right, lvl + 1, level, false); } // A wrapper over deepestLeftLeafUtil(). public virtual void deepestLeftLeaf(Node node) { Level level = new Level(); deepestLeftLeafUtil(node, 0, level, false); } // Driver program to test above functions public static void Main(string[] args) { BinaryTree tree = new BinaryTree(); tree.root = new Node(1); tree.root.left = new Node(2); tree.root.right = new Node(3); tree.root.left.left = new Node(4); tree.root.right.left = new Node(5); tree.root.right.right = new Node(6); tree.root.right.left.right = new Node(7); tree.root.right.right.right = new Node(8); tree.root.right.left.right.left = new Node(9); tree.root.right.right.right.right = new Node(10); tree.deepestLeftLeaf(tree.root); if (tree.result != null) { Console.WriteLine("The deepest left child is " + tree.result.data); } else { Console.WriteLine("There is no left leaf in the given tree"); } } } // This code is contributed by Shrikant13
JavaScript <script> // A Javascript program to find // the deepest left leaf // in a binary tree class Node { constructor(data) { this.left = null; this.right = null; this.data = data; } } let maxlevel = 0; let root; // Node to store resultant // node after left traversal let result; // A utility function to // find deepest leaf node. // lvl: level of current node. // isLeft: A bool indicate // that this node is left child function deepestLeftLeafUtil(node, lvl, isLeft) { // Base case if (node == null) return; // Update result if this node // is left leaf and its level // is more than the maxl level // of the current result if (isLeft != false && node.left == null && node.right == null && lvl > maxlevel) { result = node; maxlevel = lvl; } // Recur for left and right subtrees deepestLeftLeafUtil(node.left, lvl + 1, true); deepestLeftLeafUtil(node.right, lvl + 1, false); } // A wrapper over deepestLeftLeafUtil(). function deepestLeftLeaf(node) { deepestLeftLeafUtil(node, 0, false); } // Driver code root = new Node(1); root.left = new Node(2); root.right = new Node(3); root.left.left = new Node(4); root.right.left = new Node(5); root.right.right = new Node(6); root.right.left.right = new Node(7); root.right.right.right = new Node(8); root.right.left.right.left = new Node(9); root.right.right.right.right = new Node(10); deepestLeftLeaf(root); if (result != null) document.write("The deepest left child"+ " is " + result.data + "</br>"); else document.write("There is no left leaf in"+ " the given tree"); // This code is contributed by decode2207 </script>
OutputThe deepest left child is 9
Time Complexity: The function does a simple traversal of the tree, so the complexity is O(n).
Auxiliary Space: O(n) for call stack because using recursion
Iterative Approach(Using Level Order Traversal):
Follow the below steps to solve the above problem:
1) We simply traverse the tree using Level Order Traversal with queue data structure.
2) If current node has left child then we update our answer with left child.
3) Finally return the ans node.
Below is the implementation of above approach:
C++ // Iterative Approach to solve this problem // C++ code for above approach // This code is contributed by Yash Agarwal(yashagarwal2852002) #include<bits/stdc++.h> using namespace std; // a binary tree node struct Node{ int data; Node* left; Node* right; Node(int data){ this->data = data; this->left = NULL; this->right = NULL; } }; // utility function to create a new tree node Node* newNode(int data){ return new Node(data); } // function will return the deepest left leaf node Node* deepestLeftLeaf(Node* root){ if(root == NULL) return NULL; Node* ans = NULL; queue<Node*> q; q.push(root); while(!q.empty()){ Node* front_node = q.front(); q.pop(); if(front_node->left){ q.push(front_node->left); ans = front_node->left; } if(front_node->right){ q.push(front_node->right); } } return ans; } // Driver program to test above function int main() { Node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->right->left = newNode(5); root->right->right = newNode(6); root->right->left->right = newNode(7); root->right->right->right = newNode(8); root->right->left->right->left = newNode(9); root->right->right->right->right = newNode(10); Node *result = deepestLeftLeaf(root); if (result) cout << "The deepest left child is " << result->data; else cout << "There is no left leaf in the given tree"; return 0; } // THIS CODE IS CONTRIBUTED BY YASH AGARWAL(YASHAGARWAL2852002)
