def f1(n):
    while n > 0:
        print(“I love computer science”)
        n=n-1
    return n
Θ(n) - n iterations of the while loop

def f2(n):
    while n > 0:
        print(“I love 61A”)
        n = n * 2
    return n
Θ(logn) - Instead of n iterations of the while loop, there are logn because each iteration, n gets multiplied by 2, rather than incremented by 1

def f3(n):
    m = 100000
    while m > 0:
        n=n+1
        m=m-1
    return n
Θ(1) - The while loop is based off of m and m is always 100000

def f4(n):
    if n <= 0:
        return 0
    else:
        return f4(n - 1) + f4(n - 1)
Θ(2ⁿ) - You can draw out a tree of recursive calls where each node splits into two new ones. The tree has height n, so you have 2ⁿ + (2ⁿ - 1) + .... + 1 runs of the function, which gives 2ⁿ