Four years ago, another group published a paper describing a new method for estimating an important parameter in my field. The method is theoretically elegant, has good accuracy in their benchmarks, and can be applied in cases where every other method I know of gives unreliable estimates.
The authors provided a GitHub repo with the code they used to realize this method. Unfortunately, the code in the repo is very poor. Several scripts do not complete successfully without fixing several lines of code; a key step in the pipeline is left as an exercise for the reader (notably, the paper stated that code for this step would be in the repo); as written, the whole pipeline requires the user to manually run many different scripts in succession; and the code is very inefficient, with e.g. computationally intensive calculations done to define objects that never get used. (The first author was a master's student, which might explain some of this.)
According to the citations of the parent paper, it seems that this method has only ever been used by the same group that wrote it, likely because of the limitations above. The issues page on the GitHub repo demonstrates that a few other people tried to run the code before hitting multiple serious errors and apparently giving up. After a lot of effort and fixes, I was able to run the code, and confirmed that it gives good results in cases where every other method fails. I also decided to reimplement the method almost from scratch as an evening project across a couple of weeks. I would like to believe my rewrite is an improvement: among other things, the runtime is much quicker (e.g. one particular step now takes 10 minutes rather than 40 hours), it takes a greater variety of file formats as input, and the whole process can be run in a single command. I have tested it on multiple machines and Linux distros and confirm that it does actually run out-of-the-box on all of them.
I think it would be good for my field to be able to discover this implementation of a useful method which nobody else has been able to use to date, and to be honest it would also be nice if I could somehow get recognized for this work. I really do think that it would satisfy a significant unmet need.
My idea right now is to put the method up on... JOSS? Zenodo? A preprint server? so it gets a citable DOI. (The venue to publicize this on is another question - I think it would be difficult and unnecessary to somehow turn this rewrite into a more traditional research paper.) But I'm not sure how I would attribute the original authors. I could reach out and offer to make them co-authors on whatever citable DOI I create. I could leave instructions on the GitHub repo to cite both the rewrite's DOI and the original paper when using it - although in practice I think many people would not bother citing both. Or am I wrong for expecting citations for this kind of work? After all, I did not add any functionality, I just made an implementation that is more flexible and much easier to run at all. Should I just make the repo public, tweet about it, add the repo as a line in my CV, and be done with it? I did not get to my current position via a traditional academic route, so I am not as familiar with the norms around publishing and so on.
