Big O Notation HW Aarush Gowda

Big O Notation Submission

O(1) – Constant Time

This function always runs in the same time, no matter how big the list is.

def print_hello():
    print("Hello, world!")

# Example
print_hello()

O(log n) – Logarithmic Time

This example keeps dividing the number by 2 until it becomes 1.

def divide_until_one(n):
    while n > 1:
        n = n // 2
        print(n)

# Example
divide_until_one(32)

O(n) – Linear Time

This function prints every number from 1 to n.

def print_numbers(n):
    for i in range(1, n + 1):
        print(i)

# Example
print_numbers(10)

O(n²) – Quadratic Time

This function checks if any two elements in the list add up to 10.

def has_sum_ten(lst):
    for i in lst:
        for j in lst:
            if i + j == 10:
                return True
    return False

# Example
print(has_sum_ten([1, 3, 7, 2, 5]))