cpp-flashcards/org/study_deck_02/dsa/trees/0230-kth-smallest-element-in-a-bst.org

#+ANKI_DECK: study_deck_02
* TODO 0230. Kth Smallest Element In a Bst :medium:
:PROPERTIES:
:NEETCODE: [[file:../../roadmap.org::*0230. Kth Smallest Element In a Bst][0230. Kth Smallest Element In a Bst]]
:END:

Given the ~root~ of a binary search tree, and an integer ~k~, return /the/ ~k^{th}~ /smallest value (*1-indexed*) of all the values of the nodes in the tree/.

*Example 1:*


#+begin_src
Input: root = [3,1,4,null,2], k = 1
Output: 1
#+end_src


*Example 2:*


#+begin_src
Input: root = [5,3,6,2,4,null,null,1], k = 3
Output: 3
#+end_src


*Constraints:*

 - The number of nodes in the tree is ~n~.

 - ~1 <= k <= n <= 10^{4}~

 - ~0 <= Node.val <= 10^{4}~

*Follow up:* If the BST is modified often (i.e., we can do insert and delete operations) and you need to find the kth smallest frequently, how would you optimize?

** TODO Approach
Write your approach here.

** TODO Python
#+begin_src python :lc-problem 230 :lc-lang python3
# 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 kthSmallest(self, root: Optional[TreeNode], k: int) -> int:
#+end_src

** TODO C++
#+begin_src cpp :lc-problem 230
/**
 * 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:
    int kthSmallest(TreeNode* root, int k) {
        
    }
};
#+end_src