Leetcode #968: Binary Tree Cameras
In this guide, we solve Leetcode #968 Binary Tree Cameras in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
You are given the root of a binary tree. We install cameras on the tree nodes where each camera at a node can monitor its parent, itself, and its immediate children.
Quick Facts
- Difficulty: Hard
- Premium: No
- Tags: Tree, Depth-First Search, Dynamic Programming, Binary Tree
Intuition
The problem breaks into overlapping subproblems, so caching results prevents exponential repetition.
A carefully chosen DP state captures exactly what we need to build the final answer.
Approach
Define the DP state and recurrence, then compute states in the correct order.
Optionally compress space once the recurrence is clear.
Steps:
- Choose a DP state definition.
- Write the recurrence and base cases.
- Compute states in the correct order.
Example
Input: root = [0,0,null,0,0]
Output: 1
Explanation: One camera is enough to monitor all nodes if placed as shown.
Python Solution
# 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 minCameraCover(self, root: Optional[TreeNode]) -> int:
def dfs(root):
if root is None:
return inf, 0, 0
la, lb, lc = dfs(root.left)
ra, rb, rc = dfs(root.right)
a = min(la, lb, lc) + min(ra, rb, rc) + 1
b = min(la + rb, lb + ra, la + ra)
c = lb + rb
return a, b, c
a, b, _ = dfs(root)
return min(a, b)
Complexity
The time complexity is , and the space complexity is , where is the number of nodes in the binary tree. The space complexity is , where is the number of nodes in the binary tree.
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.