Search in Rotated Sorted Array in DSA Rust - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to start the binary search with correct initial boundaries.

DSA Rust

let mut left = [1];
let mut right = nums.len() as i32 - 1;

Drag options to blanks, or click blank then click option'

A0

B1

Cnums.len() as i32

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Starting left at 1 skips the first element.

Using negative indices causes errors.

The search starts from the first index 0 to the last index (length - 1).

2fill in blank

medium

Complete the code to calculate the middle index safely.

DSA Rust

let mid = left + (right - left) [1] 2;

Drag options to blanks, or click blank then click option'

A*

B/

C+

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplication instead of division.

Adding left and right directly without dividing.

To find the middle index, we add half the distance between left and right to left.

3fill in blank

hard

Fix the error in the condition to check if the left half is sorted.

DSA Rust

if nums[left as usize] [1] nums[mid as usize] {

Drag options to blanks, or click blank then click option'

A<=

B>

C<

D>=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>' excludes equal elements and breaks logic.

Using '<' reverses the condition.

The left half is sorted if the element at left is less than or equal to the element at mid.

4fill in blank

hard

Fill both blanks to update the search boundaries when target is in the left sorted half.

DSA Rust

if target >= nums[left as usize] && target < nums[mid as usize] {
    right = [1];
} else {
    left = [2];
}

Drag options to blanks, or click blank then click option'

Amid - 1

Bmid + 1

Cleft + 1

Dright - 1

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping left and right updates.

Using mid instead of mid ± 1 causes infinite loops.

If target is in left half, move right boundary to mid - 1; else move left boundary to mid + 1.

5fill in blank

hard

Fill all three blanks to update boundaries when right half is sorted and target is checked.

DSA Rust

if target > nums[mid as usize] && target <= nums[[1] as usize] {
    left = [2];
} else {
    right = [3];
}

Drag options to blanks, or click blank then click option'

Aright

Bmid + 1

Cmid - 1

Dleft

Attempts:

3 left

💡 Hint

Common Mistakes

Using left instead of right in comparison.

Updating boundaries incorrectly causing infinite loops.

Check target against right boundary; if in range, move left to mid + 1; else move right to mid - 1.

Practice

1. What is the main challenge when searching for a target 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 sorted in descending order

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: Impact on search

   This split means a normal binary search can't be applied directly because the order is disrupted at the pivot.

3. Final Answer:

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

4. Quick Check:

   Rotated array = two sorted parts [OK]

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

Common Mistakes:

• Assuming the array is fully sorted without rotation
• Ignoring the pivot point in the array
• Thinking duplicates cause the main challenge
• Confusing descending order with rotation

2. Which Rust code snippet correctly declares a function signature to search a target in a rotated sorted array?

easy

A. fn search(nums: &[i32], target: i32) -> Option<usize>

B. fn search(nums: Vec<i32>, target: i32) -> usize

C. fn search(nums: &Vec<i32>, target: i32) -> bool

D. fn search(nums: &[i32], target: i32) -> i32

Solution

1. Step 1: Analyze parameter types

   Using a slice &[i32] is efficient and idiomatic for read-only array input in Rust.

2. Step 2: Analyze return type

   Returning Option<usize> allows indicating if the target was found (Some(index)) or not (None).

3. Final Answer:

   fn search(nums: &[i32], target: i32) -> Option<usize> -> Option A

4. Quick Check:

   Slice input + Option return = fn search(nums: &[i32], target: i32) -> Option<usize> [OK]

Hint: Use &[i32] for input and Option<usize> for index result [OK]

Common Mistakes:

• Using Vec<i32> unnecessarily copies data
• Returning usize without Option loses 'not found' info
• Returning bool loses index information
• Returning i32 index can be ambiguous

3. Given the Rust function below, what is the output when searching for target 3?

fn search(nums: &[i32], target: i32) -> Option<usize> {
    let mut left = 0;
    let mut right = nums.len() - 1;
    while left <= right {
        let mid = (left + right) / 2;
        if nums[mid] == target {
            return Some(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;
            }
        }
    }
    None
}

let arr = [4,5,6,7,0,1,2];
println!("{:?}", search(&arr, 3));

medium

A. None

B. Some(2)

C. Some(4)

D. Some(0)

Solution

1. Step 1: Understand the array and target

   The array is [4,5,6,7,0,1,2], target is 3 which is not present in the array.

2. Step 2: Trace the search logic

   The function performs binary search on rotated array but since 3 is missing, the loop ends returning None.

3. Final Answer:

   None -> Option A

4. Quick Check:

   3 not in array = None [OK]

Hint: If target missing, function returns None [OK]

Common Mistakes:

• Assuming target 3 is present and returning wrong index
• Confusing mid calculation causing infinite loop
• Ignoring rotation logic in conditions
• Returning Some with wrong index

4. Identify the bug in the following Rust code for searching a target in a rotated sorted array:

fn search(nums: &[i32], target: i32) -> Option<usize> {
    let mut left = 0;
    let mut right = nums.len() - 1;
    while left < right {
        let mid = (left + right) / 2;
        if nums[mid] == target {
            return Some(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;
            }
        }
    }
    None
}

medium

A. The function should return bool instead of Option<usize>

B. The mid calculation should use floating division

C. The loop condition should be while left <= right, not while left < right

D. The array should be mutable

Solution

1. Step 1: Analyze loop condition

   The loop uses while left < right, which misses checking when left == right, possibly skipping the last element.

2. Step 2: Correct loop condition

   Changing to while left <= right ensures all elements are checked, including when left equals right.

3. Final Answer:

   The loop condition should be while left <= right, not while left < right -> Option C

4. Quick Check:

   Loop must cover all indices [OK]

Hint: Use while left <= right to cover all elements [OK]

Common Mistakes:

• Using < instead of <= causing missed checks
• Trying floating division for mid index
• Changing return type unnecessarily
• Making array mutable without need

5. You have a rotated sorted array with possible duplicates: [2,2,2,3,4,2]. How would you modify the search algorithm to correctly find target 3?

hard

A. Sort the array before searching

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

C. Use linear search instead of binary search

D. Ignore duplicates and apply normal rotated search

Solution

1. Step 1: Understand duplicates impact

   Duplicates can make it unclear which side is sorted because nums[left], nums[mid], nums[right] may be equal.

2. Step 2: Modify algorithm to skip duplicates

   When nums[left] == nums[mid] == nums[right], increment left and decrement right to skip duplicates and continue search.

3. Step 3: Avoid sorting or linear search

   Sorting changes array order; linear search is inefficient. Proper duplicate handling keeps binary search efficient.

4. Final Answer:

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

5. Quick Check:

   Skip duplicates to maintain binary search [OK]

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

Common Mistakes:

• Sorting array losing rotation info
• Using linear search losing efficiency
• Ignoring duplicates causing wrong results
• Assuming duplicates don't affect logic