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Correctness and composability bugs in the Julia ecosystem

yuri.is

1–10 of 419 posts

Re: Correctness and composability bugs in the Julia ecosystem

#2
Ouch. That sounds all the more damning for the authors studious care to calmly describe instead of angrily rant.

I’ve spent too much time in research working on codebases that feel like quicksand — you never know what changing something might do!— to want to worry about that for stdlib or major package ecosystems, too.

Re: Correctness and composability bugs in the Julia ecosystem

#9
If you look at the history of lots of packages in matlab they fixed tons of bugs that sound similar to this stuff over the years. It requires consistent hard work by a core group of people who understand the issues to get everything right. I have no idea who maintains Julia and these packages but the author of the article mentions this as language problems — aren’t these just bugs? Like if gcc was incorrectly multiplying some constant by the wrong value, that doesn’t sound like a bug with C but a bug with gcc right?

Re: Correctness and composability bugs in the Julia ecosystem

#10
Only thing "interesting" to me there would be the automatic differentiation bugs ...but is there any argument as to them being the fault of the language, instead of just poor engineering from the library developers' part?

I mean, one can't expect all algorithms to work correctly with all datatypes just because the compiler allows that code to run ...you write tests and guarantee numerical stability for a small subset of types you can actually do it for, and then it's the code's consumers' job to ensure it work with types it's not documented to work and such, no? ...Julia is quite a dynamic language, JITed or what not, its semantics are closer to Python and Lisp than to Rust or Haskell ...maybe don't expect guarantees that aren't there and just code more defensively when making libraries others depends on?

Probably the Python + C(++) ecosystems works better bc their devs know they are working in loose, dynamic and weekly typed shoot-your-foot-off type languages and just take action and code defensively and test things properly, whereas Julia devs expect the language to give them guarantees that aren't there.

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