Find Minimum in Rotated Sorted Array in DSA Java - Time & Space Complexity

Time Complexity: Find Minimum in Rotated Sorted Array

O(log n)

Understanding Time Complexity

We want to know how fast we can find the smallest number in a rotated sorted array.

How does the time needed grow as the array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public int findMin(int[] nums) {
    int left = 0, right = nums.length - 1;
    while (left < right) {
        int mid = left + (right - left) / 2;
        if (nums[mid] > nums[right]) {
            left = mid + 1;
        } else {
            right = mid;
        }
    }
    return nums[left];
}
    

This code finds the smallest number by using a smart search that cuts the search area in half each time.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loop that compares middle and right elements.
• How many times: The loop runs until the search space is reduced to one element, roughly halving each time.

How Execution Grows With Input

Each step cuts the search area 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 more step.

Final Time Complexity

Time Complexity: O(log n)

This means the time needed grows slowly, adding just a few more steps even if the array gets much bigger.

Common Mistake

[X] Wrong: "The loop runs through every element one by one, so it is O(n)."

[OK] Correct: The code cuts the search area in half each time, so it does not check every element.

Interview Connect

Understanding this search method shows you can use smart ways to find answers quickly, a skill valued in many coding challenges.

Self-Check

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

Practice

1. What is the main goal when finding the minimum in a rotated sorted array?

easy

A. To find the largest element in the array

B. To find the smallest element after the rotation point

C. To count the number of rotations

D. To sort the array again

Solution

1. Step 1: Understand the rotated sorted array

   A rotated sorted array is a sorted array shifted at some pivot. The smallest element is the rotation point.

2. Step 2: Identify the minimum element

   The minimum element is the smallest value after the rotation, which is the point where the order breaks.

3. Final Answer:

   To find the smallest element after the rotation point -> Option B

4. Quick Check:

   Minimum element = smallest after rotation [OK]

Hint: Look for the point where order breaks to find minimum [OK]

Common Mistakes:

• Confusing minimum with maximum element
• Trying to count rotations instead of finding minimum
• Assuming array is fully sorted without rotation

2. Which Java syntax correctly declares a method to find the minimum in a rotated sorted array?

easy

A. public int findMin(int[] nums) {}

B. int findMin(int nums) {}

C. void findMin(int[] nums) {}

D. public static findMin(int[] nums) {}

Solution

1. Step 1: Check method return type and parameters

   The method should return an int (the minimum value) and accept an int array parameter.

2. Step 2: Validate Java method syntax

   public int findMin(int[] nums) {} uses 'public int findMin(int[] nums) {}' which is correct Java syntax for this method.

3. Final Answer:

   public int findMin(int[] nums) {} -> Option A

4. Quick Check:

   Correct method signature = public int findMin(int[] nums) {} [OK]

Hint: Method must return int and accept int array parameter [OK]

Common Mistakes:

• Missing return type or using void incorrectly
• Incorrect parameter syntax
• Missing access modifier or static keyword incorrectly

3. What is the output of the following code snippet?

int[] nums = {4,5,6,7,0,1,2};
System.out.println(findMin(nums));

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

medium

A. 2

B. 4

C. 7

D. 0

Solution

1. Step 1: Understand the binary search logic

   The code uses binary search to find the minimum by comparing middle and right elements, narrowing the search space.

2. Step 2: Trace the loop with given array

   Array: [4,5,6,7,0,1,2] - mid=3 (value 7), 7 > 2, so left = mid+1 = 4 - left=4, right=6 - mid=5 (value 1), 1 <= 2, so right = mid = 5 - left=4, right=5 - mid=4 (value 0), 0 <= 1, so right = mid = 4 Loop ends when left == right == 4, nums[4] = 0.

3. Final Answer:

   0 -> Option D

4. Quick Check:

   Minimum element found = 0 [OK]

Hint: Compare mid and right to narrow search for minimum [OK]

Common Mistakes:

• Returning nums[mid] instead of nums[left]
• Confusing comparison direction in binary search
• Not updating left or right correctly

4. Identify the error in this code snippet for finding minimum in rotated sorted array:

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

medium

A. The return statement should be 'nums[right]'

B. The mid calculation is incorrect

C. The loop condition should be 'left < right' instead of 'left <= right'

D. The array should be sorted before searching

Solution

1. Step 1: Analyze the loop condition

   The loop uses 'left <= right', which can cause infinite loop or index errors because left can go beyond right.

2. Step 2: Correct the loop condition

   Changing the condition to 'left < right' ensures the loop stops when left meets right, correctly identifying the minimum index.

3. Final Answer:

   The loop condition should be 'left < right' instead of 'left <= right' -> Option C

4. Quick Check:

   Loop condition must be 'left < right' [OK]

Hint: Use 'left < right' to avoid infinite loops in binary search [OK]

Common Mistakes:

• Using 'left <= right' causing infinite loops
• Incorrectly adjusting right pointer
• Returning wrong array element after loop

5. Given a rotated sorted array that may contain duplicates, which modification is needed in the binary search to find the minimum correctly?

int[] nums = {2,2,2,0,1,2};

hard

A. Add a condition to reduce right by one when nums[mid] equals nums[right]

B. Ignore duplicates and proceed as usual

C. Sort the array before searching

D. Use linear search instead of binary search

Solution

1. Step 1: Understand the effect of duplicates

   Duplicates can cause ambiguity when nums[mid] equals nums[right], making it unclear which side to search.

2. Step 2: Modify binary search to handle duplicates

   When nums[mid] == nums[right], reduce right by one to shrink search space safely without missing minimum.

3. Final Answer:

   Add a condition to reduce right by one when nums[mid] equals nums[right] -> Option A

4. Quick Check:

   Handle duplicates by shrinking right pointer [OK]

Hint: When equal, reduce right pointer to handle duplicates [OK]

Common Mistakes:

• Ignoring duplicates causing wrong minimum
• Sorting array which is inefficient
• Switching to linear search unnecessarily