Why BST Find Maximum Element in DSA C++?

The Big Idea

What if you could find the biggest number instantly without looking at every single one?

The Scenario

Imagine you have a messy pile of books with different heights, and you want to find the tallest book. If you try to check each book one by one, it will take a lot of time and effort.

The Problem

Manually searching for the tallest book means looking at every single book, which is slow and tiring. You might lose track or miss some books, making mistakes easy.

The Solution

A Binary Search Tree (BST) organizes books so that taller books are always to the right. To find the tallest book, you just keep moving right until you can't go further. This saves 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 findMax(Node* root) {
  Node* current = root;
  while (current->right != nullptr) {
    current = current->right;
  }
  return current->data;
}

What It Enables

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

Real Life Example

In a phone contact list sorted by name, finding the last contact alphabetically is like finding the maximum in a BST.

Key Takeaways

Manual search checks every item, which is slow.

BST stores data so max is always at the rightmost node.

Finding max in BST is fast and simple by moving right.

Practice

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

easy

A. At the leftmost node

B. At any leaf node

C. At the root node

D. At the rightmost 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 D

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++ function signatures correctly finds the maximum element in a BST node pointer root?

easy

A. int findMax(Node* root) { return root->data; }

B. int findMax(Node* root) { while(root->left) root = root->left; return root->data; }

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

D. int findMax(Node* root) { while(root->parent) root = root->parent; return root->data; }

Solution

1. Step 1: Check traversal direction for maximum

   Maximum is found by moving right until no right child exists.

2. Step 2: Verify code correctness

   int findMax(Node* root) { while(root->right) root = root->right; return root->data; } correctly loops while root->right exists and returns root->data.

3. Final Answer:

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

4. Quick Check:

   Traverse right child to find max [OK]

Hint: Traverse right child pointer until null [OK]

Common Mistakes:

• Traversing left child instead of right
• Returning root data without traversal
• Using parent pointer which may not exist

3. What will be the output of the following C++ code snippet?

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

Node* root = new Node{10, nullptr, nullptr};
root->right = new Node{20, nullptr, nullptr};
root->right->right = new Node{30, nullptr, nullptr};

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

std::cout << findMax(root) << std::endl;

medium

A. 30

B. 20

C. 10

D. Runtime error

Solution

1. Step 1: Trace the BST structure

   Root is 10, right child 20, right child's right child 30.

2. Step 2: Follow findMax function

   Loop moves from 10 to 20, then 20 to 30, then stops as 30 has no right child.

3. Final Answer:

   30 -> Option A

4. Quick Check:

   Rightmost node data = 30 [OK]

Hint: Rightmost node data is maximum [OK]

Common Mistakes:

• Returning root data without traversal
• Confusing left and right pointers
• Assuming runtime error due to nullptr

4. Identify the bug in the following C++ function to find the maximum element in a BST:

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

medium

A. Should traverse right child, not left child

B. Should return 0 instead of -1 for nullptr

C. Missing check for root->right in while loop

D. Function should be void, not int

Solution

1. Step 1: Analyze traversal direction

   The function incorrectly traverses left child to find maximum, but maximum is at rightmost node.

2. Step 2: Correct traversal logic

   Change while(root->left) to while(root->right) to find maximum correctly.

3. Final Answer:

   Should traverse right child, not left child -> Option A

4. Quick Check:

   Maximum = rightmost node, not leftmost [OK]

Hint: Maximum is rightmost, so traverse right pointer [OK]

Common Mistakes:

• Traversing left child instead of right
• Ignoring nullptr check
• Returning wrong default value

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?

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

// Function to find max element
int findMax(Node* root) {
  // Your code here
}

hard

A. Traverse right while root->right exists and root->right->data > root->data

B. Traverse right while root->right exists only

C. Traverse left while root->left exists and root->left->data > root->data

D. Return root->data without traversal

Solution

1. Step 1: Understand duplicates in BST

   Even with duplicates allowed on the right subtree, BST property ensures right subtree values are >= parent, so maximum is always the rightmost node.

2. Step 2: Correct traversal for maximum

   Traverse right while root->right exists only. No data comparison needed due to BST invariants.

3. Final Answer:

   Traverse right while root->right exists only -> Option B

4. Quick Check:

   Traverse right child pointer until null [OK]

Hint: Traverse right child pointer until null [OK]

Common Mistakes:

• Using strict > check which stops early on duplicates
• Traversing left instead of right
• Returning root data without traversal