Problem 3. Collaborative filtering is a technique for generating recommendations, such as sugges- tions for products, songs, movies, news stories, and so on. The idea is to identify other users who have similar preferences, and recommend to you things that have been popular with them. It requires a formal notion of similarity between users, and some of the essence of this is captured by the problem of counting the number of inversions in an array. An inversion in an array A[1, ..., n) is a pair of indices (i, j) such that i A[j]. For example, in the array A = (1, 3, 5, 2, 4,6], there are three inversions, 5 and 2 (corresponding to i = 3 and j = 4), 3 and the 2, and the 5 and the 4. For this problem we will count the number of inversions in an array of size n. (a) Write pseudo-code for an efficient brute force algorithm to find the total number of inver- sions in the worst-case. Find the exact number of inversions. Show your work. (b) Write pseudo-code for an optimal algorithm to find the total number of inversions in the worst-case. What is the asymptotic runtime of your algorithm