Kth Smallest Element in BST in DSA C - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Binary Search Tree (BST)?

A BST is a tree where each node has at most two children. The left child's value is less than the parent's value, and the right child's value is greater. This helps in fast searching and sorting.

beginner

What does 'Kth smallest element in BST' mean?

It means finding the element that would appear in position K if all elements were sorted from smallest to largest.

beginner

Which traversal method helps find the Kth smallest element in a BST?

Inorder traversal visits nodes in ascending order in a BST, so it helps find the Kth smallest element by counting nodes visited.

intermediate

What is the time complexity of finding the Kth smallest element in a BST using inorder traversal?

The time complexity is O(H + K), where H is the height of the tree. This is because we traverse down to the leftmost node and then count K nodes.

advanced

How can you optimize finding the Kth smallest element if the BST is frequently queried?

You can store the count of nodes in each subtree at every node. This allows skipping entire subtrees and finding the Kth smallest in O(H) time.

Which traversal order visits BST nodes in ascending order?

A Preorder

B Postorder

C Inorder

D Level order

Inorder traversal visits left child, then node, then right child, which results in ascending order for BST.

What is the first step to find the Kth smallest element in a BST?

A Perform inorder traversal

B Perform preorder traversal

C Perform postorder traversal

D Count total nodes

Inorder traversal visits nodes in ascending order, so it is used to find the Kth smallest element.

If K=1, what element does the Kth smallest in BST represent?

A Median element

B Largest element

C Root element

D Smallest element

The 1st smallest element is the smallest element in the BST.

What is the worst-case height H of a BST?

A Square root of N

B Number of nodes (N)

C Constant 1

D Logarithm of N

In worst case, BST can be skewed and height equals number of nodes.

How can storing subtree node counts help in finding the Kth smallest element?

A Skip entire subtrees to reach Kth element faster

B Avoid traversing the tree

C Sort the tree nodes

D Convert BST to array

Knowing subtree sizes lets you decide if Kth element is in left subtree, current node, or right subtree, skipping unnecessary nodes.

Explain how inorder traversal helps find the Kth smallest element in a BST.

Think about the order nodes are visited in inorder traversal.

Describe one optimization to improve repeated queries for the Kth smallest element in a BST.

Consider extra information stored at each node.

Practice

1. What does the term kth smallest element in a BST mean?

easy

A. The element that appears in the kth position when BST elements are sorted in ascending order

B. The element with the kth largest value in the BST

C. The element at the kth level of the BST

D. The element with the kth highest frequency in the BST

Solution

1. Step 1: Understand BST property

   A Binary Search Tree (BST) stores elements so that left subtree has smaller values and right subtree has larger values.

2. Step 2: Define kth smallest element

   The kth smallest element is the one that appears in the kth position when all elements are sorted in ascending order.

3. Final Answer:

   The element that appears in the kth position when BST elements are sorted in ascending order -> Option A

4. Quick Check:

   kth smallest = kth in sorted order [OK]

Hint: Think of inorder traversal to get sorted order [OK]

Common Mistakes:

• Confusing kth smallest with kth largest
• Thinking kth smallest means kth level node
• Assuming frequency matters

2. Which of the following C function signatures is correct to find the kth smallest element in a BST node structure struct Node?

easy

A. void kthSmallest(int root, int k);

B. int kthSmallest(struct Node root, int k);

C. int kthSmallest(struct Node* root, int k);

D. int kthSmallest(struct Node* root);

Solution

1. Step 1: Understand function parameters

   The function needs the root pointer to the BST and the integer k to find kth smallest.

2. Step 2: Check parameter types

   Passing struct Node* for root and int for k is correct. Return type should be int for the element value.

3. Final Answer:

   int kthSmallest(struct Node* root, int k); -> Option C

4. Quick Check:

   Correct signature includes pointer and k parameter [OK]

Hint: Use pointer for tree root and int for k [OK]

Common Mistakes:

• Passing root by value instead of pointer
• Missing k parameter
• Wrong return type or missing return

3. Given the BST below and k = 3, what is the output of the function kthSmallest(root, 3)?

      5
     / \
    3   7
   / \   \
  2   4   8

medium

A. 5

B. 4

C. 3

D. 7

Solution

1. Step 1: Perform inorder traversal

   Inorder traversal of BST visits nodes in ascending order: 2, 3, 4, 5, 7, 8.

2. Step 2: Identify 3rd element in traversal

   The 3rd element is 4.

3. Final Answer:

   4 -> Option B

4. Quick Check:

   Inorder 3rd element = 4 [OK]

Hint: Inorder traversal gives sorted order; pick kth element [OK]

Common Mistakes:

• Counting nodes incorrectly in traversal
• Confusing preorder or postorder with inorder
• Choosing root or other node instead of kth

4. Consider this buggy C code snippet to find kth smallest element in BST:

int count = 0;
int kthSmallest(struct Node* root, int k) {
    if (!root) return -1;
    int left = kthSmallest(root->left, k);
    if (left != -1) return left;
    count++;
    if (count == k) return root->data;
    return kthSmallest(root->right, k);
}

What is the main issue with this code?

medium

A. Global variable 'count' causes incorrect results on multiple calls

B. Function does not handle empty tree

C. Returns -1 for valid kth element

D. Does not traverse right subtree

Solution

1. Step 1: Analyze use of 'count'

   The variable 'count' is global and not reset between calls, causing wrong counts if function called multiple times.

2. Step 2: Understand impact on results

   Because 'count' is not reset, subsequent calls may return wrong kth smallest element or fail.

3. Final Answer:

   Global variable 'count' causes incorrect results on multiple calls -> Option A

4. Quick Check:

   Global count not reset breaks repeated calls [OK]

Hint: Avoid global counters; pass as function argument [OK]

Common Mistakes:

• Ignoring global variable side effects
• Assuming function works for multiple calls
• Not resetting count before each call

5. You have a BST with nodes containing duplicate values. How would you modify the standard kth smallest element algorithm to correctly find the kth smallest unique element?

hard

A. Use preorder traversal instead of inorder

B. Count all nodes including duplicates normally

C. Remove duplicates from BST before traversal

D. Use inorder traversal and skip duplicates by comparing with previous visited value

Solution

1. Step 1: Understand duplicates in BST

   Duplicates appear as multiple nodes with same value; inorder traversal visits them in sorted order including duplicates.

2. Step 2: Modify traversal to skip duplicates

   Track previous visited value during inorder traversal; only increment count when current value differs from previous.

3. Step 3: Find kth unique element

   Increment count only for unique values; when count equals k, return current node's value.

4. Final Answer:

   Use inorder traversal and skip duplicates by comparing with previous visited value -> Option D

5. Quick Check:

   Skip duplicates by comparing previous value [OK]

Hint: Track previous value to count unique elements [OK]

Common Mistakes:

• Counting duplicates as separate elements
• Using preorder traversal which is not sorted
• Trying to remove duplicates instead of skipping