This approach involves using a recursive function to traverse the root tree and checking for a matching subtree starting from every node. A helper function can be used to check if trees rooted at specific nodes are identical.
Time Complexity: O(N*M), where N is the number of nodes in the root tree and M is the number of nodes in subRoot tree.
Space Complexity: O(min(N, M)), depending on the tree height during recursion.
1class Solution {
2 public boolean isSubtree(TreeNode root, TreeNode subRoot) {
3 if (root == null) return false;
4 if (isIdentical(root, subRoot)) return true;
5 return isSubtree(root.left, subRoot) || isSubtree(root.right, subRoot);
6 }
7 public boolean isIdentical(TreeNode s, TreeNode t) {
8 if (s == null && t == null) return true;
9 if (s == null || t == null) return false;
10 return s.val == t.val && isIdentical(s.left, t.left) && isIdentical(s.right, t.right);
11 }
12}
This Java solution uses recursion to traverse through each node of the main tree and checks if starting from that node, the two trees are identical using isIdentical
.
Another approach to solving this problem is by converting the trees into their preorder traversal strings with marker symbols for nulls, and then checking if the subRoot string is a substring of the root string.
Time Complexity: O(N + M + N*M), where N and M are the sizes of the trees.
Space Complexity: O(N + M), for the preorder traversal strings.
1class Solution:
2 def isSubtree(self, root, subRoot):
3 return self.preorder(root).find(self.preorder(subRoot)) != -1
4
5 def preorder(self, node):
6 if not node:
7 return "null "
8 return str(node.val) + " " + self.preorder(node.left) + self.preorder(node.right)
The Python solution uses preorder traversal to obtain a string representation of both trees and checks the inclusion of subRoot's string representation within root's string.