"ALGORITHM Riddle"(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. Set up a recurrence relation for the al

In many applications, only a small percentage of the points in a given set p of n points are extreme. in such a case, the convex hull of p has less than n vertices. this can actually make our algorithm convexhull run faster than θ(nlogn). assume, for instance, that the expected number of extreme points in a random sample of p of size r is o(rα ), for some constant α < 1. (this is true when the set p has been created by picking points uniformly at random in a ball.) prove that under this condition, the running time of the algorithm is o(n).