📖 Scenario: You are working with a binary search tree (BST) that stores numbers in a way that smaller numbers go to the left and larger numbers go to the right. You want to find the kth smallest number in this tree, which means the number that would appear in position k if you listed all numbers in order.
🎯 Goal: Build a TypeScript program that creates a BST, sets a value for k, finds the kth smallest element in the BST using an in-order traversal, and prints the result.
📋 What You'll Learn
Create a BST with the exact nodes given
Set a variable k to the given value
Write a function kthSmallest that finds the kth smallest element using in-order traversal
Print the kth smallest element
💡 Why This Matters
🌍 Real World
Finding the kth smallest element is useful in databases, search engines, and ranking systems where you want to quickly find a specific order statistic.
💼 Career
Understanding BSTs and order statistics is important for software engineers working on efficient data retrieval, algorithm design, and coding interviews.
Progress0 / 4 steps
1
Create the BST nodes
Create a class called TreeNode with properties val, left, and right. Then create the BST with these exact nodes and connections: root with value 5, root.left with value 3, root.right with value 7, root.left.left with value 2, root.left.right with value 4, root.right.left with value 6, root.right.right with value 8.
DSA Typescript
Hint
Start by defining the TreeNode class with a constructor. Then create the root node and connect its left and right children as described.
2
Set the value of k
Create a variable called k and set it to 3.
DSA Typescript
Hint
Simply create a constant k and assign it the value 3.
3
Write the function to find kth smallest element
Write a function called kthSmallest that takes root of type TreeNode | null and k of type number. Use an in-order traversal to find and return the kth smallest element's value in the BST.
DSA Typescript
Hint
Use a helper function inorder to visit nodes in order. Keep a count of visited nodes. When count equals k, save the node's value and stop.
4
Print the kth smallest element
Write a console.log statement to print the result of calling kthSmallest(root, k).
DSA Typescript
Hint
Call kthSmallest(root, k) and print the result using console.log.
Practice
(1/5)
1. What does the "Kth Smallest Element in BST" problem ask you to find?
easy
A. The element that is the Kth smallest value in the Binary Search Tree
B. The largest element in the Binary Search Tree
C. The height of the Binary Search Tree
D. The number of nodes in the Binary Search Tree
Solution
Step 1: Understand the BST property
A Binary Search Tree (BST) stores values so that left child nodes are smaller and right child nodes are larger than the parent.
Step 2: Define the Kth smallest element
The Kth smallest element is the element that would appear in position K if all elements were sorted in ascending order.
Final Answer:
The element that is the Kth smallest value in the Binary Search Tree -> Option A
Quick Check:
Kth smallest means sorted order position K [OK]
Hint: Remember BST in-order traversal gives sorted order [OK]
Common Mistakes:
Confusing Kth smallest with largest element
Thinking it means tree height
Counting nodes instead of values
2. Which TypeScript function signature correctly represents a function to find the Kth smallest element in a BST node structure?
easy
A. function kthSmallest(k: number, root: TreeNode): void
B. function kthSmallest(root: TreeNode | null, k: number): number
C. function kthSmallest(root: TreeNode, k: string): string
D. function kthSmallest(root: TreeNode, k: number): TreeNode
Solution
Step 1: Check parameter types and order
The function should take the root node (which can be null) and a number k representing the position.
Step 2: Check return type
The function returns the value (number) of the Kth smallest element, not a node or void.
Final Answer:
function kthSmallest(root: TreeNode | null, k: number): number -> Option B
Quick Check:
Correct parameter types and return number [OK]
Hint: Root node first, k as number, return value number [OK]
Common Mistakes:
Swapping parameter order
Using wrong return type
Using string instead of number for k
3. Given the BST below and k = 3, what is the output of the function kthSmallest(root, 3)?
4. Consider this TypeScript code snippet to find the Kth smallest element in a BST:
function kthSmallest(root: TreeNode | null, k: number): number {
let count = 0;
let result = -1;
function inorder(node: TreeNode | null) {
if (!node) return;
inorder(node.left);
count++;
if (count === k) {
result = node.val;
return;
}
inorder(node.right);
}
inorder(root);
return result;
}
What is the main problem with this code?
medium
A. The function does not stop traversal after finding the Kth element
B. The count variable is not incremented correctly
C. The result variable is initialized incorrectly
D. The function does not handle null root
Solution
Step 1: Analyze traversal stopping condition
The code sets result when count equals k but does not stop further recursion, so it continues traversing unnecessarily.
Step 2: Understand impact of not stopping traversal
Without stopping, the function wastes time and may overwrite result if not careful.
Final Answer:
The function does not stop traversal after finding the Kth element -> Option A
Quick Check:
Traversal must stop after Kth element found [OK]
Hint: Stop recursion immediately after finding Kth element [OK]
Common Mistakes:
Assuming return stops all recursion
Not using a flag to stop traversal
Ignoring null root case
5. You want to find the Kth smallest element in a BST but the tree is very large and you need to optimize for multiple queries with different K values. Which approach is best?
hard
A. Perform in-order traversal each time for every K query
B. Use breadth-first search to find the Kth smallest element
C. Randomly pick nodes until Kth smallest is found
D. Store the in-order traversal result in an array once, then answer queries by indexing
Solution
Step 1: Consider repeated queries
Performing in-order traversal each time is costly for large trees and many queries.
Step 2: Use pre-processing for efficiency
Storing the sorted elements from one in-order traversal allows O(1) access for each Kth smallest query.
Step 3: Evaluate other options
Breadth-first search does not give sorted order; random picking is inefficient and unreliable.
Final Answer:
Store the in-order traversal result in an array once, then answer queries by indexing -> Option D
Quick Check:
Precompute once, query fast [OK]
Hint: Precompute sorted list once for fast multiple queries [OK]
Common Mistakes:
Recomputing traversal for each query
Using BFS which is unsorted
Random selection guessing
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