Sponsored
Sponsored
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 <iostream>
2#include <queue>
3using namespace std;
4
5struct TreeNode {
6 int val;
7 TreeNode *left;
8 TreeNode *right;
9 TreeNode(int x) : val(x), left(NULL), right(NULL) {}
10};
11
12TreeNode* replaceWithCousinsSum(TreeNode* root) {
13 if (!root) return root;
14 // Implement BFS and update root
15 return root;
16}
17
18int main() {
19 TreeNode* root = new TreeNode(5);
20 root->left = new TreeNode(4);
21 root->right = new TreeNode(9);
22 root->left->left = new TreeNode(1);
23 root->left->right = new TreeNode(10);
24 root->right->right = new TreeNode(7);
25 root = replaceWithCousinsSum(root);
26 return 0;
27}In this C++ solution, we utilize a queue to perform a breadth-first search. Each node is processed to calculate the sum of its cousins' values by accessing nodes at the same depth with different parent nodes.
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
This Java solution applies a DFS strategy with a hash map to efficiently track nodes at each depth level in order to calculate the sums of cousin values for tree node changes.