Test-driven development of random algorithms
steve at REMOVEME.cybersource.com.au
Tue Nov 14 04:25:54 CET 2006
I'm working on some functions that, essentially, return randomly generated
strings. Here's a basic example:
"""Return a random string based on a pseudo
normally-distributed random number.
x = 0.0
for i in range(12):
x += random.random()
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?
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