Test-driven development of random algorithms

[Steven D'Aprano]

I'm working on some functions that, essentially, return randomly generated
strings. Here's a basic example:

def rstr():
    """Return a random string based on a pseudo 
    normally-distributed random number.
    """
    x = 0.0
    for i in range(12):
        x += random.random()
    return str(int(x)+6))

I want to do test-driven development. What should I do? Generally, any
test I do of the form

assert rst() == '1'

will fail more often than not (about 85% of the time, by my estimate). An
easy work around would be to do this:

assert rstr() in [str(n) for n in range(-6, 6)]

but (1) that doesn't scale very well (what if rstr() could return one of
a billion different strings?) and (2) there could be bugs which only show
up probabilistically, e.g. if I've got the algorithm wrong, rstr() might
return '6' once in a while.

Does anyone have generic advice for the testing and development of this
sort of function?


-- 
Steven D'Aprano