Given a binary tree. The task is to find the value of the deepest node in the given binary tree.
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
Approach: We have already discussed the two different ways to find the deepest node in a binary tree in this post. Here, we will find the deepest node in the tree using a queue data structure. We will first push the root into the queue and then we will push it’s child nodes after removing parent node from the queue. We will continue this process until the queue empty. The last node in the queue is the deepest node of the binary tree.
Below is the implementation of the above approach :
Time Complexity: O(N)
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- Find the Deepest Node in a Binary Tree
- Deepest left leaf node in a binary tree
- Depth of the deepest odd level node in Binary Tree
- Deepest left leaf node in a binary tree | iterative approach
- Deepest right leaf node in a binary tree | Iterative approach
- Find depth of the deepest odd level leaf node
- Convert a Binary Tree to Threaded binary tree | Set 1 (Using Queue)
- queue::empty() and queue::size() in C++ STL
- queue::push() and queue::pop() in C++ STL
- queue::front() and queue::back() in C++ STL
- Binary Tree to Binary Search Tree Conversion using STL set
- Find maximum and minimum element in binary tree without using recursion or stack or queue
- Right view of Binary Tree using Queue
- Complexity of different operations in Binary tree, Binary Search Tree and AVL tree
- Check if a binary tree is subtree of another binary tree using preorder traversal : Iterative
- Check if a binary tree is subtree of another binary tree | Set 1
- Check if a binary tree is subtree of another binary tree | Set 2
- Convert a Binary Tree to Threaded binary tree | Set 2 (Efficient)
- Binary Tree | Set 3 (Types of Binary Tree)
- Priority Queue in C++ Standard Template Library (STL)
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