/**
Given a binary search tree, write a function kthSmallest to find the kth smallest element in it.
Note:
You may assume k is always valid, 1 ≤ k ≤ BST's total elements.
Example 1:
Input: root = [3,1,4,null,2], k = 1
3
/ \
1 4
\
2
Output: 1
Example 2:
Input: root = [5,3,6,2,4,null,null,1], k = 3
5
/ \
3 6
/ \
2 4
/
1
Output: 3
Follow up:
What if the BST is modified (insert/delete operations) often and you need to find the kth smallest frequently? How would you optimize the kthSmallest routine?
*/
public class KthSmallestInBST{
public int kthSmallest(TreeNode root, int k) {
int count = countNodes(root.left);
if (k <= count) {
return kthSmallest(root.left, k);
} else if (k > count + 1) {
return kthSmallest(root.right, k-1-count); // 1 is counted as current node
}
return root.val;
}
public int countNodes(TreeNode n) {
if (n == null) return 0;
return 1 + countNodes(n.left) + countNodes(n.right);
}
}
Given a binary search tree, write a function kthSmallest to find the kth smallest element in it.
Note:
You may assume k is always valid, 1 ≤ k ≤ BST's total elements.
Example 1:
Input: root = [3,1,4,null,2], k = 1
3
/ \
1 4
\
2
Output: 1
Example 2:
Input: root = [5,3,6,2,4,null,null,1], k = 3
5
/ \
3 6
/ \
2 4
/
1
Output: 3
Follow up:
What if the BST is modified (insert/delete operations) often and you need to find the kth smallest frequently? How would you optimize the kthSmallest routine?
*/
public class KthSmallestInBST{
public int kthSmallest(TreeNode root, int k) {
int count = countNodes(root.left);
if (k <= count) {
return kthSmallest(root.left, k);
} else if (k > count + 1) {
return kthSmallest(root.right, k-1-count); // 1 is counted as current node
}
return root.val;
}
public int countNodes(TreeNode n) {
if (n == null) return 0;
return 1 + countNodes(n.left) + countNodes(n.right);
}
}
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