572. Subtree of Another Tree
Problem Description
Given the roots of two binary trees root and subRoot, return true if there is a subtree of root with the same structure and node values of subRoot and false otherwise.
A subtree of a binary tree tree is a tree that consists of a node in tree and all of this node's descendants. The tree tree could also be considered as a subtree of itself.
Example 1:
Input: root = [3,4,5,1,2], subRoot = [4,1,2]
Output: true
Example 2:
Input: root = [3,4,5,1,2,null,null,null,null,0], subRoot = [4,1,2]
Output: false
Constraints:
- The number of nodes in the
roottree is in the range[1, 2000] - The number of nodes in the
subRoottree is in the range[1, 1000] -10⁴ <= root.val <= 10⁴-10⁴ <= subRoot.val <= 10⁴
Solution
Python Solution
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
class Solution:
def isSubtree(self, root: Optional[TreeNode], subRoot: Optional[TreeNode]) -> bool:
if not root:
return False
if self.isSameTree(root, subRoot):
return True
return self.isSubtree(root.left, subRoot) or self.isSubtree(root.right, subRoot)
def isSameTree(self, p: Optional[TreeNode], q: Optional[TreeNode]) -> bool:
if not p and not q:
return True
if not p or not q:
return False
return (p.val == q.val and
self.isSameTree(p.left, q.left) and
self.isSameTree(p.right, q.right))
Time Complexity: O(m * n)
Where m and n are the number of nodes in root and subRoot trees respectively.
Space Complexity: O(h)
Where h is the height of the root tree, for the recursion stack.
Java Solution
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode() {}
* TreeNode(int val) { this.val = val; }
* TreeNode(int val, TreeNode left, TreeNode right) {
* this.val = val;
* this.left = left;
* this.right = right;
* }
* }
*/
class Solution {
public boolean isSubtree(TreeNode root, TreeNode subRoot) {
if (root == null) {
return false;
}
if (isSameTree(root, subRoot)) {
return true;
}
return isSubtree(root.left, subRoot) || isSubtree(root.right, subRoot);
}
private boolean isSameTree(TreeNode p, TreeNode q) {
if (p == null && q == null) {
return true;
}
if (p == null || q == null) {
return false;
}
return p.val == q.val &&
isSameTree(p.left, q.left) &&
isSameTree(p.right, q.right);
}
}
Time Complexity: O(m * n)
Where m and n are the number of nodes in root and subRoot trees respectively.
Space Complexity: O(h)
Where h is the height of the root tree, for the recursion stack.
C++ Solution
/**
* Definition for a binary tree node.
* struct TreeNode {
* int val;
* TreeNode *left;
* TreeNode *right;
* TreeNode() : val(0), left(nullptr), right(nullptr) {}
* TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
* TreeNode(int x, TreeNode *left, TreeNode *right) : val(x), left(left), right(right) {}
* };
*/
class Solution {
public:
bool isSubtree(TreeNode* root, TreeNode* subRoot) {
if (!root) {
return false;
}
if (isSameTree(root, subRoot)) {
return true;
}
return isSubtree(root->left, subRoot) || isSubtree(root->right, subRoot);
}
private:
bool isSameTree(TreeNode* p, TreeNode* q) {
if (!p && !q) {
return true;
}
if (!p || !q) {
return false;
}
return p->val == q->val &&
isSameTree(p->left, q->left) &&
isSameTree(p->right, q->right);
}
};
Time Complexity: O(m * n)
Where m and n are the number of nodes in root and subRoot trees respectively.
Space Complexity: O(h)
Where h is the height of the root tree, for the recursion stack.
JavaScript Solution
/**
* Definition for a binary tree node.
* function TreeNode(val, left, right) {
* this.val = (val===undefined ? 0 : val)
* this.left = (left===undefined ? null : left)
* this.right = (right===undefined ? null : right)
* }
*/
/**
* @param {TreeNode} root
* @param {TreeNode} subRoot
* @return {boolean}
*/
var isSubtree = function(root, subRoot) {
if (!root) {
return false;
}
if (isSameTree(root, subRoot)) {
return true;
}
return isSubtree(root.left, subRoot) || isSubtree(root.right, subRoot);
};
function isSameTree(p, q) {
if (!p && !q) {
return true;
}
if (!p || !q) {
return false;
}
return p.val === q.val &&
isSameTree(p.left, q.left) &&
isSameTree(p.right, q.right);
}
Time Complexity: O(m * n)
Where m and n are the number of nodes in root and subRoot trees respectively.
Space Complexity: O(h)
Where h is the height of the root tree, for the recursion stack.
C# Solution
/**
* Definition for a binary tree node.
* public class TreeNode {
* public int val;
* public TreeNode left;
* public TreeNode right;
* public TreeNode(int val=0, TreeNode left=null, TreeNode right=null) {
* this.val = val;
* this.left = left;
* this.right = right;
* }
* }
*/
public class Solution {
public bool IsSubtree(TreeNode root, TreeNode subRoot) {
if (root == null) {
return false;
}
if (IsSameTree(root, subRoot)) {
return true;
}
return IsSubtree(root.left, subRoot) || IsSubtree(root.right, subRoot);
}
private bool IsSameTree(TreeNode p, TreeNode q) {
if (p == null && q == null) {
return true;
}
if (p == null || q == null) {
return false;
}
return p.val == q.val &&
IsSameTree(p.left, q.left) &&
IsSameTree(p.right, q.right);
}
}
Time Complexity: O(m * n)
Where m and n are the number of nodes in root and subRoot trees respectively.
Space Complexity: O(h)
Where h is the height of the root tree, for the recursion stack.
Approach Explanation
The solution uses recursive tree traversal and comparison:
- Key Insights:
- Tree traversal
- Recursive comparison
- Subtree matching
- Base case handling
- Algorithm Steps:
- Check current node
- Compare trees
- Traverse children
- Combine results
Implementation Details:
- Null checks
- Value comparison
- Recursive calls
- Boolean logic
Optimization Insights:
- Early termination
- Stack management
- Memory efficiency
- Base case handling
Edge Cases:
- Empty trees
- Single node
- Identical trees
- Multiple matches