
In a given binary tree, the task is to identify nodes which are considered "good". A "good" node is defined as one where no ancestor (or no node in the path from the root to the node itself) has a value greater than the node's value. Essentially, for a node to qualify as "good", during the traversal from the root to this node, this node should be the highest value encountered or should at least tie with the highest. The problem's goal is to count and return how many such "good" nodes exist in the binary tree.
Input:
Output:
Explanation:
Input:
Output:
Explanation:
Input:
Output:
Explanation:
[1, 10^5].[-10^4, 10^4].The basic approach to find the "good" nodes relies on traversal techniques (DFS or BFS) to explore each node and compare its maximum ancestors’ values along the path. Here is a systematic breakdown of how one can approach this:
Initiate a Depth First Search traversal from the root. While traversing:
If the current node’s value is greater than or equal to the recorded maximum for that particular path, it is considered a "good" node.
Continue to traverse all branches of the tree:
Upon completing the traversal of all nodes, the count will reflect the total number of "good" nodes in the binary tree.
Example Walkthroughs:
This approach efficiently allows identification of "good" nodes and adheres to the constraints provided, handling varying sizes and node values of the binary tree efficiently.
In the given Java solution for counting good nodes in a binary tree, a NodePair class encapsulates a tree node and the current maximum value observed along the path from the root to that node. This approach assists in determining if a node is considered "good." A node is defined as good if its value is greater than or equal to the highest value observed along the path from the root node to that node.
The process begins with initializing a count for good nodes and setting up a queue to manage nodes during breadth-first traversal. The root node, paired with the smallest possible integer (representing the minimum value initially), is added to this queue.
Throughout the traversal:
Nodes are dequeued from nodeQueue, and each node's value is compared with currentMax to decide if it is a good node. If the condition holds true, the good node count is incremented.
If a right child exists, it is added to the queue with a currentMax value that is the maximum between the current node's value and the inherited currentMax.
The same procedure follows for the left child.
The solution efficiently tracks and updates the path maximum for each node traversed, ensuring that by the end of the traversal, the total number of good nodes is determined and returned. This approach leverages a breadth-first search strategy, ensuring that all nodes in the tree are checked in a level-order manner.
0 Comments
Be the first to comment and share your perspective with the community.