Search in Rotated Sorted Array in DSA Go - Time & Space Complexity

Time Complexity: Search in Rotated Sorted Array

O(log n)

Understanding Time Complexity

We want to understand how fast we can find a number in a rotated sorted list.

How does the time to find the number grow as the list gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

func search(nums []int, target int) int {
    left, right := 0, len(nums)-1
    for left <= right {
        mid := (left + right) / 2
        if nums[mid] == target {
            return mid
        }
        if nums[left] <= nums[mid] {
            if target >= nums[left] && target < nums[mid] {
                right = mid - 1
            } else {
                left = mid + 1
            }
        } else {
            if target > nums[mid] && target <= nums[right] {
                left = mid + 1
            } else {
                right = mid - 1
            }
        }
    }
    return -1
}
    

This code searches for a target number in a rotated sorted array using a modified binary search.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The for loop that halves the search range each time.
• How many times: The loop runs about log base 2 of n times, where n is the array size.

How Execution Grows With Input

Each step cuts the search area roughly in half, so the number of steps grows slowly as the list 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 search time grows slowly, even if the list becomes very large.

Common Mistake

[X] Wrong: "Because the array is rotated, we must check every element, so it takes O(n) time."

[OK] Correct: The code cleverly uses the sorted parts to skip half the elements each time, keeping the search fast.

Interview Connect

Understanding this search helps you show how to handle tricky sorted data efficiently, a skill many interviews value.

Self-Check

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

Practice

1. What is the main challenge when searching in a rotated sorted array compared to a normal sorted array?

easy

A. The array size is unknown

B. The array contains duplicate elements

C. The array is unsorted

D. The array is split into two sorted parts, making direct binary search tricky

Solution

1. Step 1: Understand the array structure

   A rotated sorted array is originally sorted but then rotated at some pivot, splitting it into two sorted parts.

2. Step 2: Identify the search challenge

   Because of the rotation, a simple binary search cannot be applied directly as the array is not fully sorted in one sequence.

3. Final Answer:

   The array is split into two sorted parts, making direct binary search tricky -> Option D

4. Quick Check:

   Rotation splits array = search challenge [OK]

Hint: Look for the pivot splitting the array into two sorted halves [OK]

Common Mistakes:

• Assuming the array is fully sorted
• Ignoring the rotation pivot
• Trying linear search only

2. Which of the following Go function signatures correctly represents a binary search in a rotated sorted array?

easy

A. func search(nums []int, target int) int

B. func search(nums int, target int) int

C. func search(nums []int, target string) int

D. func search(nums []int, target int) bool

Solution

1. Step 1: Check parameter types

   The function should accept a slice of integers and an integer target to search for.

2. Step 2: Check return type

   The function returns an integer index of the target or -1 if not found, so return type int is correct.

3. Final Answer:

   func search(nums []int, target int) int -> Option A

4. Quick Check:

   Correct params and return type = func search(nums []int, target int) int [OK]

Hint: Function takes []int and int target, returns int index [OK]

Common Mistakes:

• Using wrong parameter types
• Returning bool instead of index
• Using string target instead of int

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

nums := []int{4,5,6,7,0,1,2}
target := 0
fmt.Println(search(nums, target))

func search(nums []int, target int) int {
    left, right := 0, len(nums)-1
    for left <= right {
        mid := (left + right) / 2
        if nums[mid] == target {
            return mid
        }
        if nums[left] <= nums[mid] {
            if nums[left] <= target && target < nums[mid] {
                right = mid - 1
            } else {
                left = mid + 1
            }
        } else {
            if nums[mid] < target && target <= nums[right] {
                left = mid + 1
            } else {
                right = mid - 1
            }
        }
    }
    return -1
}

medium

A. -1

B. 0

C. 4

D. 6

Solution

1. Step 1: Identify target and array

   Target is 0, array is rotated sorted: [4,5,6,7,0,1,2].

2. Step 2: Trace binary search steps

   Mid starts at index 3 (value 7), target 0 is not equal. Left half [4..7] is sorted. Target 0 is not in left half, so move left to mid+1=4. Now left=4, right=6. Mid=5 (value 1). Target 0 < 1, right=mid-1=4. Now left=4, right=4. Mid=4 (value 0), found target at index 4.

3. Final Answer:

   4 -> Option C

4. Quick Check:

   Target 0 found at index 4 [OK]

Hint: Check mid, decide which half is sorted, adjust search [OK]

Common Mistakes:

• Not updating left/right correctly
• Confusing sorted half
• Returning wrong index

4. The following Go code attempts to search a target in a rotated sorted array but has a bug. What is the bug?

func search(nums []int, target int) int {
    left, right := 0, len(nums)-1
    for left < right {
        mid := (left + right) / 2
        if nums[mid] == target {
            return mid
        }
        if nums[left] <= nums[mid] {
            if nums[left] <= target && target < nums[mid] {
                right = mid - 1
            } else {
                left = mid + 1
            }
        } else {
            if nums[mid] < target && target <= nums[right] {
                left = mid + 1
            } else {
                right = mid - 1
            }
        }
    }
    return -1
}

medium

A. The function does not return the index

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

C. The target comparison uses wrong operators

D. The mid calculation is incorrect

Solution

1. Step 1: Analyze loop condition

   The loop uses 'left < right', which stops when left == right, possibly missing the last element check.

2. Step 2: Correct loop condition

   Changing to 'left <= right' ensures the last element is checked, preventing missed target.

3. Final Answer:

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

4. Quick Check:

   Loop must include equal to check [OK]

Hint: Use 'left <= right' to cover all elements in binary search [OK]

Common Mistakes:

• Using 'left < right' and missing last element
• Incorrect mid calculation
• Wrong comparison operators

5. Given a rotated sorted array with possible duplicates, which modification is needed in the binary search to correctly find the target?

nums := []int{2,5,6,0,0,1,2}
target := 0

hard

A. Add extra checks to skip duplicates when nums[left] == nums[mid] == nums[right]

B. Use linear search instead of binary search

C. Ignore duplicates and apply normal rotated binary search

D. Sort the array before searching

Solution

1. Step 1: Understand duplicates effect

   Duplicates can cause ambiguity in deciding which half is sorted when nums[left] == nums[mid] == nums[right].

2. Step 2: Modify search to skip duplicates

   When duplicates appear at left, mid, and right, increment left and decrement right to skip duplicates and continue search.

3. Final Answer:

   Add extra checks to skip duplicates when nums[left] == nums[mid] == nums[right] -> Option A

4. Quick Check:

   Skip duplicates to avoid ambiguity [OK]

Hint: Skip duplicates at edges when equal to mid [OK]

Common Mistakes:

• Ignoring duplicates causing wrong half detection
• Switching to linear search unnecessarily
• Sorting array breaks problem constraints