Why BST Find Maximum Element in DSA C?

The Big Idea

What if you could find the biggest item instantly without searching everything?

The Scenario

Imagine you have a messy pile of books with no order. You want to find the thickest book, but you have to check each one by hand, flipping through all of them.

The Problem

Looking through every book one by one takes a lot of time and effort. You might lose track or miss the thickest book because the pile is unorganized and large.

The Solution

A Binary Search Tree (BST) organizes books by thickness so the thickest book is always at one end. To find it, you just follow the path to the rightmost book, saving time and effort.

Before vs After

✗ Before

int findMax(int arr[], int size) {
    int max = arr[0];
    for (int i = 1; i < size; i++) {
        if (arr[i] > max) max = arr[i];
    }
    return max;
}

✓ After

int findMaxInBST(Node* root) {
    Node* current = root;
    while (current->right != NULL) {
        current = current->right;
    }
    return current->data;
}

What It Enables

This lets you quickly find the largest value in a sorted structure without checking every element.

Real Life Example

Finding the highest score in a leaderboard where scores are stored in a BST, so you just go to the rightmost node to get the top score instantly.

Key Takeaways

Manual search is slow and error-prone for large, unordered data.

BST organizes data so the maximum is always at the rightmost node.

Finding max in BST is fast by following right children only.

Practice

1. In a Binary Search Tree (BST), where is the maximum element always located?

easy

A. At any leaf node

B. At the leftmost node

C. At the rightmost node

D. At the root node

Solution

1. Step 1: Understand BST property

   In a BST, left child nodes have smaller values and right child nodes have larger values than their parent.

2. Step 2: Locate maximum element

   The maximum element is the rightmost node because it has no right child and is greater than all other nodes.

3. Final Answer:

   At the rightmost node -> Option C

4. Quick Check:

   Maximum = rightmost node [OK]

Hint: Maximum is always the rightmost node in BST [OK]

Common Mistakes:

• Confusing maximum with root node
• Thinking maximum is at leftmost node
• Assuming maximum can be any leaf

2. Which of the following C code snippets correctly finds the maximum element in a BST?

easy

A. while(root->left != NULL) root = root->left; return root->data;

B. while(root->right != NULL) root = root->right; return root->data;

C. if(root == NULL) return INT_MIN; return root->data;

D. return root->data;

Solution

1. Step 1: Analyze code logic

   while(root->right != NULL) root = root->right; return root->data; moves right until no right child exists, which is correct for max in BST.

2. Step 2: Check other options

   while(root->left != NULL) root = root->left; return root->data; moves left (minimum), C returns root data without traversal, D returns root data directly.

3. Final Answer:

   while(root->right != NULL) root = root->right; return root->data; -> Option B

4. Quick Check:

   Traverse rightmost node for max [OK]

Hint: Traverse right child until NULL to find max [OK]

Common Mistakes:

• Traversing left child instead of right
• Returning root data without traversal
• Not checking for NULL pointers

3. What will be the output of the following code snippet that finds the maximum element in a BST?

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

int findMax(Node* root) {
  while(root->right != NULL) {
    root = root->right;
  }
  return root->data;
}

// BST structure:
//       10
//      /  \
//     5    20
//         /  \
//        15   30

int main() {
  // Assume BST is created as above
  printf("%d", findMax(root));
  return 0;
}

medium

A. 30

B. 20

C. 15

D. 10

Solution

1. Step 1: Understand BST structure

   The rightmost node is 30, which is the maximum element.

2. Step 2: Trace findMax function

   The function moves right from root (10) to 20, then to 30, stops as 30->right is NULL, returns 30.

3. Final Answer:

   30 -> Option A

4. Quick Check:

   Max element = 30 [OK]

Hint: Max is rightmost node: 10 -> 20 -> 30 [OK]

Common Mistakes:

• Returning root data without traversal
• Confusing max with root or left child
• Not following right pointers correctly

4. Identify the error in the following C function that is supposed to find the maximum element in a BST:

int findMax(Node* root) {
  if(root == NULL) return -1;
  while(root->left != NULL) {
    root = root->left;
  }
  return root->data;
}

medium

A. It returns -1 for empty tree instead of INT_MIN

B. It should use recursion instead of loop

C. It does not check if root is NULL before accessing data

D. It traverses left instead of right to find maximum

Solution

1. Step 1: Analyze traversal direction

   The function moves left to find max, but max is at rightmost node in BST.

2. Step 2: Check other issues

   Returning -1 is acceptable for empty tree; checking root NULL is done; recursion is optional.

3. Final Answer:

   It traverses left instead of right to find maximum -> Option D

4. Quick Check:

   Max is rightmost, not leftmost [OK]

Hint: Max element is at rightmost, not leftmost node [OK]

Common Mistakes:

• Confusing left and right child traversal
• Ignoring NULL checks
• Thinking recursion is mandatory

5. Given a BST where some nodes have duplicate values, which approach correctly finds the maximum element considering duplicates are allowed on the right subtree?

int findMax(Node* root) {
  if(root == NULL) return INT_MIN;
  while(root->right != NULL) {
    root = root->right;
  }
  return root->data;
}

What is the output if the BST has nodes with values: 10, 20, 20, 30 (duplicates on right)?

hard

A. 30

B. 20

C. 10

D. Error due to duplicates

Solution

1. Step 1: Understand duplicates in BST

   Duplicates allowed on right means equal values go to right subtree, so max is still rightmost node.

2. Step 2: Trace findMax with duplicates

   Traversal moves right from 10 to 20, then to next 20, then to 30, which is rightmost and max.

3. Final Answer:

   30 -> Option A

4. Quick Check:

   Duplicates on right do not affect max = rightmost node [OK]

Hint: Duplicates on right subtree keep max at rightmost node [OK]

Common Mistakes:

• Assuming duplicates cause errors
• Stopping at first duplicate value
• Confusing duplicates location in BST