Two minute papers is fantastic! I just wish that all of the papers he covers had source code available. A few of them I've gotten excited about and hopped around the net to read the paper only to find no code available.

This is the state of science in a lot fields unfortunately. Many reviewers skim the paper, put in a thinly veiled complaint about why their own paper was not cited, and don't bother with the code.

The code itself is always usually a mess: no readme, no license, random binaries, and a 'pipeline' which is simply a bunch of perl and python scripts cobbler together from snippets found on the web.

People publish, then move onto the next project. There is no maintenance.

In my case, I'm not a researcher or even a computer scientist (EE). I'm just a person with a curiosity in various topics. I find the language in papers to be a big barrier. Even cludgy bad code in ten different languages is more readable to me than the strange symbols and vague diagrams.

I agree with you that this is research and there's no reason for it to be pretty. The fact that it's unsightly and brittle makes a lot of people reticent about sharing it online since it could reflect on the quality of their non prototype code. Maintenance is a large burden and once the original goal of the paper has been proved, there's little benefit to the researcher to keep the code around, so I understand why they might say let's not release it at all.

A recent example of this was I was building a gesture classifier using an accelerometer to generate data. I decided do use an svm as based on what I had read, it would be the simplest to port to the microcontroller I was using. I was getting decent performance but needed to extract better features. I found several papers talking about the topic with some novel ideas and their impressive results. While it was nice to know that accuracy could get that high, none of the papers explained how the features they extracted were made. It was usually a one or two sentence line about using both time and frequency domain data.

> This is the state of science in a lot fields unfortunately. Many reviewers skim the paper, put in a thinly veiled complaint about why their own paper was not cited, and don't bother with the code.

Excuse me. Is this your actual experience or the meme that everybody is simply repeating?

In the admittedly few papers I have published, the reviewers’ feedback has been a net positive I wouldn’t be without.

Also, the general focus on code in science here on HN is so incredibly myopic and narrow minded. Code for research are not high-profile software projects. They are a piece in the toolbox used to solve a problem. Some grow to become larger projects, some fulfill their purpose and stay fixed in time.

Actual experience. The state of code in Bioinformatics is a joke. Many do not know the word 'conda' or 'docker', and example datasets are far and few between.