Consider the following recursive algorithm. Algorithm Mystery A[0..n-1]) //Input: An array A[0..n - 1] of real numbers if n = 1 return A[0] else temp← Riddle(A[0..n -2]) if temp ≤ A[n 1] return temp else return A[n - 1] a. What does this algorithm compute? b. What is its input size? c. What is its basic operation? d. Set up a recurrence relation for the algorithm's basic operation count and solve it. e. What is the efficiency class of this algorithm?

You want to design an algorithm, called minMax(A,p,r), that takes an array of integers and indexes of the first and last elements, and returns the minimum and maximum values in that range. Now write the pseudo code of a divide and conquer (and therefore, recursive) algorithm with the same time complexity (Θ(n)). You can assume that p ≤ r. Also, in your code, you can return two numbers by returning a pair, e.g. "return (a, b)", and can save the output in a similar way, e.g. "(a, b) = minMax(parameters)". (Short answer please)

Write the algorithm which finds the second maximum value of the array. Then find the complexity of the algorithm as Big O notation

Consider the algorithm given below. ALGORITHM MinDistance(A[0..n − 1]) //Input: Array A[0..n − 1] of numbers //Output: Minimum distance between two of its elements dmin←∞ for i ←0 to n − 1 do for j ←0 to n − 1 do if i != j and |A[i]− A[j ]| < dmin dmin ←|A[i]− A[j ]| return dminif n = 20, and the list is sorted in descending order, then the loop " or i ←0 to n − 1 do " will be executed ______ times.

Given n arrays, each array contain n positive integers. Write an O (n2 log n) algorithm to find the smallest n sums out of nn possible sums that can be obtained by picking one positive integer from each of n arrays. For example, given three arrays as follows: [5, 1, 8], [5, 2,9], and [6,7, 10]. The smallest n sums of the given array is [9, 10, 12].