Convert Sorted Array to Balanced BST in DSA Java - Time & Space Complexity

Time Complexity: Convert Sorted Array to Balanced BST

O(n)

Understanding Time Complexity

We want to know how the time needed to build a balanced binary search tree changes as the input array grows.

How does the number of steps grow when we convert a sorted array into a balanced BST?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public TreeNode sortedArrayToBST(int[] nums) {
    return buildBST(nums, 0, nums.length - 1);
}

private TreeNode buildBST(int[] nums, int left, int right) {
    if (left > right) return null;
    int mid = left + (right - left) / 2;
    TreeNode node = new TreeNode(nums[mid]);
    node.left = buildBST(nums, left, mid - 1);
    node.right = buildBST(nums, mid + 1, right);
    return node;
}

This code builds a balanced BST by choosing the middle element as root and recursively building left and right subtrees.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls that split the array and create tree nodes.
• How many times: Each element in the array is visited exactly once to create a node.

How Execution Grows With Input

Each element leads to one node creation and recursive calls split the array evenly.

Input Size (n)	Approx. Operations
10	About 10 node creations and recursive calls
100	About 100 node creations and recursive calls
1000	About 1000 node creations and recursive calls

Pattern observation: The number of operations grows roughly in direct proportion to the input size.

Final Time Complexity

Time Complexity: O(n)

This means the time needed grows linearly with the number of elements in the array.

Common Mistake

[X] Wrong: "Because the function calls itself twice, the time complexity is exponential like O(2^n)."

[OK] Correct: Each element is processed only once, and the recursive calls split the array without overlapping work, so the total work is linear, not exponential.

Interview Connect

Understanding this time complexity helps you explain how recursion and divide-and-conquer work together efficiently in building balanced trees.

Self-Check

"What if we changed the code to always pick the first element as root instead of the middle? How would the time complexity change?"

Practice

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

easy

A. To reverse the array elements

B. To create a linked list from the array

C. To sort the array again

D. To create a BST with minimal height for efficient search

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 benefits

   A balanced BST ensures search operations are efficient, typically O(log n) time, by minimizing height.

3. Final Answer:

   To create a BST with minimal height for efficient search -> Option D

4. Quick Check:

   Balanced BST = minimal height = efficient search [OK]

Hint: Balanced BST means minimal height for fast search [OK]

Common Mistakes:

• Thinking the array needs to be reversed
• Confusing BST with linked list
• Ignoring the balance requirement

2. Which Java method signature correctly represents the recursive function to convert a sorted array to a balanced BST?

easy

A. public TreeNode sortedArrayToBST(int[] nums, int left, int right)

B. public void sortedArrayToBST(int[] nums)

C. public int sortedArrayToBST(int[] nums, int start)

D. public TreeNode sortedArrayToBST(int[] nums, int mid)

Solution

1. Step 1: Identify parameters needed for recursion

   The recursive function needs the array and two indices (left and right) to define the current subarray.

2. Step 2: Check return type and parameters

   The function returns a TreeNode (root of subtree) and takes int[] nums, int left, int right as parameters.

3. Final Answer:

   public TreeNode sortedArrayToBST(int[] nums, int left, int right) -> Option A

4. Quick Check:

   Recursive BST function needs array + left + right indices [OK]

Hint: Recursive BST needs array and left-right indices [OK]

Common Mistakes:

• Missing left and right indices parameters
• Wrong return type (void or int)
• Using mid as parameter instead of indices

3. What is the output tree structure (inorder traversal) after running the code below?

int[] nums = {1, 2, 3, 4, 5};
TreeNode root = sortedArrayToBST(nums, 0, nums.length - 1);
printInorder(root);

Assuming printInorder prints nodes in inorder.

medium

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

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

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

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

Solution

1. Step 1: Understand inorder traversal of BST

   Inorder traversal of a BST always returns the sorted order of elements.

2. Step 2: Check input array and output

   The input array is sorted: [1, 2, 3, 4, 5]. The inorder traversal of the BST built from it will be the same sorted array.

3. Final Answer:

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

4. Quick Check:

   Inorder traversal of BST = sorted array [OK]

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

Common Mistakes:

• Confusing preorder or postorder with inorder
• Expecting reversed or shuffled output
• Not understanding BST property

4. Identify the error in the following code snippet for converting a sorted array to a balanced BST:

public TreeNode sortedArrayToBST(int[] nums, int left, int right) {
  if (left > right) return null;
  int mid = (left + right) / 2;
  TreeNode root = new TreeNode(nums[mid]);
  root.left = sortedArrayToBST(nums, left, mid - 1);
  root.right = sortedArrayToBST(nums, mid + 1, right);
  return root;
}

// Called with sortedArrayToBST(nums, 0, nums.length);

medium

A. The base case condition is incorrect

B. The initial call uses wrong right index

C. The mid calculation causes overflow

D. The TreeNode constructor is missing

Solution

1. Step 1: Check the initial call parameters

   The function expects right to be the last valid index, but the call uses nums.length which is out of bounds.

2. Step 2: Understand array indexing

   Array indices go from 0 to nums.length - 1, so right should be nums.length - 1.

3. Final Answer:

   The initial call uses wrong right index -> Option B

4. Quick Check:

   Right index must be nums.length - 1, not nums.length [OK]

Hint: Right index = last array index (length - 1) [OK]

Common Mistakes:

• Passing nums.length as right index
• Ignoring zero-based indexing
• Assuming mid calculation causes overflow here

5. Given a sorted array with duplicate values: int[] nums = {1, 2, 2, 3, 4, 4, 5}; Which statement about the balanced BST created by sortedArrayToBST(nums, 0, nums.length - 1) is true?

hard

A. The BST will only keep unique values in left subtree

B. The BST will remove duplicates automatically

C. The BST will contain duplicate nodes for repeated values

D. The BST will throw an error due to duplicates

Solution

1. Step 1: Understand BST property with duplicates

   BST can contain duplicates; they are usually placed consistently either left or right subtree.

2. Step 2: Check behavior of conversion from sorted array

   The conversion uses array elements as nodes directly, so duplicates appear as separate nodes in the tree.

3. Final Answer:

   The BST will contain duplicate nodes for repeated values -> Option C

4. Quick Check:

   Duplicates in array = duplicates in BST nodes [OK]

Hint: Duplicates in array become duplicate nodes in BST [OK]

Common Mistakes:

• Assuming duplicates are removed automatically
• Thinking duplicates cause errors
• Believing duplicates go only to left subtree