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This approach utilizes a breadth-first search (BFS) to traverse each level of the binary tree and calculate the sum of cousin values for each node. We maintain a queue to process each level separately and keep track of parent nodes to ensure calculations of cousins are accurate. This allows us to update the tree with the required values.
Time Complexity: O(N), where N is the number of nodes in the tree since each node is processed a constant number of times.
Space Complexity: O(W), where W is the maximum width of the tree (number of nodes at the widest level) due to the queue.
1#include <stdio.h>
2#include <stdlib.h>
3
4struct TreeNode {
5 int val;
6 struct TreeNode *left;
7 struct TreeNode *right;
8};
9
10struct TreeNode* createNode(int val) {
11 struct TreeNode* node = (struct TreeNode*)malloc(sizeof(struct TreeNode));
12 node->val = val;
13 node->left = node->right = NULL;
14 return node;
15}
16
17void modifyTree(struct TreeNode* root) {
18 if (!root) return;
19 // Implement BFS to modify the tree
20 // Placeholder for the actual logic
21}
22
23int main() {
24 struct TreeNode* root = createNode(5);
25 root->left = createNode(4);
26 root->right = createNode(9);
27 root->left->left = createNode(1);
28 root->left->right = createNode(10);
29 root->right->right = createNode(7);
30 modifyTree(root);
31 return 0;
32}This solution uses a typical BFS approach to traverse the tree and calculate the value of cousins for each node. We can modify this to calculate the cousin sum and then update each node in the binary tree. For simplicity, the function `modifyTree` is a placeholder where we will implement the logic.
This approach leverages a depth-first search (DFS) strategy in combination with a hash map to keep track of nodes and their parents at each depth level. This allows easy computation of cousin sums to modify tree node values.
Time Complexity: O(N)
Space Complexity: O(H), where H is the height of the tree.
1
The Python implementation uses depth-first search (DFS) with a dictionary to correlate nodes to their respective depth levels, computing cousin sums for tree values, which allows for efficient node updates.