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Comment by guelo | Hacker News Reader

My non-academist opinion is that the biggest problem in science is that there is little incentive for scientists to reproduce each other's results. Anything that makes it easier for other labs to rerun an experiment is a good thing for your field overall. The goal of a paper should be to communicate as plainly as possible how to reproduce the experiment. That probably means a good-enough standard programming language that everyone learns in school and uses in their work.

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Well I think it should communicate how to reproduce the experiment in a lab with the same or similar setup, not how to reproduce it with all kinds of different setups. If a lab does not have the equipment to reproduce a certain experiment, it's not the problem of the original authors.

Also, I think you should choose equipment which best suits the experiment, not other people.

>If a lab does not have the equipment to reproduce a certain experiment, it's not the problem of the original authors.

While I think that's true, a paper can potentially be much more impactful if its' results can be easily understood by others, and isn't that really the point of science? In that sense, it's better for the author to stay away from niche methods and tools unless absolutely necessary.

I agree, unless it's something that can't be done well in the current language. Or, if like me, you're an economist and the default language used by academics is horrible, horrible Stata, which needs to be replaced by R.

For me, both are horrible. I use Stata a lot and thought a lot about switching to R (there is even a nice tutorial by Matthieu Gomez at http://www.princeton.edu/~mattg/statar/ ).

However, I believe that moving to R is not the answer, as you will still be riddled with a lot of the problems that you faced in Stata such as a quirky syntax (except backticks. I hate those backticks). Maybe Python will catch up (I doubt it, what we need is a DSL, not something too general that requires loong commands to do a simple regress). My best bet would be Julia, but it's still a long way to go regarding things like missing values.

If you're a macroeconomist, the default is Matlab. I'm not sure which is worse.

I agree, but I still think the idea/algorithm/etc should be conveyed in sentences and math in the body of the paper. The code should purely be optional and not associated with the paper. I think the problem here is the author is referencing code in the paper, which puts the onus on the journal to evaluate the code. Juts put the code on your website. If people want it enough they will google you.

Look at the Reproducibility Project: https://osf.io/ezcuj/

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