Recursion and Data Structures Quiz

What is the base case in recursion?

• The case where the function calls itself

• The condition that stops further recursive calls

• The first step in the recursive function

• A case where infinite recursion occurs

What happens if a recursive function lacks a proper base case?

• It will execute normally

• It will result in infinite recursion leading to a stack overflow

• It will execute but return None

• It will compile but not run

Consider the following recursive function: def mystery(n): if n == 0: return 1 return n * mystery(n - 1) What does mystery(5) return?

• 5

• 24

• 120

• 25

Which of the following recursive functions correctly calculates the sum of digits of a number?

• def sum_of_digits(n): return sum_of_digits(n // 10) + n % 10

• def sum_of_digits(n): if n == 0: return 0 return sum_of_digits(n // 10) + n % 10

• def sum_of_digits(n): if n < 0: return 0 return sum_of_digits(n - 1) + n % 10

• None of the above

Which data structure is used for handling recursive function calls internally?

• Queue

• Stack

• Linked List

• Heap

What is the time complexity of a naive recursive Fibonacci function?

• O(n)

• O(n²)

• O(2ⁿ)

• O(log n)

Which of the following approaches optimizes recursive Fibonacci using memoization?

• Storing computed values in an array and reusing them

• Using a loop instead of recursion

• Using an explicit stack

• Removing the base case

What is the result of the following code? def factorial(n): if n == 1: return 1 return n * factorial(n - 1) print(factorial(4))

• 24

• 12

• 10

• 4

Which of the following is not a correct way to compute the Fibonacci sequence?

• def fib(n): if n == 0 or n == 1: return n return fib(n - 1) + fib(n - 2)

• def fib(n): a, b = 0, 1 for _ in range(n): a, b = b, a + b return a

• def fib(n): return fib(n-1) * fib(n-2)

• Using dynamic programming

What is the space complexity of the recursive Fibonacci function (without memoization)?

• O(n)

• O(1)

• O(2ⁿ)

• O(n²)