Kth Smallest Element in BST in DSA C - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Kth Smallest Element Function

What is the output of the following C code that finds the 3rd smallest element in the given BST?

DSA C

typedef struct Node {
    int val;
    struct Node* left;
    struct Node* right;
} Node;

int count = 0;
int result = -1;

void kthSmallestUtil(Node* root, int k) {
    if (!root) return;
    kthSmallestUtil(root->left, k);
    count++;
    if (count == k) {
        result = root->val;
        return;
    }
    kthSmallestUtil(root->right, k);
}

int kthSmallest(Node* root, int k) {
    count = 0;
    result = -1;
    kthSmallestUtil(root, k);
    return result;
}

// BST structure:
//       5
//      / \
//     3   7
//    / \   \
//   2   4   8

// Call: kthSmallest(root, 3);

A 5

B 4

C 3

D 7

💡 Hint

Remember that inorder traversal of BST gives sorted order.

The inorder traversal visits nodes in ascending order: 2, 3, 4, 5, 7, 8. The 3rd smallest is 4.

🧠 Conceptual

intermediate

Understanding Kth Smallest Element in BST

Which property of a Binary Search Tree (BST) allows us to find the kth smallest element efficiently using inorder traversal?

A BST nodes are stored in a heap structure

B BST is always a balanced tree

C BST nodes have pointers to their parents

D Inorder traversal of BST visits nodes in ascending order

💡 Hint

Think about the order in which nodes are visited in inorder traversal.

Inorder traversal of BST visits nodes from smallest to largest, which helps find the kth smallest element.

🔧 Debug

advanced

Identify the Bug in Kth Smallest Element Code

What error will occur when running this code to find the kth smallest element in a BST?

DSA C

int kthSmallestUtil(Node* root, int k, int* count) {
    if (!root) return -1;
    int left = kthSmallestUtil(root->left, k, count);
    if (left != -1) return left;
    (*count)++;
    if (*count == k) return root->val;
    return kthSmallestUtil(root->right, k, count);
}

int kthSmallest(Node* root, int k) {
    int count = 0;
    return kthSmallestUtil(root, k, &count);
}

// Suppose k is larger than number of nodes in BST.

A Returns -1 indicating kth element not found

B Causes segmentation fault due to null pointer dereference

C Returns 0 as default value

D Enters infinite recursion

💡 Hint

What happens if k is bigger than total nodes?

If k is larger than number of nodes, function returns -1 to indicate kth element not found.

❓ Predict Output

advanced

Output of Iterative Kth Smallest Element Code

What is the output of this iterative C code to find the 2nd smallest element in the BST below?

DSA C

#include <stdio.h>
#include <stdlib.h>

typedef struct Node {
    int val;
    struct Node* left;
    struct Node* right;
} Node;

typedef struct Stack {
    Node* data[100];
    int top;
} Stack;

void push(Stack* s, Node* node) {
    s->data[++(s->top)] = node;
}

Node* pop(Stack* s) {
    return s->data[(s->top)--];
}

int kthSmallest(Node* root, int k) {
    Stack s = {.top = -1};
    Node* curr = root;
    int count = 0;
    while (curr || s.top != -1) {
        while (curr) {
            push(&s, curr);
            curr = curr->left;
        }
        curr = pop(&s);
        count++;
        if (count == k) return curr->val;
        curr = curr->right;
    }
    return -1;
}

// BST:
//      6
//     / \
//    3   8
//   / \   \
//  2   4   9

// Call: kthSmallest(root, 2);

A 3

B 4

C 2

D 6

💡 Hint

Iterative inorder traversal visits nodes in ascending order.

Inorder traversal order: 2, 3, 4, 6, 8, 9. The 2nd smallest is 3.

🚀 Application

expert

Kth Smallest Element with Augmented BST

In an augmented BST where each node stores the count of nodes in its left subtree, how can you find the kth smallest element efficiently?

A Use postorder traversal to find kth smallest element

B Always traverse entire tree inorder and count nodes until kth is found

C Traverse left subtree if k is less or equal to left count; else go right with k reduced by left count + 1

D Perform level order traversal and pick kth element visited

💡 Hint

Use the stored counts to skip subtrees.

Using left subtree counts, we decide whether kth smallest is in left subtree, current node, or right subtree, reducing search time.

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