Most academic code runs once, on one collection of data, on a particular file system.
Academic code can be really bad. But most of the time it doesn't matter, unless they're building libraries, packages, or applications intended for others. That's when it hurts and shows.
I'm a research programmer. I have a master's in CS. I take programming seriously. I think academic programmers could benefit from better practice. But I think software developers make the mistake of thinking that just because academics use code the objective is the same or that best practices should be the same too. Yes, research code should perform tests, though that should mostly look like running code on dummy data and making sure the results look like you expect.
I know a lot of "research programmers" (meaning people who write code in research labs but are not themselves the researchers or investigators on a study), and they often have MS degrees in CS - though actually, highly quantitative masters degrees where very elaborate code is used to generate answers is a bit more common than CS per se (math, operations research, branches of engineering, bioinformatics, etc).
Here's the thing - in industry, this background (quant undergrad + MS, high programming ability, industry experience) is kind of the gold standard for data science jobs. In academic job ladders it's... hmm. Here's the thing - by the latest data, MS grads in these fields from top programs are starting at between 120k-160k in industry, and there are very good opportunities for growth.
I actually think that universities and research centers can compete with highly in demand workers in spite of lower salaries, but highly talented people in demand will not turn away an industry job with salary and advancement potential to remain in a dead end job.
Academic code can be really bad. But most of the time it doesn't matter, unless they're building libraries, packages, or applications intended for others. That's when it hurts and shows.
I'm a research programmer. I have a master's in CS. I take programming seriously. I think academic programmers could benefit from better practice. But I think software developers make the mistake of thinking that just because academics use code the objective is the same or that best practices should be the same too. Yes, research code should perform tests, though that should mostly look like running code on dummy data and making sure the results look like you expect.