The drawback of this approach, is that with each recursive function call, we only reduce the size of the array by one element, and we use a storage space for one activation record. A faster approach...

The drawback of this approach, is that with each recursive function call, we only reduce the

size of the array by one element, and we use a storage space for one activation record. A

faster approach is, with each recursive call, reduce the size of the array by 3 elements.

a. Write a reduce-and-conquer recursive function FastRecSum()(C++ or python) that find

the sum of all float (real) elements in an array of size n.

b. Using addition of float (real) values as a basic operation, set up and solve a recurrence

relationship to compute the complexity of your code, as a function of the size n of the array.