Consider the recursive implementation to find the nth fibonacci number:int fibo(int n) if n <= 1 return n return __________ Which line would make the implementation complete?  fibo(n) + fibo(n) fibo(n) + fibo(n – 1)  fibo(n – 1) + fibo(n + 1) fibo(n – 1) + fibo(n – 2)

which of the following program generates a Fibonacci sequence of length 28?A.  def Fibo(n):  if n<=1:    return n  else:    return (Fibo(n-1)+Fibo(n-2)) n= input("Enter number of terms: ")if n<=0:  print(" Check the number entered ")elif:n != 28  print("No sequence ")else:  for i in range(n):    print(Fibo(i))B.  def Fibo(n):  if n<=1:    return n  else:    return (Fibo(n-1)+Fibo(n-2)) n= input("Enter number of terms: ")if n<=0:  print(" Check the number entered ")else:  print("The required sequence is ")  for i in range(n):    print(Fibo(i))C.  def Fibo(n):  if n<=1:    return n  else:    return (Fibo(n-1)+Fibo(n-2)) n= int(input("Enter number of terms: "))#n= t//2if n<=0:  print(" Check the number entered ")else:  print("The required sequence is ")  for i in range(28):    print(Fibo(i)) D.  def Fibo(n):  if n<=1:    return n  else:    return (Fibo(n-1)+Fibo(n-2)) n=int input("Enter number of terms: ")if n<=0:  print(" Check the number entered ")else:  print("The required sequence is ")  for i in range(28):    print(Fibo(i))

What is the space complexity of the recursive implementation used to find the nth fibonacci term? O(1)O(n) O(n2) O(n3)

What correction should be made to the following code to calculate the Fibonacci number correctly?def fib(n): return fib(n-1) + fib(n-2)

A Fibonacci sequence is a sequence of numbers (called Fibonacci numbers) in which each number is the sum of the two preceding ones as following: 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, ... The task is to implement two functions in C a) using recursive function style, F(n) = F(n − 1) + F(n − 2) when n ≥ 2, F(0) = 0, F(1) = 1.

What is the time complexity of this function / algorithm?int Fibonacci(int number){ if (number <= 1) return number; return Fibonacci(number - 2) + Fibonacci(number - 1);}O(n)O(1)O(log(n))O(nlog(n))O(2^n)O(n!)O(n^2)