-
Notifications
You must be signed in to change notification settings - Fork 243
Count Rotations
Unit 7 Session 2 (Click for link to problem statements)
- 💡 Difficulty: Medium
- ⏰ Time to complete: 20 mins
- 🛠️ Topics: Binary Search, Arrays, Rotations
Understand what the interviewer is asking for by using test cases and questions about the problem.
- Established a set (2-3) of test cases to verify their own solution later.
- Established a set (1-2) of edge cases to verify their solution handles complexities.
- Have fully understood the problem and have no clarifying questions.
- Have you verified any Time/Space Constraints for this problem?
- Q: What happens if the array has not been rotated?
- A: If the array has not been rotated, the function should return 0 as the array's minimum element will be at the first index.
HAPPY CASE
Input: [11, 12, 15, 18, 2, 5, 6, 8]
Output: 4
Explanation: The array has been rotated 4 times (the minimum element, 2, is at index 4).
EDGE CASE
Input: [2, 5, 6, 8, 11, 12, 15, 18]
Output: 0
Explanation: The array is not rotated (the minimum element is at index 0).
Match what this problem looks like to known categories of problems, e.g. Linked List or Dynamic Programming, and strategies or patterns in those categories.
This problem is a variant of binary search, adapted to detect the number of rotations in a circularly sorted array:
- Adapting binary search to find the point of minimum value, which indicates the number of rotations.
Plan the solution with appropriate visualizations and pseudocode.
General Idea: Use binary search to find the index of the minimum element in the array, which corresponds to the number of rotations.
1) Establish pointers for the beginning (`low`) and end (`high`) of the array.
2) If the element at `low` is less than or equal to the element at `high`, the array is not rotated.
3) Use a loop to continue searching as long as `low` is less than `high`:
- Calculate the middle index (`mid`).
- Check the relationship between `mid`, `low`, and `high` to determine the unsorted part:
- If the element at `mid` is greater than the element at `high`, the rotation is in the right half, set `low` to `mid + 1`.
- Otherwise, set `high` to `mid`.
4) At the end of the loop, `low` will point to the smallest element, which is the number of rotations.
- Incorrectly identifying the sorted and unsorted parts of the array, which could lead to missing the minimum element.
Implement the code to solve the algorithm.
def count_rotations(nums):
low, high = 0, len(nums) - 1
while low <= high:
if nums[low] <= nums[high]: # Array is sorted, no rotation
return low
mid = (low + high) // 2
next_index = (mid + 1) % len(nums) # circular indexing
prev_index = (mid - 1 + len(nums)) % len(nums) # circular indexing
# Check if the mid element is the minimum element
if nums[mid] <= nums[next_index] and nums[mid] <= nums[prev_index]:
return mid
elif nums[mid] > nums[high]:
low = mid + 1 # Min must be in the right unsorted portion
else:
high = mid - 1 # Min must be in the left unsorted portion
return 0 # This return is technically unreachable due to the logic
Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.
- Test the function with input [11, 12, 15, 18, 2, 5, 6, 8] to ensure it returns 4.
- Validate with a non-rotated input [2, 5, 6, 8, 11, 12, 15, 18] to confirm that it correctly identifies 0 rotations.
Evaluate the performance of your algorithm and state any strong/weak or future potential work.
-
Time Complexity:
O(log n)
because each iteration of the loop narrows the search range by about half. -
Space Complexity:
O(1)
as it uses a constant amount of space.