Fibonacci Using Recursion in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the base case in a recursive Fibonacci function?

The base cases are when n is 0 or 1. For n=0, Fibonacci returns 0; for n=1, it returns 1. These stop the recursion.

beginner

Explain how recursion works in calculating Fibonacci numbers.

The function calls itself twice for n-1 and n-2, then adds the results. This repeats until base cases are reached.

intermediate

What is the time complexity of the naive recursive Fibonacci algorithm?

It is exponential, specifically O(2^n), because it recalculates the same values many times.

beginner

Show the recursive formula used in Fibonacci sequence.

F(n) = F(n-1) + F(n-2) with base cases F(0) = 0 and F(1) = 1.

intermediate

Why is recursion not efficient for large Fibonacci numbers without optimization?

Because it repeats calculations many times, leading to a lot of unnecessary work and slow performance.

What does the Fibonacci recursive function return when n = 0?

A 0

B 1

C n

D Undefined

By definition, Fibonacci(0) = 0 as the base case.

Which two previous Fibonacci numbers does the recursive function add to get F(n)?

A F(n-1) and F(n-3)

B F(n-2) and F(n-3)

C F(n) and F(n-1)

D F(n-1) and F(n-2)

The recursive formula is F(n) = F(n-1) + F(n-2).

What is the main problem with the naive recursive Fibonacci approach?

A It uses too much memory

B It recalculates the same values multiple times

C It does not return correct results

D It only works for even numbers

Naive recursion repeats calculations, causing exponential time complexity.

What is the base case for Fibonacci recursion when n = 1?

A Return n

B Return 0

C Return 1

D Call function again

Fibonacci(1) = 1 is the base case to stop recursion.

Which of these is a better approach to optimize Fibonacci calculation?

A Both A and C

B Using loops instead of recursion

C Using memoization to store results

D None of the above

Both iterative loops and memoization improve efficiency over naive recursion.

Describe how a recursive function calculates the Fibonacci number for n=4.

Think about the tree of calls and how results combine.

Explain why the naive recursive Fibonacci function has exponential time complexity.

Consider how many times the function calls itself.

Practice

1. What does the Fibonacci sequence represent when calculated using recursion?

easy

A. Each number is the square of the previous number

B. Each number is the sum of the two preceding numbers starting from 0 and 1

C. Each number is the difference between the two preceding numbers

D. Each number is the product of the two preceding numbers

Solution

1. Step 1: Understand Fibonacci sequence definition

   The Fibonacci sequence starts with 0 and 1, and each next number is the sum of the two before it.

2. Step 2: Relate to recursion

   Recursion calls the function for the two previous numbers and adds their results to get the current number.

3. Final Answer:

   Each number is the sum of the two preceding numbers starting from 0 and 1 -> Option B

4. Quick Check:

   Fibonacci = sum of two previous numbers [OK]

Hint: Fibonacci adds last two numbers recursively [OK]

Common Mistakes:

• Thinking Fibonacci multiplies previous numbers
• Confusing subtraction or squares with Fibonacci
• Ignoring the base cases 0 and 1

2. Which of the following is the correct base case for a recursive Fibonacci function in C++?

easy

A. if (n == 1) return 0; if (n == 2) return 1;

B. if (n <= 2) return n;

C. if (n == 0) return 0; if (n == 1) return 1;

D. if (n == 0) return 1; if (n == 1) return 1;

Solution

1. Step 1: Identify correct Fibonacci base cases

   Fibonacci sequence starts with 0 at position 0 and 1 at position 1, so base cases must return these values.

2. Step 2: Match base cases to code

   if (n == 0) return 0; if (n == 1) return 1; correctly returns 0 for n=0 and 1 for n=1, matching Fibonacci definition.

3. Final Answer:

   if (n == 0) return 0; if (n == 1) return 1; -> Option C

4. Quick Check:

   Base cases match Fibonacci start [OK]

Hint: Base cases: 0 returns 0, 1 returns 1 [OK]

Common Mistakes:

• Using wrong base values like 1 for n=0
• Returning n for n <= 2 which is incorrect
• Confusing base cases with general recursive step

3. What is the output of the following C++ code?

int fib(int n) {
  if (n == 0) return 0;
  if (n == 1) return 1;
  return fib(n-1) + fib(n-2);
}

int main() {
  std::cout << fib(5);
  return 0;
}

medium

A. 5

B. 8

C. 3

D. 13

Solution

1. Step 1: Calculate fib(5) using recursion

   fib(5) = fib(4) + fib(3). Calculate fib(4) = fib(3) + fib(2), fib(3) = fib(2) + fib(1), and so on until base cases.

2. Step 2: Evaluate values step-by-step

   fib(0)=0, fib(1)=1, fib(2)=1, fib(3)=2, fib(4)=3, fib(5)=5.

3. Final Answer:

   5 -> Option A

4. Quick Check:

   fib(5) = 5 [OK]

Hint: Remember fib(5) = 5 in Fibonacci sequence [OK]

Common Mistakes:

• Calculating fib(5) as 8 or 13 by mistake
• Confusing index starting point
• Skipping base cases in calculation

4. Identify the error in this recursive Fibonacci function:

int fib(int n) {
  if (n == 0) return 0;
  if (n == 1) return 1;
  return fib(n-2) + fib(n-1);
}

medium

A. No error, function is correct

B. The recursive calls are in wrong order; should be fib(n-1) + fib(n-2)

C. Base cases are incorrect

D. Missing return type in function

Solution

1. Step 1: Check base cases

   Base cases for n==0 return 0 and n==1 return 1 are correct for Fibonacci.

2. Step 2: Check recursive step

   fib(n-2) + fib(n-1) equals fib(n-1) + fib(n-2) because addition is commutative. Function computes correct values. No error.

3. Final Answer:

   No error, function is correct -> Option A

4. Quick Check:

   Addition commutative, no error [OK]

Hint: Addition order irrelevant, commutative [OK]

Common Mistakes:

• Thinking recursive call order must be strictly n-1 first
• Assuming reversed order changes the result
• Overlooking commutativity of addition

5. How many times is the function fib called when computing fib(4) using the recursive function below?

int fib(int n) {
  if (n == 0) return 0;
  if (n == 1) return 1;
  return fib(n-1) + fib(n-2);
}

hard

A. 5

B. 7

C. 15

D. 9

Solution

1. Step 1: Trace calls for fib(4)

   fib(4) calls fib(3) and fib(2). fib(3) calls fib(2) and fib(1). fib(2) calls fib(1) and fib(0).

2. Step 2: Count total calls

   Calls: fib(4), fib(3), fib(2), fib(1), fib(2), fib(1), fib(0), fib(1), fib(0) = 9 calls total.

3. Final Answer:

   9 -> Option D

4. Quick Check:

   Count recursive calls carefully = 9 [OK]

Hint: Count each fib call including duplicates [OK]

Common Mistakes:

• Counting only unique calls
• Ignoring repeated calls for same n
• Underestimating recursion tree size