SciMLStyle VS RequiredInterfaces.jl

No, you do get type errors during runtime. The most common one is a MethodNotFound error, which corresponds to a dispatch not being found. This is the one that people then complain about for long stacktraces and as being hard to read (and that's a valid criticism). The reason for it is because if you do xy with a type combination that does not have a corresponding dispatch, i.e. (x::T1,y::T2) not defined anywhere, then it looks through the method table of the function, does not find one, and throws this MethodNotFound error. You will only get no error if a method is found. Now what can happen is that you can have a method to an abstract type, *(x::T1,y::AbstractArray), but `y` does not "actually" act like an AbstractArray in some way. If the way that it's "not an AbstractArray" is that it's missing some method overloads of the AbstractArray interface (https://docs.julialang.org/en/v1/manual/interfaces/#man-inte...), you will get a MethodNotFound error thrown on that interface function. Thus you will only not get an error if someone has declared `typeof(y) <: AbstractArray` and implemented the AbstractArray interface.

However, what Yuri pointed out is that there are some packages (specifically in the statistics area) which implemented functions like `f(A::AbstractArray)` but used `for i in 1:length(A)` to iterate through x's values. Notice that the AbstractArray interface has interface functions for "non-traditional indices", including `axes(A)` which is a function to call to get "the a tuple of AbstractUnitRange{<:Integer} of valid indices". Thus these codes are incorrect, because by the definition of the interface you should be doing `for i in axes(A)` if you want to support an AbstractArray because there is no guarantee that its indices go from `1:length(A)`. Note that this was added to the `AbstractArray` interface in the v1.0 change, which is notably after the codes he referenced were written, and thus it's more that they were not updated to handle this expanded interface when the v1.0 transition occurred.

This is important to understand because the criticisms and proposed "solutions" don't actually match the case... at all. This is not a case of Julia just letting anything through: someone had to purposefully define these functions for them to exist. And interfaces are not a solution here because there is an interface here, its rules were just not followed. I don't know of an interface system which would actually throw an error if someone does a loop `for i in 1:length(A)` in a code where `A` is then indexed by the element. That analysis is rather difficult at the compiler level because it's non-local: `length(A)` is valid since querying for the length is part of the AbstractArray interface (for good reasons), so then `1:length(A)` is valid since that's just range construction on integers, so the for loop construction itself is valid, and it's only invalid because of some other knowledge about how `A[i]` should work (this look structure could be correct if it's not used to `A[i]` but rather do something like `sum(i)` without indexing). If you want this to throw an error, the only real thing you could do is remove indexing from the AbstractArray interface and solely rely on iteration, which I'm not opposed to (given the relationship to GPUs of course), but etc. you can see the question to solving this is "what is the right interface?" not "are there even interfaces?" (of which the answer is, yes but the errors are thrown at runtime MethodNotFound instead of compile time MethodNotImplemented for undefined things, the latter would be cool for better debugging and stacktraces but isn't a solution).

This is why the real discussions are not about interfaces as a solution, they don't solve this issue, and even further languages with interfaces also have this issue. It's about tools for helping code style. You probably should just never do `for i in 1:length(A)`, probably you should always do `for i in eachindex(A)` or `for i in axes(A)` because those iteration styles work for `Array` but also work for any `AbstractArray` and thus it's just a safer way to code. That is why there are specific mentions to not do this in style guides (for example, https://github.com/SciML/SciMLStyle#generic-code-is-preferre...), and things like JuliaFormatter automatically flag it as a style break (which would cause CI failures in organizations like SciML which enforce SciML Style formatting as a CI run with Github Actions https://github.com/SciML/ModelingToolkit.jl/blob/v8.14.1/.gi...). There's a call to add linting support for this as well, flagging it any time someone writes this code. If everyone is told to not assume 1-based indexing, formatting CI fails if it is assumed, and the linter underlines every piece of code that does it as red, (along with many other measures, which includes extensive downstream testing, fuzzing against other array types, etc.) then we're at least pretty well guarded against it. And many Julia organizations, like SciML, have these practices in place to guard against it. Yuri's specific discussion is more that JuliaStats does not.

There is no rebuttal because nothing much has really changed culture wise. Sure, the various @inbounds issues and concrete bugs that are mentioned in Yuris post have mostly been addressed, but the larger point (that is, "what can I actually expect/get guaranteed when calling a given function?") definitely hasn't been, at least not culturally. Documentation of pre- and postconditions are still lackluster, PRs trying to establish that for functions in Base stall for unclear reasons/don't get followups and when you try to talk about that on Slack retorts boil down to "we're tired of hearing you complain about this" instead of trying to find a systemic solution to that problem. Until that changes, I have large doubts about Yuris post losing relevance.

My own efforts (shameless plug, https://github.com/Seelengrab/PropCheck.jl for property based testing inspired by Hedgehog and https://github.com/Seelengrab/RequiredInterfaces.jl for somewhat formalizing "what methods are needed to subtype an abstract type") are unused in the wider community as far as I can tell, in spite of people speaking highly of them when coming across them. I also don't think Kenos InterfaceSpecs.jl is the way forward either - I think there's quite a lot of design space left in the typesystem the language could do without reaching for z3 and other SAT/SMT solvers. I personally attribute the lack of progress on that front to the lack of coherent direction of the project at large (and specifically not to the failings of individuals - folks are always very busy with their lives outside of Julia development/other priorities). In spite of the fact that making this single area better could be a big boon with more traditional software engineers, which are very underrepresented in the community.