Fibonacci Using Recursion in DSA C++ - Time & Space Complexity

Time Complexity: Fibonacci Using Recursion

O(2^n)

Understanding Time Complexity

We want to understand how the time taken by the recursive Fibonacci function grows as the input number increases.

Specifically, how many steps does it take to find the nth Fibonacci number?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int fibonacci(int n) {
  if (n <= 1) return n;
  return fibonacci(n - 1) + fibonacci(n - 2);
}
    

This code calculates the nth Fibonacci number by calling itself twice for smaller values until it reaches the base cases.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Two recursive calls per function call.
• How many times: Each call splits into two more calls until reaching base cases, causing many repeated calculations.

How Execution Grows With Input

Each number requires calculating two smaller Fibonacci numbers, which themselves require two smaller calls, and so on.

Input Size (n)	Approx. Operations
10	About 177 calls
20	About 21,891 calls
30	About 2,692,537 calls

Pattern observation: The number of calls grows very fast, roughly doubling with each increase in n.

Final Time Complexity

Time Complexity: O(2^n)

This means the time needed roughly doubles every time n increases by one, making it very slow for large n.

Common Mistake

[X] Wrong: "The recursive Fibonacci runs in linear time because it just counts down from n to 0."

[OK] Correct: Each call makes two more calls, so the total number of calls grows exponentially, not linearly.

Interview Connect

Understanding this recursive pattern helps you recognize when recursion leads to repeated work and why optimization or different approaches are needed.

Self-Check

"What if we add memoization to store results of previous calls? How would the time complexity change?"

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