If I recall, the same argument was used to justify Octave's Fortran coded libraries for stats. Primarily, it was an argument about historical consistency in th

If I recall, the same argument was used to justify Octave's Fortran coded libraries for stats. Primarily, it was an argument about historical consistency in the assumptions people agreed upon at NASA. Julia's library compatibility is still an issue, but hardly related to the language itself. Unlike many languages, Julia has regression testing for its graphical plotting output. This means it can and usually does check that a given output matches a previously known function(s) output across each release iteration. This means that unlike many languages that fix/ignore various external library versions, Julia actually checks that data gives the exact same results every time. The caveat is that people must report issues to the project, or add regression tests to ensure correctness persists throughout the ecosystem. =)