Speaking from experience, the code is normally functional but unsightly, thus it would be embarrassing to place it online. Most researchers are happy to email

Speaking from experience, the code is normally functional but unsightly, thus it would be embarrassing to place it online. Most researchers are happy to email you the code if you ask for it though. Most of my code is for scientific computing and consists of a bunch of one-off Jupyter notebooks and Julia scripts that are written with two objectives in mind: get-the-task-done-before-my-advisor-meeting and make-it-as-fast-as-possible. Good coding practices and code cleanliness are not priorities. And particularly for code that needs to run on HPC clusters or supercomputers, it's really hard to make it look nice — one could easily spend weeks designing a proper, modular system only to throw it all away in favor of using a better algorithm that was just published. Anecdotally, the vast majority of my code has produced results that were later discarded. For example, I have a function named YPXt. What does such a woefully named subroutine do? It multiplies a matrix Y by a permutation matrix P, and then multiplies that by another (transposed) matrix X. The matrices are small, so the overhead of using BLAS for the task is wasteful. It's better to use Julia's macro system to generate the necessary for loops on the fly and let the compiler SIMD-ify the result. Also, permutation matrix multiplies can be done in a way that doesn't actually involve creating a full permutation matrix. And of course the subroutine has side effects — in order to conserve memory I need to overwrite the input matrices instead of allocating new ones. Immutable data structures may work great for functional programming, but the overhead of red-black trees and stateless programming is too high for numerical data crunching. Add that to the fact that a lot of scientists in academia are unfamiliar with tools like Git, and so manually versioning the code and emailing it back and forth is unfortunately a necessary part of the collaboration process.