Find Peak Element Using Binary Search in DSA C++ - Time & Space Complexity

Time Complexity: Find Peak Element Using Binary Search

O(log n)

Understanding Time Complexity

We want to know how fast the binary search method finds a peak element in an array.

How does the number of steps grow as the array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int findPeakElement(std::vector<int>& nums) {
    int left = 0, right = nums.size() - 1;
    while (left < right) {
        int mid = left + (right - left) / 2;
        if (nums[mid] < nums[mid + 1]) {
            left = mid + 1;
        } else {
            right = mid;
        }
    }
    return left;
}

This code finds a peak element by repeatedly dividing the search space in half using binary search.

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: About log base 2 of n times, where n is the array size.

How Execution Grows With Input

Each step cuts the array size roughly in half, so the number of steps grows slowly as the array grows.

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 steps needed grow very slowly even if the array gets much bigger.

Common Mistake

[X] Wrong: "The loop runs n times because it looks like it checks each element."

[OK] Correct: Actually, the loop cuts the search space in half each time, so it runs much fewer times than n.

Interview Connect

Understanding this binary search approach shows you can find answers quickly by smartly reducing work, a key skill in many coding challenges.

Self-Check

"What if we changed the array to be sorted strictly increasing or strictly decreasing? How would the time complexity change?"

Practice

1. What is a peak element in an array when using binary search to find it?

easy

A. An element that is greater than its neighbors

B. An element that is smaller than its neighbors

C. The first element of the array

D. The last element of the array

Solution

1. Step 1: Understand the definition of a peak element

   A peak element is one that is strictly greater than its neighbors on both sides (or only one side if at the boundary).

2. Step 2: Apply this to binary search context

   Binary search finds such an element by comparing mid element with neighbors to decide search direction.

3. Final Answer:

   An element that is greater than its neighbors -> Option A

4. Quick Check:

   Peak element = greater than neighbors [OK]

Hint: Peak element is bigger than neighbors, not smaller [OK]

Common Mistakes:

• Confusing peak with smallest element
• Thinking peak is always first or last element
• Ignoring boundary conditions

2. Which of the following is the correct syntax to start binary search for peak element in C++?

easy

A. int left = 1, right = n;

B. int left = 0, right = n;

C. int left = 0, right = n - 1;

D. int left = 1, right = n - 1;

Solution

1. Step 1: Identify valid index range for array of size n

   Array indices go from 0 to n-1, so left should start at 0 and right at n-1.

2. Step 2: Check each option for correct initialization

   int left = 0, right = n - 1; correctly initializes left=0 and right=n-1, suitable for binary search.

3. Final Answer:

   int left = 0, right = n - 1; -> Option C

4. Quick Check:

   Index range = 0 to n-1 [OK]

Hint: Array indices start at 0, end at n-1 [OK]

Common Mistakes:

• Starting left at 1 instead of 0
• Setting right to n instead of n-1
• Confusing inclusive and exclusive ranges

3. What will be the output index of the peak element for the array [1, 3, 20, 4, 1, 0] using binary search peak finding?

medium

A. 0

B. 2

C. 3

D. 1

Solution

1. Step 1: Identify peak elements in the array

   Array: [1, 3, 20, 4, 1, 0]. 20 at index 2 is greater than neighbors 3 and 4, so it's a peak.

2. Step 2: Binary search will find index 2 as peak

   Binary search compares mid elements and moves left or right until it finds 20 at index 2.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Peak at index 2 = 20 [OK]

Hint: Peak is local max, here 20 at index 2 [OK]

Common Mistakes:

• Choosing first or last element as peak incorrectly
• Confusing index with value
• Not checking both neighbors

4. Given the following code snippet, what is the bug that prevents finding the peak element correctly?

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

medium

A. Decreasing right by 1 skips potential peak

B. Mid calculation causes overflow

C. Loop condition should be left <= right

D. Returning left instead of right

Solution

1. Step 1: Analyze the binary search update steps

   If arr[mid] >= arr[mid+1], the code sets right = mid - 1, which skips mid as a candidate peak.

2. Step 2: Correct approach is to set right = mid to include mid in search

   Setting right = mid keeps mid in range; subtracting 1 may miss the peak.

3. Final Answer:

   Decreasing right by 1 skips potential peak -> Option A

4. Quick Check:

   Right update must keep mid included [OK]

Hint: Do not exclude mid when moving right pointer [OK]

Common Mistakes:

• Setting right = mid - 1 instead of right = mid
• Ignoring mid element as possible peak
• Incorrect loop condition

5. You have an array [10, 20, 15, 2, 23, 90, 67]. Using binary search for peak element, which index will be returned and why?

hard

A. 0, because 10 is the first element

B. 1, because 20 is a peak element

C. 6, because 67 is the last element

D. 5, because 90 is a peak element

Solution

1. Step 1: Identify all peak elements in the array

   Array: [10, 20, 15, 2, 23, 90, 67]. Peaks are 20 (index 1) and 90 (index 5). 90 is greater than neighbors 23 and 67.

2. Step 2: Binary search tends to find a peak, often the higher one

   Binary search will find 90 at index 5 because it is a higher peak than 20 at index 1.

3. Final Answer:

   5, because 90 is a peak element -> Option D

4. Quick Check:

   Highest peak found = index 5 [OK]

Hint: Binary search finds any peak; higher peaks likely found first [OK]

Common Mistakes:

• Assuming first peak is always returned
• Ignoring multiple peaks in array
• Confusing last element as peak without checking neighbors