intersectionOfArrays.md

Description: Given two integer arrays nums1 and nums2, return an array of their intersection in such away that each element in the result must be unique.

Note: The elements in result can appear in any order.

Examples

Example 1:

Input: nums1 = [5,3,3,5], nums2 = [5,3] Output: [ 5, 3 ]

Example 2:

Input: nums1 = [1, 3, 5], nums2 = [2, 4] Output: [ ]

Algorithmic Steps This problem is solved with the help of set data structure and array traversal over the elements. The algorithmic approach can be summarized as follows:

1. Create a function named intersection, which accepts input arrays(nums1 and nums2) to find the intersection of elements.

2. Define a set data structure named set which stores the elements of nums1. Create a result list(result) to return the intersection of elements.

3. Iterate over first array(nums1) and add each element to a set.

4. Iterate over second array(nums2) and add an element to result list if that element exists in a set. Also, remove the same element from set to avoid adding duplicate elements to result list.

5. Return the result array which has intersection of elements.

Time and Space complexity: This algorithm has a time complexity of O(n1+n2), where n1 is the number of elements in first array and n2 is the number of elements in second array. This is because we need to iterate over all the elements of first array to insert them into a set with a time complexity of O(n1). At the same time, we need to iterate over each element of second array to find the intersected elements. Hence, total time complexity is O(n1+n2).

It takes constant time complexity of O(n1+n2). This is due to hash set usage with a space complexity of O(n1)and O(min(n1+n2)) if all the elements of one array exists in another array.