Testing for type stability regressions


Is there a standard way of testing for regressions in type stability?

Currently I manually check there are no unions etc in @code_warntype, but it would be preferable if that was a test.


Base.Test.@inferred? It returns the value of the expression, so you can sprinkle it in your runtests.jl file, like @test @inferred(f(12)) == 12


I’ve been using that, but it seems that it doesn’t really check that all the code generated is type stable, just that the result is?

@inferred might pass just fine but @code_warntype can still show a whole lot of Union types. Maybe I need to be more specific in how I’m using it. It just seemed like there could be a general test of stability for a whole block of code, not just the result.


Perhaps https://github.com/MikeInnes/Traceur.jl can help? In its current form, it just prints out issues like type-instability, but I’m sure it could be adapted to act as a unit test.


There is an open PR

and a package

which I asked the author to register, but there was no response, so it may be abandonned.

Perhaps the PR could be dusted off.


You can also use TraceCalls.jl to check for type-stability of all subcalls. Something like

trace = @trace YourModule f(x)
@test all(is_inferred, collect(trace))


Given that the end-result of a type-instability is unexpected allocations, you can also test the behavior with @allocated to ensure Julia isn’t allocating more than is necessary.


Thanks for all the suggestions! I didn’t know about any of those modules, I’ll look into them. The allocated trick also sounds good, would simultaneously test allocation regressions, which is also useful