Profile the performance of the memoized version of the Fibonacci function defined in Project 6. The function should count the number of recursive calls. State its computational complexity using big-O...

Profile the performance of the memoized version of the Fibonacci function defined in Project 6. The function should count the number of recursive calls. State its computational complexity using big-O notation, and justify your answer.

(i). The function makeRandomList creates and returns a list of numbers of a given size (its argument). The numbers in the list are unique and range from 1 through the size. They are placed in random order. Here is the code for the function:

def makeRandomList(size):

lyst = []

for count in range(size):

while True:

number = random.randint(1, size)

if not number in lyst:

lyst.append(number) break return lyst

You can assume that range, randint, and append are constant time functions. You can also assume that random randint more rarely returns duplicate numbers as the range between its arguments increases. State the computational complexity of this function using big-O notation, and justify your answer.