2025-12-05 14:29:01

1. Description

This report presents benchmark results for computing Fibonacci numbers using different methods. We compare recursive and iterative implementations for various input sizes.

1.1. Session

  • Hostname: feelpp2

  • User: feelpp2

  • Time Start: 20251205T142905+0100

  • Time End: 20251205T142930+0100

1.2. Cases

  • Total: 14

  • Failures: 0

  • Runs: 1

2. Parametrization

Hash n method Total Time (s)

🟢

22f2a7df

25

recursive

0.422

Logs

🟢

38ccb5ca

25

iterative

0.430

Logs

🟢

3ef797fb

40

recursive

17.471

Logs

🟢

43216008

35

recursive

1.873

Logs

🟢

6931b0f8

20

iterative

0.427

Logs

🟢

6989b2c3

10

recursive

0.446

Logs

🟢

6bbe229f

35

iterative

0.421

Logs

🟢

7052aba9

15

recursive

0.426

Logs

🟢

878bea9a

30

recursive

0.573

Logs

🟢

8e3ffe4e

30

iterative

0.421

Logs

🟢

c24c7889

10

iterative

0.420

Logs

🟢

c2de7935

40

iterative

0.429

Logs

🟢

c86ef9ce

20

recursive

0.424

Logs

🟢

fe2310b7

15

iterative

0.424

Logs

3. Complexity Analysis

3.1. Time Complexity

The plot above shows execution time for each Fibonacci method as a function of input size N. Recursive implementation grows exponentially, while iterative grows linearly.