Java import java.util.LinkedList; import java.util.Queue; class Node { int data; Node left, right; public Node(int item) { data = item; left = right = null; } } public class Main { // utility function create a new node static Node newNode(int data) { return new Node(data); } // function will return the deepest left leaf node static Node deepestLeftLeaf(Node root) { if (root == null) return null; Node ans = null; Queue<Node> q = new LinkedList<Node>(); q.add(root); while (!q.isEmpty()) { Node front_node = q.poll(); if (front_node.left != null) { q.add(front_node.left); ans = front_node.left; } if (front_node.right != null) q.add(front_node.right); } return ans; } // driver code to test above function public static void main(String[] args) { Node root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.right.left = newNode(5); root.right.right = newNode(6); root.right.left.right = newNode(7); root.right.right.right = newNode(8); root.right.left.right.left = newNode(9); root.right.right.right.right = newNode(10); Node result = deepestLeftLeaf(root); if (result != null) { System.out.println("The deepest left child is : " + result.data); } else { System.out.println("There is no left leaf in the given tree."); } } }
Python # Iterative approach to solve this problem # Python code for the above approach # a binary tree node class Node: def __init__(self, data): self.data = data self.left = None self.right = None # utility function to create a new tree node def newNode(data): return Node(data) # // function will return the deepest left leaf node def deepestLeftLeaf(root): if(root is None): return ans = None q = [] q.append(root) while(len(q) > 0): front_node = q.pop(0) if(front_node.left is not None): q.append(front_node.left) ans = front_node.left if(front_node.right is not None): q.append(front_node.right) return ans # driver program to test above function root = newNode(1) root.left = newNode(2) root.right = newNode(3) root.left.left = newNode(4) root.right.left = newNode(5) root.right.right = newNode(6) root.right.left.right = newNode(7) root.right.right.right = newNode(8) root.right.left.right.left = newNode(9) root.right.right.right.right = newNode(10) result = deepestLeftLeaf(root) if(result is not None): print("The deepest left child is : ") print(result.data) else: print("There is no left leaf in the given tree.")
C# // C# Program to find sum of all right leaves using System; using System.Collections.Generic; public class Node{ public int data; public Node left, right; public Node(int item){ data = item; left = right = null; } } class GFG{ // utility function create a new node static Node newNode(int data){ return new Node(data); } // function will return the deepest left leaf node static Node deepestLeftLeaf(Node root){ if(root == null) return null; Node ans = null; Queue<Node> q = new Queue<Node>(); q.Enqueue(root); while(q.Count > 0){ Node front_node = q.Dequeue(); if(front_node.left != null){ q.Enqueue(front_node.left); ans = front_node.left; } if(front_node.right != null) q.Enqueue(front_node.right); } return ans; } // driver code to test above function public static void Main(String[] args){ Node root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.right.left = newNode(5); root.right.right = newNode(6); root.right.left.right = newNode(7); root.right.right.right = newNode(8); root.right.left.right.left = newNode(9); root.right.right.right.right = newNode(10); Node result = deepestLeftLeaf(root); if(result != null){ Console.WriteLine("The deepest left child is : " + result.data); } else{ Console.WriteLine("There is no left leaf in the given tree."); } } } // THIS CODE IS CONTRIBUTED BY YASH AGARWAL
JavaScript // JavaScript implementation of above approach // a binary tree node class Node{ constructor(data){ this.data = data; this.left = null; this.right = null; } } // utility functionto create a new node function newNode(data){ return new Node(data); } // function will return the deepest left leaf node function deepestLeftLeaf(root){ if(root == null) return null; let ans = null; let q = []; q.push(root); while(q.length > 0){ let front_node = q.shift(); if(front_node.left){ q.push(front_node.left); ans = front_node.left; } if(front_node.right) q.push(front_node.right); } return ans; } // driver code to test above function let root = newNode(1); root.left = newNode(2); root.right = newNode(3); root.left.left = newNode(4); root.right.left = newNode(5); root.right.right = newNode(6); root.right.left.right = newNode(7); root.right.right.right = newNode(8); root.right.left.right.left = newNode(9); root.right.right.right.right = newNode(10); let result = deepestLeftLeaf(root); if(result) console.log("The deepest left child is : " + result.data); else console.log("There is no left leaf in the given tree.");
OutputThe deepest left child is 9
Time Complexity: O(N) where N is the number of nodes in given binary tree.
