The previous HN thread:

Correctness and composability bugs in the Julia ecosystem - https://news.ycombinator.com/item?id=31396861 - May 2022 (407 comments)

Edit: since there are (again? I seem to remember this last time) complaints about the title being a bit too baity, I've pilfered that previous title for this thread as well

As an experiment, I would be interested to see if somebody would make a 1-based python list-like data structure (or a 0-based R array), to check how many 3rd party (or standard library) function would no longer work.

I've seen this article several times, and I'm sure Jerf has as well.

Our instinct, with years of being here, is it isn't a good fit for HN, at least at its current age and as labelled.

It is not conducive to healthy discussion to have an aged[1] blanket dismissal of a language coupled to an assertion that saying "the issues looked fixed?" is denial of people's lived experience.

[1] We can infer it was written in 2021, as the newest issue they created is from then, and they avowed never to use the language again.

https://github.com/scipy/scipy/issues?q=is%3Aissue%20state%3...

Scrolling through this list, it’s clear that many are “correctness issues.”

I do not link this to argue that scipy bugs are more serious or more frequent. I don’t think that kind of statistical comparison is meaningful.

However, I think a motivated reasoner could write a very similar blog post to the OP, but about $arb_python_lib instead of $arb_julia_lib.

I suppose my position is closer to “only Kahan, Boyd and Higham write correct numerical algorithms” (a hyperbole, but illustrative of the difficulty level).

This is true, and it's a powerful part of the language - but you can implement it incorrectly when you compose elements together that expect some attributes from the custom data type. There is no way to formally enforce that, so you can end up with correctness bugs.

My understanding is that it's a difficult problem to solve, and there are people working on traits/interfaces - but these are still peripheral projects and not part of the core mission to my knowledge. In practice, composability problems arise seldomly, but there is no formal way to guard against it yet. I believe there was some work done at Northeastern U. [1] toward this goal but it's still up to the user to "be careful", essentially.

[1] https://repository.library.northeastern.edu/files/neu:4f20cn...