Given the root of a binary tree, return its maximum depth.
A binary tree’s maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.
Example 1:

Input: root = [3,9,20,null,null,15,7]
Output: 3
Example 2:
Input: root = [1,null,2] **Output:** 2
Constraints:
- The number of nodes in the tree is in the range
[0, 104]. -100 <= Node.val <= 100
Approach - BFS
- We use queue which uses linked lists, we start by adding the root node then go BFS
- We check how long it takes to reach the end
Time: O(n) Space: O(n)
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode() {}
* TreeNode(int val) { this.val = val; }
* TreeNode(int val, TreeNode left, TreeNode right) {
* this.val = val;
* this.left = left;
* this.right = right;
* }
* }
*/
class Solution {
public int maxDepth(TreeNode root) {
Queue<TreeNode> q = new LinkedList<>();
if (root != null) q.add(root); //tp kickstart
int l = 0;
while (!q.isEmpty()) {
int size = q.size(); //use this instead direclty in for loop because the queue size will be altered inside the loop
for (int i = 0; i < size; i++) {
TreeNode n = q.poll(); // npt only removes but returns
if (n.left != null) q.add(n.left);
if (n.right != null) q.add(n.right);
}
l++;
}
return l;
}
}Approach - Recursion
- Time complexity: O(n)
- Space complexity: O(h)
- Best Case (balanced tree): O(log(n))
- Worst Case (degenerate tree): O(n)
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode() {}
* TreeNode(int val) { this.val = val; }
* TreeNode(int val, TreeNode left, TreeNode right) {
* this.val = val;
* this.left = left;
* this.right = right;
* }
* }
*/
class Solution {
public int maxDepth(TreeNode root) {
if (root == null)
return 0;
return 1 + Math.max(maxDepth(root.left), maxDepth(root.right));
}
}