Another happy quickcheck customer
Even when I announced overflower, I confessed to lacking tests for the support library. Since the code is fairly simple, I am of acceptable confidence that it’ll work, but I’d sleep more soundly if this stuff really was tested.
I could of course craft known-good inputs to test the functions, but then I’d miss out on the unknown inputs, good or bad. I also always wanted to try quickcheck, and this is the perfect opportunity.
To sum it up, quickcheck rocks. And
overflow_support does what I want. If
that’s all you wanted to know, you can stop reading here.
Still here? Cool.
Quickcheck contains a lot of cleverness so you can simply write a predicate
function for some input type which has an
Arbitrary implementation (which
already covers the usual suspect types and is easy to extend), and call
quickcheck::quickcheck(_) on that function (to be fair, you’ll need to
explicitly cast to the
fn(..) -> _ type for that to work). There’s even a
plugin that lets you annotate your predicate functions with
directly which turns them into quickcheck-using tests (I didn’t test it though,
because the direct way worked good enough for me).
However, there was one slight wrinkle: Since some of my methods under test
panic, I needed to deal with that. Luckily,
turn panics into results (with earlier Rust versions, I could have used a
thread). Unfortunately, the panic handler which prints a message (and
optionally a stack trace) gets called regardless.
So I tried to silence the panics (cue odyssey). This is just a bit more complicated because the tests run in parallel, and you cannot depend on execution order to reliably distinguish quickcheck panics (which contain the reduced test inputs, thus we want them on standard output) and caught panics from my tests.
In the end, I relied on the fact that my tests only threw errors from two
src/lib.rs and somewhere in
num for overflow). Whie this is a
brittle and very specific solution, it works well enough for me.
Quickcheck is plenty fast, given that it generates 100 random inputs and runs your test code with each of them. Even with the 100 random executions, quickcheck may sometimes miss an error in the tests. However, over a few runs, I’m fairly confident that finding more errors by chance is very unlikely.
So if you have any non-trivial project that could benefit from more test coverage, give quickcheck a try. Even with fairly uncommon scenarios like mine, using quickcheck really is quick – writing all those tests by hand would’ve been prohibitively time-consuming.