Binary Search Iterative Approach in DSA C++ - Time & Space Complexity

Time Complexity: Binary Search Iterative Approach

O(log n)

Understanding Time Complexity

We want to understand how the time taken by binary search changes as the list size grows.

Specifically, how many steps does it take to find a number in a sorted list?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int binarySearch(int arr[], int n, int target) {
    int left = 0, right = n - 1;
    while (left <= right) {
        int mid = left + (right - left) / 2;
        if (arr[mid] == target) return mid;
        else if (arr[mid] < target) left = mid + 1;
        else right = mid - 1;
    }
    return -1;
}
    

This code searches for a target number in a sorted array by repeatedly dividing the search range in half.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loop that halves the search range each time.
• How many times: The loop runs until the search range is empty, roughly halving the range each step.

How Execution Grows With Input

Each step cuts the search area in half, so the number of steps grows slowly as the list gets bigger.

Input Size (n)	Approx. Operations
10	About 4 steps
100	About 7 steps
1000	About 10 steps

Pattern observation: Doubling the input size adds only one extra step.

Final Time Complexity

Time Complexity: O(log n)

This means the number of steps grows slowly, increasing by one step each time the input size doubles.

Common Mistake

[X] Wrong: "Binary search checks every element one by one, so it is O(n)."

[OK] Correct: Binary search skips half the elements each step, so it does not check all elements.

Interview Connect

Knowing binary search time complexity helps you explain why it is efficient and when to use it in real problems.

Self-Check

"What if the array was not sorted? How would the time complexity change?"

Practice

1. What is the main purpose of the binarySearchIterative function in the iterative binary search approach?

easy

A. To find the position of a target value in a sorted array

B. To sort an unsorted array

C. To reverse the elements of an array

D. To count the number of elements in an array

Solution

1. Step 1: Understand the function goal

   The binary search function is designed to locate a target value within a sorted array efficiently.

2. Step 2: Identify the operation performed

   It repeatedly divides the search interval in half to find the target's position or determine it is not present.

3. Final Answer:

   To find the position of a target value in a sorted array -> Option A

4. Quick Check:

   Binary search locates target index [OK]

Hint: Binary search finds target index in sorted array fast [OK]

Common Mistakes:

• Thinking binary search sorts the array
• Confusing binary search with linear search
• Assuming it works on unsorted arrays

2. Which of the following is the correct syntax to calculate the middle index in an iterative binary search to avoid overflow?

easy

A. int mid = (low - high) / 2;

B. int mid = (low + high) / 2;

C. int mid = low + (high - low) / 2;

D. int mid = (high - low) / 2 + high;

Solution

1. Step 1: Understand overflow risk in mid calculation

   Using (low + high) / 2 can overflow if low and high are large integers.

2. Step 2: Use safe formula to avoid overflow

   The formula low + (high - low) / 2 calculates mid without adding large numbers directly.

3. Final Answer:

   int mid = low + (high - low) / 2; -> Option C

4. Quick Check:

   Safe mid calculation avoids overflow [OK]

Hint: Use low + (high - low)/2 to prevent overflow [OK]

Common Mistakes:

• Using (low + high)/2 causing overflow
• Subtracting incorrectly in mid calculation
• Mixing up low and high in formula

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

int arr[] = {2, 4, 6, 8, 10};
int n = 5;
int target = 6;
int result = binarySearchIterative(arr, n, target);
std::cout << result << std::endl;

// Assume binarySearchIterative is correctly implemented iterative binary search

medium

A. -1

B. 2

C. 3

D. 1

Solution

1. Step 1: Identify the target and array

   The array is {2, 4, 6, 8, 10} and the target is 6.

2. Step 2: Find the index of target using binary search

   6 is at index 2 (0-based indexing) in the array.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Index of 6 in array = 2 [OK]

Hint: Remember array indexing starts at 0 [OK]

Common Mistakes:

• Confusing index with value
• Using 1-based indexing instead of 0-based
• Assuming target not found returns 0

4. Identify the error in the following iterative binary search code snippet:

int binarySearchIterative(int arr[], int n, int target) {
    int low = 0, high = n - 1;
    while (low <= high) {
        int mid = (low + high) / 2;
        if (arr[mid] == target) {
            return mid;
        } else if (arr[mid] < target) {
            low = mid + 1;
        } else {
            high = mid - 1;
        }
    }
    return -1;
}

medium

A. The mid calculation can cause integer overflow

B. The loop condition should be low < high

C. The return value should be 0 when not found

D. The array should be unsorted for binary search

Solution

1. Step 1: Review mid calculation

   Mid is calculated as (low + high) / 2 which can overflow if low and high are large.

2. Step 2: Suggest safer mid calculation

   Use low + (high - low) / 2 to avoid overflow in mid calculation.

3. Final Answer:

   The mid calculation can cause integer overflow -> Option A

4. Quick Check:

   Mid calculation overflow risk = true [OK]

Hint: Use safe mid formula to avoid overflow [OK]

Common Mistakes:

• Changing loop condition incorrectly
• Returning 0 instead of -1 when not found
• Assuming binary search works on unsorted arrays

5. Given a sorted array arr = {1, 3, 5, 7, 9, 11, 13}, how many iterations will the iterative binary search take to find the target value 7?

hard

A. 4

B. 2

C. 3

D. 1

Solution

1. Step 1: Initialize low and high pointers

   low = 0, high = 6 (array length - 1)

2. Step 2: Trace each iteration to find 7

   Iteration 1: mid = 0 + (6-0)/2 = 3, arr[3] = 7 (target found at first check)

3. Step 3: Count iterations

   Only 1 iteration is needed because target is found immediately at mid index 3.

4. Final Answer:

   1 -> Option D

5. Quick Check:

   Target found at first mid check [OK]

Hint: Count mid calculations until target found [OK]

Common Mistakes:

• Assuming always 3 iterations for any search
• Counting array length instead of iterations
• Forgetting zero-based indexing