Here is a blog post that was making the rounds recently.
https://yuri.is/not-julia/
It has many concrete examples of low quality and buggy code making it into pretty core statistics libraries. Most of these bugs are a combination of 'sloppy' coding and lack of vigorous testing of all the corner cases that the language has. Many developers seem to take a more 'academic' approach to things (it works correctly in all the cases I care about) rather than caring about creating robust libraries that are rock solid under all conditions.
From the blog:
"My conclusion after using Julia for many years is that there are too many correctness and composability bugs throughout the ecosystem to justify using it in just about any context where correctness matters."
The good news is that this blog post seems to have brought some light to this problem and hopefully the Julia community can start addressing it.