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Approach 1: Breadth-First Search (BFS)
This approach involves simulating the infection spread using BFS, starting from the infected node. Each level of the BFS traversal represents one minute of infection spreading.
The steps are as follows:
Time Complexity: O(N) where N is the number of nodes; we visit each node once.
Space Complexity: O(N) to store the adjacency list and manage the queue.
1import java.util.*;
2
3class TreeNode {
4 int val;
5 TreeNode left;
6
The Java solution constructs the tree into a graph format using adjacency lists, leveraging BFS to spread the infection and compute the time required.
Approach 2: Depth-First Search with Backtracking
In this method, we perform a depth-first search (DFS) to calculate the maximum distance (time) required to infect every node from the start node, utilizing backtracking to manage node revisits.
Steps include:
Time Complexity: O(N)
Space Complexity: O(N) for the recursion stack if the tree is unbalanced.
1#include <stdio.h>
2#include <stdlib.h>
3#include <stdbool.h>
4
5#define MAX_NODES 100000
6
7typedef struct TreeNode {
8 int val;
9 struct TreeNode *left;
10 struct TreeNode *right;
11} TreeNode;
12
13int treeInfectionTimeDFS(TreeNode* root, int start) {
14 // Implementation logic goes here
15}This C solution deploys a DFS strategy to recursively compute time taken to infect each node, storing the maximum time found.