LeetCode 0222. Count Complete Tree Nodes Solution in Java, C++, Python & More | Explanation + Code

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0222. Count Complete Tree Nodes

Description

Given the root of a complete binary tree, return the number of the nodes in the tree.

According to Wikipedia, every level, except possibly the last, is completely filled in a complete binary tree, and all nodes in the last level are as far left as possible. It can have between 1 and 2h nodes inclusive at the last level h.

Design an algorithm that runs in less than O(n) time complexity.

 

Example 1:

Input: root = [1,2,3,4,5,6]
Output: 6

Example 2:

Input: root = []
Output: 0

Example 3:

Input: root = [1]
Output: 1

 

Constraints:

  • The number of nodes in the tree is in the range [0, 5 * 104].
  • 0 <= Node.val <= 5 * 104
  • The tree is guaranteed to be complete.

Solutions

Solution 1: Recursion

We recursively traverse the entire tree and count the number of nodes.

The time complexity is O(n), and the space complexity is O(n), where n is the number of nodes in the tree.

PythonJavaC++GoRustJavaScriptC#
# Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def countNodes(self, root: Optional[TreeNode]) -> int: if root is None: return 0 return 1 + self.countNodes(root.left) + self.countNodes(root.right)(code-box)

Solution 2: Binary Search

For this problem, we can also take advantage of the characteristics of a complete binary tree to design a faster algorithm.

Characteristics of a complete binary tree: leaf nodes can only appear on the bottom and second-to-bottom layers, and the leaf nodes on the bottom layer are concentrated on the left side of the tree. It should be noted that a full binary tree is definitely a complete binary tree, but a complete binary tree is not necessarily a full binary tree.

If the number of layers in a full binary tree is h, then the total number of nodes is 2^h - 1.

We first count the heights of the left and right subtrees of root, denoted as left and right.

  1. If left = right, it means that the left subtree is a full binary tree, so the total number of nodes in the left subtree is 2^{left} - 1. Plus the root node, it is 2^{left}. Then we recursively count the right subtree.
  2. If left > right, it means that the right subtree is a full binary tree, so the total number of nodes in the right subtree is 2^{right} - 1. Plus the root node, it is 2^{right}. Then we recursively count the left subtree.

The time complexity is O(log^2 n).

PythonJavaC++GoJavaScriptC#
# Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def countNodes(self, root: Optional[TreeNode]) -> int: def depth(root): d = 0 while root: d += 1 root = root.left return d if root is None: return 0 left, right = depth(root.left), depth(root.right) if left == right: return (1 << left) + self.countNodes(root.right) return (1 << right) + self.countNodes(root.left)(code-box)

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