Binary Search as Divide and Conquer in DSA Java - Time & Space Complexity

Time Complexity: Binary Search as Divide and Conquer

O(log n)

Understanding Time Complexity

We want to understand how fast binary search finds an item in a sorted list.

How does the number of steps change as the list gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public int binarySearch(int[] arr, int target) {
    int left = 0, right = arr.length - 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: Checking the middle element of the current search range.
• How many times: The search range halves each time, so this check repeats until the range is empty.

How Execution Grows With Input

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

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

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

Final Time Complexity

Time Complexity: O(log n)

This means the number of steps grows slowly, adding just one step when the list size doubles.

Common Mistake

[X] Wrong: "Binary search checks every element one by one like linear search."

[OK] Correct: Binary search skips half the list each time, so it does far fewer checks than linear search.

Interview Connect

Understanding binary search time complexity shows you can analyze efficient algorithms, a key skill in coding interviews.

Self-Check

"What if the array was not sorted? How would that affect the time complexity of searching for a target?"

Practice

1. What is the main idea behind Binary Search as a divide and conquer algorithm?

easy

A. It searches every element one by one from start to end.

B. It divides the search space into two halves and eliminates one half each time.

C. It sorts the array before searching.

D. It uses recursion to add elements.

Solution

1. Step 1: Understand divide and conquer in binary search

   Binary search splits the sorted array into two halves and decides which half to continue searching in.

2. Step 2: Eliminate half the search space

   By comparing the middle element with the target, it discards one half, reducing the problem size quickly.

3. Final Answer:

   It divides the search space into two halves and eliminates one half each time. -> Option B

4. Quick Check:

   Divide and conquer = split and discard half [OK]

Hint: Binary search halves the search space each step [OK]

Common Mistakes:

• Thinking binary search checks every element
• Confusing binary search with sorting
• Believing binary search adds elements

2. Which of the following is the correct Java method signature for a binary search function on an integer array?

easy

A. public static int binarySearch(int[] arr, int target)

B. int binarySearch(int arr[], target)

C. public int binarySearch(int[] arr, int target, int start, int end)

D. static void binarySearch(int[] arr, int target)

Solution

1. Step 1: Check method signature correctness

   public static int binarySearch(int[] arr, int target) uses public static, returns int index, and has correct parameter types and order.

2. Step 2: Compare other options

   int binarySearch(int arr[], target) misses access modifier and parameter type for target; public int binarySearch(int[] arr, int target, int start, int end) has extra parameters but no static; static void binarySearch(int[] arr, int target) returns void which is incorrect for search.

3. Final Answer:

   public static int binarySearch(int[] arr, int target) -> Option A

4. Quick Check:

   Correct signature returns int and uses static [OK]

Hint: Binary search returns index as int, not void [OK]

Common Mistakes:

• Omitting static keyword
• Wrong return type (void instead of int)
• Missing parameter types

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

int[] arr = {2, 4, 6, 8, 10};
int target = 6;
int result = binarySearch(arr, target);
System.out.println(result);

public static int binarySearch(int[] arr, int target) {
    int left = 0, right = arr.length - 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;
}

medium

A. 2

B. 3

C. -1

D. 0

Solution

1. Step 1: Identify the target and array

   The array is [2,4,6,8,10], target is 6.

2. Step 2: Trace binary search steps

   Initial left=0, right=4, mid=2; arr[2]=6 equals target, so return 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Index of 6 in array = 2 [OK]

Hint: Check middle element index for target match first [OK]

Common Mistakes:

• Confusing index with value
• Off-by-one errors in mid calculation
• Returning wrong index when target found

4. Find the error in the following binary search code and choose the correct fix.

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

medium

A. Change mid calculation to mid = left - right to fix mid index.

B. Change while condition to left < right to fix infinite loop.

C. Change right to arr.length - 1 to avoid ArrayIndexOutOfBoundsException.

D. Remove else if and use only if statements.

Solution

1. Step 1: Identify array bounds usage

   Right is set to arr.length, which is out of array index range (max index is length-1).

2. Step 2: Fix right boundary

   Set right = arr.length - 1 to prevent accessing invalid index and avoid runtime error.

3. Final Answer:

   Change right to arr.length - 1 to avoid ArrayIndexOutOfBoundsException. -> Option C

4. Quick Check:

   Array indices go from 0 to length-1 [OK]

Hint: Array last index is length minus one [OK]

Common Mistakes:

• Setting right to arr.length causes index error
• Incorrect mid calculation
• Changing loop condition incorrectly

5. You have a sorted array with duplicate elements: int[] arr = {1, 2, 2, 2, 3, 4}. How would you modify binary search to find the first occurrence of the target 2?

hard

A. Modify mid calculation to always pick left middle element.

B. Return the first found index immediately without further checks.

C. Use linear search instead of binary search for duplicates.

D. After finding target, continue searching left half to find earlier occurrence.

Solution

1. Step 1: Understand duplicate handling in binary search

   Standard binary search returns any matching index, not necessarily first occurrence.

2. Step 2: Modify search to find first occurrence

   When target found, move right pointer to mid-1 to continue searching left side for earlier matches.

3. Final Answer:

   After finding target, continue searching left half to find earlier occurrence. -> Option D

4. Quick Check:

   Find first occurrence by searching left after match [OK]

Hint: On match, search left half to find first duplicate [OK]

Common Mistakes:

• Stopping at first found index
• Using linear search unnecessarily
• Changing mid calculation without reason