Fibonacci Using DP in DSA C - Time & Space Complexity

Time Complexity: Fibonacci Using DP

O(n)

Understanding Time Complexity

We want to understand how fast the Fibonacci sequence calculation runs when using dynamic programming.

Specifically, how the number of steps grows as the input number increases.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int fibonacci(int n) {
    int dp[n+1];
    dp[0] = 0;
    dp[1] = 1;
    for (int i = 2; i <= n; i++) {
        dp[i] = dp[i-1] + dp[i-2];
    }
    return dp[n];
}
    

This code calculates the nth Fibonacci number by storing previous results to avoid repeated work.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The for-loop that runs from 2 to n, calculating each Fibonacci number once.
• How many times: Exactly n-1 times, once for each number from 2 up to n.

How Execution Grows With Input

Each new Fibonacci number is calculated once using two previous results, so work grows steadily with n.

Input Size (n)	Approx. Operations
10	About 8 additions
100	About 98 additions
1000	About 998 additions

Pattern observation: The number of operations grows roughly in a straight line as n increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to compute the Fibonacci number grows directly in proportion to the input size.

Common Mistake

[X] Wrong: "Calculating Fibonacci with recursion is always fast because it just calls itself."

[OK] Correct: Simple recursion repeats many calculations, making it much slower than this dynamic programming approach.

Interview Connect

Understanding how dynamic programming improves speed by saving past results is a key skill that shows you can optimize solutions thoughtfully.

Self-Check

"What if we changed the array to only store the last two Fibonacci numbers instead of all? How would the time complexity change?"

Practice

1. What is the main advantage of using Dynamic Programming (DP) to calculate Fibonacci numbers compared to a simple recursive approach?

easy

A. It stores intermediate results to avoid repeated calculations

B. It uses more memory without improving speed

C. It calculates Fibonacci numbers randomly

D. It only works for small Fibonacci numbers

Solution

1. Step 1: Understand recursion vs DP

   Simple recursion recalculates the same Fibonacci numbers many times, causing slow performance.

2. Step 2: Role of DP in Fibonacci

   DP saves previously calculated Fibonacci values in a table (memoization or tabulation), avoiding repeated work.

3. Final Answer:

   It stores intermediate results to avoid repeated calculations -> Option A

4. Quick Check:

   DP = stores results to save time [OK]

Hint: DP saves past answers to speed up Fibonacci [OK]

Common Mistakes:

• Thinking DP uses more memory without speed benefit
• Believing DP calculates numbers randomly
• Assuming DP only works for small inputs

2. Which of the following is the correct way to initialize the base cases in a bottom-up DP approach for Fibonacci in C?

easy

A. int fib[2] = {0, 0};

B. int fib[2] = {1, 1};

C. int fib[2] = {0, 1};

D. int fib[2] = {1, 0};

Solution

1. Step 1: Identify Fibonacci base cases

   Fibonacci sequence starts with fib(0) = 0 and fib(1) = 1.

2. Step 2: Match initialization with base cases

   Array fib[2] = {0, 1} correctly sets fib(0) = 0 and fib(1) = 1.

3. Final Answer:

   int fib[2] = {0, 1}; -> Option C

4. Quick Check:

   Base fib = 0,1 [OK]

Hint: Start fib with 0 and 1 for base cases [OK]

Common Mistakes:

• Swapping the order of 0 and 1
• Setting both base cases to 1
• Initializing both to zero

3. What is the output of the following C code snippet using bottom-up DP to find fib(5)?

int fib[6];
fib[0] = 0;
fib[1] = 1;
for(int i = 2; i <= 5; i++) {
    fib[i] = fib[i-1] + fib[i-2];
}
printf("%d", fib[5]);

medium

A. 5

B. 8

C. 3

D. 13

Solution

1. Step 1: Calculate Fibonacci values step-by-step

   fib[0]=0, fib[1]=1 fib[2]=1, fib[3]=2, fib[4]=3, fib[5]=5

2. Step 2: Identify fib[5]

   fib[5] is 5 after the loop completes.

3. Final Answer:

   5 -> Option A

4. Quick Check:

   fib(5) = 5 [OK]

Hint: Calculate fib stepwise from 0 and 1 [OK]

Common Mistakes:

• Confusing fib(5) with fib(6)
• Starting loop from wrong index
• Off-by-one errors in array indexing

4. Identify the error in this DP Fibonacci code snippet and select the correct fix:

int fib[10];
fib[0] = 0;
fib[1] = 1;
for(int i = 1; i < 10; i++) {
    fib[i] = fib[i-1] + fib[i-2];
}

medium

A. Initialize fib[2] before loop

B. Change loop to start from i = 2

C. Change loop condition to i <= 10

D. No error, code is correct

Solution

1. Step 1: Analyze loop start index

   The loop starts at i=1, but fib[1] is already initialized, so fib[1] gets overwritten incorrectly.

2. Step 2: Correct loop start

   Loop should start at i=2 to use fib[0] and fib[1] for calculation without overwriting base cases.

3. Final Answer:

   Change loop to start from i = 2 -> Option B

4. Quick Check:

   Loop start = 2 fixes overwrite [OK]

Hint: Start loop after base cases to avoid overwrite [OK]

Common Mistakes:

• Starting loop at 1 overwrites fib[1]
• Not initializing base cases properly
• Using wrong loop end condition

5. You want to find the 10th Fibonacci number using DP but with optimized space using only two variables instead of an array. Which code snippet correctly implements this?

hard

A. int a = 0, b = 1, c, n = 10;
for(int i = 0; i < n; i++) {
c = a + b;
a = c;
b = a;
}
printf("%d", c);

B. int a = 0, b = 1, c, n = 10;
for(int i = 1; i < n; i++) {
c = a + b;
b = a;
a = c;
}
printf("%d", a);

C. int a = 1, b = 1, c, n = 10;
for(int i = 2; i <= n; i++) {
c = a + b;
a = b;
b = c;
}
printf("%d", c);

D. int a = 0, b = 1, c, n = 10;
for(int i = 2; i <= n; i++) {
c = a + b;
a = b;
b = c;
}
printf("%d", b);

Solution

1. Step 1: Understand space optimization

   Only two variables (a, b) track last two Fibonacci numbers; c stores current sum.

2. Step 2: Check loop and updates

   Loop from 2 to n, update c = a + b, then shift a = b, b = c correctly to move forward.

3. Final Answer:

   Code snippet A correctly implements optimized Fibonacci calculation -> Option D

4. Quick Check:

   Two vars + sum update = correct [OK]

Hint: Use two vars and update in loop for space optimization [OK]

Common Mistakes:

• Swapping updates of a and b incorrectly
• Wrong loop range causing off-by-one errors
• Initializing variables incorrectly