Convert Sorted Array to Balanced BST in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal when converting a sorted array to a balanced BST?

To create a binary search tree where the height difference between left and right subtrees of any node is minimal, ensuring efficient search operations.

beginner

Why do we choose the middle element of the sorted array as the root in this conversion?

Choosing the middle element ensures that the left and right subtrees have roughly equal numbers of nodes, helping keep the tree balanced.

intermediate

What is the time complexity of converting a sorted array to a balanced BST?

O(n), where n is the number of elements in the array, because each element is visited once to create the tree nodes.

beginner

In the recursive approach, what are the base cases when building the BST?

When the start index is greater than the end index, it means no elements are left to process, so return nullptr (no node).

beginner

How does the recursive function divide the array to build left and right subtrees?

It recursively calls itself on the left half (start to mid-1) for the left subtree and on the right half (mid+1 to end) for the right subtree.

What element is chosen as the root node when converting a sorted array to a balanced BST?

A The first element

B The middle element

C The last element

D A random element

The middle element is chosen to keep the tree balanced by evenly dividing the array.

What is the time complexity of building a balanced BST from a sorted array of size n?

A O(n)

B O(n log n)

C O(log n)

D O(n^2)

Each element is processed once, so the time complexity is O(n).

What happens when the start index is greater than the end index in the recursive function?

A Restart the recursion

B Create a new node

C Throw an error

D Return null (no node)

This is the base case indicating no elements left to process, so return null.

Which traversal method is naturally used to build the BST from the sorted array?

A Preorder traversal

B Postorder traversal

C Inorder traversal

D Level order traversal

The recursive approach picks the middle element first (root), then builds left and right subtrees, resembling preorder.

Why is the resulting BST balanced after conversion from a sorted array?

A Because the array is sorted

B Because the recursion stops early

C Because the middle element is chosen as root at each step

D Because the array size is even

Choosing the middle element ensures left and right subtrees have similar sizes, keeping the tree balanced.

Explain step-by-step how to convert a sorted array into a balanced BST using recursion.

Think about dividing the array and building nodes from the middle.

Describe why the balanced BST created from a sorted array is efficient for search operations.

Consider how tree height affects search speed.

Practice

1. What is the main goal when converting a sorted array to a balanced Binary Search Tree (BST)?

easy

A. To create a BST with minimum height

B. To create a BST with maximum height

C. To create a BST with all nodes having two children

D. To create a BST with nodes in reverse order

Solution

1. Step 1: Understand the problem goal

   The goal is to convert a sorted array into a BST that is balanced, meaning the tree height is minimized.

2. Step 2: Reason about balanced BST

   A balanced BST has minimum height to ensure efficient search operations.

3. Final Answer:

   To create a BST with minimum height -> Option A

4. Quick Check:

   Balanced BST = Minimum height [OK]

Hint: Pick the option that minimizes tree height for balance [OK]

Common Mistakes:

• Thinking maximum height means balanced
• Assuming all nodes must have two children
• Confusing order of nodes with balance

2. Which of the following is the correct base case condition in the recursive function to convert a sorted array to a balanced BST?

easy

A. if (start > end) return nullptr;

B. if (start == end) return nullptr;

C. if (start < end) return nullptr;

D. if (start >= end) return nullptr;

Solution

1. Step 1: Identify base case for recursion

   The recursion should stop when the start index passes the end index, meaning no elements left.

2. Step 2: Match condition to code

   The condition if (start > end) return nullptr; correctly handles this base case.

3. Final Answer:

   if (start > end) return nullptr; -> Option A

4. Quick Check:

   Base case = start > end [OK]

Hint: Stop recursion when start index exceeds end index [OK]

Common Mistakes:

• Using start == end as base case incorrectly
• Using start < end which never stops recursion
• Using start >= end which excludes valid single element

3. Given the sorted array [2, 4, 6, 8, 10, 12, 14], which of the following is the correct inorder traversal of the balanced BST created by the standard conversion method?

easy

A. [6, 4, 2, 8, 10, 12, 14]

B. [8, 4, 2, 6, 12, 10, 14]

C. [2, 4, 6, 8, 10, 12, 14]

D. [14, 12, 10, 8, 6, 4, 2]

Solution

1. Step 1: Understand inorder traversal of BST

   Inorder traversal of a BST always returns the nodes in sorted order.

2. Step 2: Check given array and traversal

   The array is sorted. The balanced BST created from it will have inorder traversal same as the original array.

3. Final Answer:

   [2, 4, 6, 8, 10, 12, 14] -> Option C

4. Quick Check:

   Inorder traversal = sorted array [OK]

Hint: Inorder traversal of BST = sorted array [OK]

Common Mistakes:

• Confusing preorder or postorder with inorder
• Assuming balanced BST changes inorder order
• Selecting reversed or mixed order arrays

4. What is the output BST preorder traversal for the sorted array [1, 2, 3, 4, 5] when converted to a balanced BST?

medium

A. [3, 2, 1, 5, 4]

B. [3, 1, 2, 4, 5]

C. [3, 2, 1, 4, 5]

D. [3, 1, 4, 2, 5]

Solution

1. Step 1: Build balanced BST from array

   Middle element is 3 (index 2), root node. Left subtree from [1,2], right subtree from [4,5].

2. Step 2: Construct preorder traversal

   Preorder = root, left subtree preorder, right subtree preorder.
   Left subtree indices [0,1], mid=(0+1)/2=0 root=1, right child from [1,1] root=2.
   Right subtree indices [3,4], mid=(3+4)/2=3 root=4, right child from [4,4] root=5.
   Preorder: 3, 1, 2, 4, 5.

3. Final Answer:

   [3, 1, 2, 4, 5] -> Option B

4. Quick Check:

   Preorder = root-left-right = [3,1,2,4,5] [OK]

Hint: Pick middle as root, preorder = root-left-right [OK]

Common Mistakes:

• Choosing wrong middle element for root
• Mixing preorder with inorder or postorder
• Incorrect subtree construction

5. Identify the error in this recursive function snippet for converting a sorted array to a balanced BST:

TreeNode* buildBST(int arr[], int start, int end) {
  if (start >= end) return nullptr;
  int mid = (start + end) / 2;
  TreeNode* root = new TreeNode(arr[mid]);
  root->left = buildBST(arr, start, mid - 1);
  root->right = buildBST(arr, mid + 1, end);
  return root;
}

medium

A. Right subtree call should use mid instead of mid + 1

B. Mid calculation should be mid = (start + end + 1) / 2

C. Left subtree call should use mid instead of mid - 1

D. Base case condition should be start > end, not start >= end

Solution

1. Step 1: Analyze base case condition

   The base case stops recursion when no elements remain. Using start >= end excludes the case when start == end, missing single element nodes.

2. Step 2: Correct base case for single element

   Base case should be start > end to allow processing single elements when start == end.

3. Final Answer:

   Base case condition should be start > end, not start >= end -> Option D

4. Quick Check:

   Base case = start > end [OK]

Hint: Base case must allow single element processing [OK]

Common Mistakes:

• Using start >= end excludes valid nodes
• Changing mid calculation unnecessarily
• Incorrect subtree index ranges