Auxiliary Space: O(N) due to queue data structure.
Similar Reads
Delete the last leaf node in a Binary Tree
Given a Binary Tree, the task is to find and DELETE the last leaf node.The leaf node is a node with no children. The last leaf node would be the node that is traversed last in sequence during Level Order Traversal. The problem statement is to identify this last visited node and delete this particula
15+ min read
Deepest left leaf node in a binary tree | iterative approach
Given a Binary Tree, find the deepest leaf node that is left child of its parent. For example, consider the following tree. The deepest left leaf node is the node with value 9. Examples: Input : 1 / \ 2 3 / / \ 4 5 6 \ \ 7 8 / \ 9 10 Output : 9 Recursive approach to this problem is discussed hereFor
8 min read
Find the Deepest Node in a Binary Tree
Given a binary tree, find the deepÂest node in it. Examples: Input : Root of below tree 1 / \ 2 3 / \ / \ 4 5 6 7 \ 8 Output : 8 Input : Root of below tree 1 / \ 2 3 / 6 Output : 6 Method 1: The idea is to do Inorder traversal of a given binary tree. While doing Inorder traversal, we pass level of c
15+ min read
Count Non-Leaf nodes in a Binary Tree
Given a Binary tree, count the total number of non-leaf nodes in the tree Examples: Input : Output :2 Explanation In the above tree only two nodes 1 and 2 are non-leaf nodesRecommended PracticeCount Non-Leaf Nodes in TreeTry It! We recursively traverse the given tree. While traversing, we count non-
10 min read
Deepest right leaf node in a binary tree | Iterative approach
Given a Binary Tree, find the deepest leaf node that is the right child of its parent. For example, consider the following tree. The deepest right leaf node is the node with the value 10. Examples: Input : 1 / \ 2 3 \ / \ 4 5 6 \ \ 7 8 / \ 9 10 Output : 10 The idea is similar to Method 2 of level or
7 min read
Find the closest leaf in a Binary Tree
Given a Binary Tree and a key 'k', find distance of the closest leaf from 'k'. Examples: A / \ B C / \ E F / \ G H / \ / I J K Closest leaf to 'H' is 'K', so distance is 1 for 'H' Closest leaf to 'C' is 'B', so distance is 2 for 'C' Closest leaf to 'E' is either 'I' or 'J', so distance is 2 for 'E'
14 min read
Closest leaf to a given node in Binary Tree
Given a Binary Tree and a node x in it, find distance of the closest leaf to x in Binary Tree. If given node itself is a leaf, then distance is 0.Examples: Input: Root of below tree And x = pointer to node 13 10 / \ 12 13 / 14 Output 1 Distance 1. Closest leaf is 14. Input: Root of below tree And x
12 min read
Level of a Node in Binary Tree
Given a Binary Tree and a key, the task is to find the level of key in the Binary Tree. Examples: Input : key = 4 Output: 3Explanation: The level of the key in above binary tree is 3.Input : key = 10 Output: -1Explanation: Key is not present in the above Binary tree. Table of Content [Expected Appro
12 min read
Depth of the deepest odd level node in Binary Tree
Given a Binary tree, find out depth of the deepest odd level leaf node. Take root level as depth 1. Examples: Input : Output : 5Input : 10 / \ 28 13 / \ 14 15 / \ 23 24Output : 3We can traverse the tree starting from the root level and keep curr_level of the node. Increment the curr_level each time
14 min read
Deletion in a Binary Tree
Given a binary tree, the task is to delete a given node from it by making sure that the tree shrinks from the bottom (i.e. the deleted node is replaced by the bottom-most and rightmost node). This is different from BST deletion. Here we do not have any order among elements, so we replace them with t
12 min read