Is Binary Tree Cameras easy or hard?

Binary Tree Cameras is categorized as a hard problem because it requires recognizing the correct greedy state transitions during DFS. Once the three-state model is understood, the implementation becomes relatively compact.

How to solve Binary Tree Cameras in O(n)?

Perform a postorder DFS and assign states to each node: 0 for not covered, 1 for a camera placed, and 2 for covered. If any child is uncovered, place a camera at the current node. If any child has a camera, the node becomes covered. Otherwise it remains uncovered so the parent can handle it.

Binary Tree Cameras Python or Java solution

Both Python and Java implementations follow the same DFS strategy. A recursive function returns the coverage state of each node and increments a camera counter when a camera must be placed. The algorithm processes every node once, giving O(n) time complexity.

What is the best approach for Binary Tree Cameras?

The greedy depth-first search approach is the most efficient and commonly expected solution. Each node returns one of three states: uncovered, covered, or has a camera. Cameras are placed only when a child is uncovered, which guarantees minimal placement. This solution runs in O(n) time and uses O(h) recursion space.

What data structure is used in Binary Tree Cameras?

The problem operates on a binary tree and is typically solved using depth-first search recursion. Some solutions also model the problem using dynamic programming states stored per node in the tree.

What is the time complexity of Binary Tree Cameras?

The optimal solution runs in O(n) time because every node in the binary tree is visited exactly once during the DFS traversal. The space complexity is O(h), where h is the height of the tree, due to recursion stack usage.

Is Binary Tree Cameras asked at Google Amazon or Meta?

Binary Tree Cameras is a classic tree greedy problem that appears in interview preparation lists for companies like Google, Amazon, and Meta. It tests understanding of DFS traversal, tree state management, and greedy placement strategies.

Description Solution Video 22:17

968. Binary Tree Cameras

Hard48.3% acceptance14 companies

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.

Return the minimum number of cameras needed to monitor all nodes of the tree.

Example 1:

Input: root = [0,0,null,0,0]
Output: 1
Explanation: One camera is enough to monitor all nodes if placed as shown.

Example 2:

Input: root = [0,0,null,0,null,0,null,null,0]
Output: 2
Explanation: At least two cameras are needed to monitor all nodes of the tree. The above image shows one of the valid configurations of camera placement.

Constraints: