LC 153. Find Minimum in Rotated Sorted Array

Alen Alex · February 10, 2024

LeetCode Link: 153. Find Minimum in Rotated Sorted Array
Language: C#

Problem Statement

Suppose an array of length n sorted in ascending order is rotated between 1 and n times. For example, the array nums = [0,1,2,4,5,6,7] might become:

[4,5,6,7,0,1,2] if it was rotated 4 times. [0,1,2,4,5,6,7] if it was rotated 7 times. Notice that rotating an array [a[0], a[1], a[2], …, a[n-1]] 1 time results in the array [a[n-1], a[0], a[1], a[2], …, a[n-2]].

Given the sorted rotated array nums of unique elements, return the minimum element of this array.

You must write an algorithm that runs in O(log n) time.

Examples

Example 1:

Input: nums = [3,4,5,1,2]
Output: 1
Explanation: The original array was [1,2,3,4,5] rotated 3 times.

Example 2:

Input: nums = [4,5,6,7,0,1,2]
Output: 0
Explanation: The original array was [0,1,2,4,5,6,7] and it was rotated 4 times.

Example 3:

Input: nums = [11,13,15,17]
Output: 11
Explanation: The original array was [11,13,15,17] and it was rotated 4 times.

Constraints

  • n == nums.length
  • 1 <= n <= 5000
  • -5000 <= nums[i] <= 5000
  • All the integers of nums are unique.
  • nums is sorted and rotated between 1 and n times.

Solution

public class Solution 
{
    public int FindMin(int[] nums) 
    {
        var left = 0;
        var right = nums.Length - 1;

        if (nums[0] < nums[right])
        {
            return nums[0];
        }

        while (left <= right)
        {
            var mid = (left + right) / 2;            

            if (mid > 0 && nums[mid] < nums[mid - 1] )
            {
                return nums[mid];
            }
            if (mid < nums.Length - 1 && nums[mid] > nums[mid + 1])
            {
                return nums[mid + 1];
            }
            
            if (nums[left] > nums[mid])
            {
                right = mid - 1;
            }
            else
            {
                left = mid + 1;
            }

        }

        return nums[0];
    }    
}

Complexity

Time Complexity: O(logN)
Space Complexity: O(1)

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