BST Find Maximum Element in DSA Java - Time & Space Complexity

Time Complexity: BST Find Maximum Element

O(h)

Understanding Time Complexity

We want to understand how long it takes to find the largest value in a Binary Search Tree (BST).

How does the search time change as the tree grows bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public int findMax(Node root) {
    if (root == null) {
        throw new IllegalArgumentException("Tree is empty");
    }
    Node current = root;
    while (current.right != null) {
        current = current.right;
    }
    return current.value;
}
    

This code finds the maximum element by moving right until no more right child exists.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Moving from one node to its right child.
• How many times: Once per level down the right side of the tree until the last node.

How Execution Grows With Input

As the tree grows, the number of steps depends on the height of the tree, especially the rightmost path.

Input Size (n)	Approx. Operations
10	Up to 10 steps if tree is skewed right
100	Up to 100 steps if skewed right
1000	Up to 1000 steps if skewed right

Pattern observation: The time grows linearly with the height of the tree, which can be as large as the number of nodes in the worst case.

Final Time Complexity

Time Complexity: O(h)

This means the time to find the maximum depends on the tree's height, moving down the right side one step at a time.

Common Mistake

[X] Wrong: "Finding the max in a BST always takes O(log n) time because it's a tree."

[OK] Correct: If the tree is not balanced and leans heavily to one side, the height can be as big as the number of nodes, making the search take longer.

Interview Connect

Understanding how tree shape affects search time helps you explain your reasoning clearly and shows you know how data structure design impacts performance.

Self-Check

"What if the BST was balanced? How would the time complexity change when finding the maximum element?"

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 root node

D. At the rightmost node

Solution

1. Step 1: Understand BST property

   In a BST, left child nodes are smaller and right child nodes are larger than the parent node.

2. Step 2: Locate maximum element

   The maximum element is the rightmost node because it has no larger right child.

3. Final Answer:

   At the rightmost node -> Option D

4. Quick Check:

   Maximum = rightmost node [OK]

Hint: Maximum is always the farthest right 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 Java method signatures correctly finds the maximum element in a BST node class named Node?

easy

A. public int findMax(Node root) { while(root.right != null) root = root.right; return root.data; }

B. public int findMax(Node root) { return root.left.data; }

C. public int findMax(Node root) { if(root == null) return 0; return root.data; }

D. public int findMax(Node root) { while(root.left != null) root = root.left; 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 method logic

   public int findMax(Node root) { while(root.right != null) root = root.right; return root.data; } correctly loops while root.right is not null, then returns root.data.

3. Final Answer:

   public int findMax(Node root) { while(root.right != null) root = root.right; return root.data; } -> Option A

4. Quick Check:

   Traverse right to find max [OK]

Hint: Loop right child until null to find max [OK]

Common Mistakes:

• Looping left child instead of right
• Returning root data without traversal
• Not checking for null root

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

class Node {
  int data;
  Node left, right;
  Node(int d) { data = d; left = right = null; }
}

public class BST {
  public static int findMax(Node root) {
    while(root.right != null) root = root.right;
    return root.data;
  }

  public static void main(String[] args) {
    Node root = new Node(10);
    root.left = new Node(5);
    root.right = new Node(20);
    root.right.right = new Node(30);
    System.out.println(findMax(root));
  }
}

medium

A. 20

B. 30

C. 10

D. 5

Solution

1. Step 1: Trace the BST structure

   Root=10, left=5, right=20, right.right=30. Maximum is rightmost node 30.

2. Step 2: Follow findMax method

   Loop moves from 10 to 20 to 30, then stops as 30.right is null, returns 30.

3. Final Answer:

   30 -> Option B

4. Quick Check:

   Rightmost node data = 30 [OK]

Hint: Follow right children to last node for max [OK]

Common Mistakes:

• Returning root data without traversal
• Confusing left and right children
• Ignoring right.right node

4. Identify the error in the following Java method to find the maximum element in a BST and select the corrected version.

public int findMax(Node root) {
  if(root == null) return -1;
  while(root.left != null) {
    root = root.left;
  }
  return root.data;
}

medium

A. Add recursive call instead of while loop

B. Return 0 instead of -1 when root is null

C. Change root.left to root.right in while loop

D. No error, code is correct

Solution

1. Step 1: Analyze traversal direction

   Maximum is found by moving right, but code moves left incorrectly.

2. Step 2: Correct the while loop

   Change while(root.left != null) to while(root.right != null) to find max correctly.

3. Final Answer:

   Change root.left to root.right in while loop -> Option C

4. Quick Check:

   Traverse right child for max [OK]

Hint: Max is rightmost, so loop on right child [OK]

Common Mistakes:

• Looping left child instead of right
• Returning wrong default value
• Thinking recursion is mandatory

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

public int findMaxWithDuplicates(Node root) {
  if(root == null) return Integer.MIN_VALUE;
  int maxVal = root.data;
  while(root.right != null) {
    root = root.right;
    if(root.data > maxVal) maxVal = root.data;
  }
  return maxVal;
}

What is the output of findMaxWithDuplicates for this BST? Root=15, root.left=10, root.right=20, root.right.right=20, root.right.right.right=25

hard

A. 25

B. 20

C. 15

D. Duplicate values cause error

Solution

1. Step 1: Understand BST with duplicates

   Duplicates can appear on right subtree; max is still rightmost largest value.

2. Step 2: Trace method execution

   Traverse right: 15 -> 20 -> 20 -> 25; maxVal updates to 25 at last node.

3. Final Answer:

   25 -> Option A

4. Quick Check:

   Rightmost node data = 25 [OK]

Hint: Rightmost node holds max even with duplicates [OK]

Common Mistakes:

• Stopping at first duplicate max value
• Assuming duplicates cause errors
• Ignoring rightmost traversal