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This approach utilizes the fact that both arrays are sorted. Using two pointers, one for each array, we traverse the arrays to find the smallest common value:
Time Complexity: O(n + m), where n and m are the lengths of the two arrays. We only traverse each array once.
Space Complexity: O(1), no additional space is used apart from a few variables.
1def find_min_common_value(nums1, nums2):
2 i, j = 0, 0
3 while i < len(nums1) and j < len(nums2):
Using Python's list indexing and a simple while-loop structure similar to other languages, this solution finds the minimum common element using the two-pointer technique efficiently.
This approach uses a HashSet to store the elements of the smaller array, providing a quick way to check for common elements:
Time Complexity: O(n log n + m), mainly due to qsort and possibly bsearch in the worst case scenario per element in the second array.
Space Complexity: O(n), additional space used for sorting elements.
using System.Collections.Generic;
public class Program
{
public static int FindMinCommonValue(int[] nums1, int[] nums2)
{
HashSet<int> set = new HashSet<int>(nums1);
foreach (int num in nums2)
{
if (set.Contains(num))
return num;
}
return -1;
}
public static void Main()
{
int[] nums1 = {1, 2, 3};
int[] nums2 = {2, 4};
Console.WriteLine(FindMinCommonValue(nums1, nums2));
}
}The C# solution uses HashSet to achieve efficient membership testing. Elements from one array are inserted into the set, and then the second array is iterated with constant time membership tests.