There is a numerical benchmark reported in Fig. 4 with absolute runtimes and memory usages that can directly be reproduced with the provided source code. The benchmark was performed on the author's computer, and since numerical performance and parallel scaling can be somewhat hardware-dependent, it would be of interest to see whether a performance that is comparable to the one reported in the paper can be reproduced by others on their own computers in practice. The benchmark simulates a growing tissue from one to 10,000 cells in just ten minutes, so this offers an easy entry point into tissue modeling and simulation. No input data is needed to reproduce the output. The program has no dependencies.
We think this is an interesting paper for anyone who wants to learn to build an API with the R package plumber. This is a novel method in health economics, but we believe will help improve the transparency of modelling methods in our field.
It uses the drake R package that should make reproducibility of R projects much easier (just run make.R and you're done). However, it does depend on very specific package versions, which are provided by the accompanying docker image.
