LeetCodee

509. Fibonacci Number

Jump to Solution: Python Java C++ JavaScript C#

Problem Description

The Fibonacci numbers, commonly denoted F(n) form a sequence, called the Fibonacci sequence, such that each number is the sum of the two preceding ones, starting from 0 and 1. That is,

  • F(0) = 0, F(1) = 1
  • F(n) = F(n - 1) + F(n - 2), for n > 1.

Given n, calculate F(n).

Example 1:

Input: n = 2
Output: 1
Explanation: F(2) = F(1) + F(0) = 1 + 0 = 1.

Example 2:

Input: n = 3
Output: 2
Explanation: F(3) = F(2) + F(1) = 1 + 1 = 2.

Example 3:

Input: n = 4
Output: 3
Explanation: F(4) = F(3) + F(2) = 2 + 1 = 3.

Constraints:

  • 0 <= n <= 30

Solution

Python Solution

class Solution:
    def fib(self, n: int) -> int:
        if n <= 1:
            return n
        
        a, b = 0, 1
        for _ in range(2, n + 1):
            a, b = b, a + b
        
        return b

Time Complexity: O(n)

Where n is the input number. We need to iterate n times.

Space Complexity: O(1)

We only use two variables regardless of the input size.

Java Solution

class Solution {
    public int fib(int n) {
        if (n <= 1) {
            return n;
        }
        
        int a = 0, b = 1;
        for (int i = 2; i <= n; i++) {
            int temp = b;
            b = a + b;
            a = temp;
        }
        
        return b;
    }
}

Time Complexity: O(n)

Where n is the input number. We need to iterate n times.

Space Complexity: O(1)

We only use two variables regardless of the input size.

C++ Solution

class Solution {
public:
    int fib(int n) {
        if (n <= 1) {
            return n;
        }
        
        int a = 0, b = 1;
        for (int i = 2; i <= n; i++) {
            int temp = b;
            b = a + b;
            a = temp;
        }
        
        return b;
    }
};

Time Complexity: O(n)

Where n is the input number. We need to iterate n times.

Space Complexity: O(1)

We only use two variables regardless of the input size.

JavaScript Solution

/**
 * @param {number} n
 * @return {number}
 */
var fib = function(n) {
    if (n <= 1) {
        return n;
    }
    
    let a = 0, b = 1;
    for (let i = 2; i <= n; i++) {
        [a, b] = [b, a + b];
    }
    
    return b;
};

Time Complexity: O(n)

Where n is the input number. We need to iterate n times.

Space Complexity: O(1)

We only use two variables regardless of the input size.

C# Solution

public class Solution {
    public int Fib(int n) {
        if (n <= 1) {
            return n;
        }
        
        int a = 0, b = 1;
        for (int i = 2; i <= n; i++) {
            int temp = b;
            b = a + b;
            a = temp;
        }
        
        return b;
    }
}

Time Complexity: O(n)

Where n is the input number. We need to iterate n times.

Space Complexity: O(1)

We only use two variables regardless of the input size.

Approach Explanation

The solution uses an iterative approach with constant space:

  1. Key Insights:
    • Base cases
    • Variable swapping
    • Iterative approach
    • Space optimization
  2. Algorithm Steps:
    • Handle base cases
    • Initialize variables
    • Iterate and update
    • Return result

Implementation Details:

  • Variable tracking
  • Efficient swapping
  • Loop control
  • Memory usage

Optimization Insights:

  • Constant space
  • No recursion
  • Early returns
  • Minimal variables

Edge Cases:

  • n = 0
  • n = 1
  • n = 2
  • Maximum n