Fine-grained Language Composition: A Case Study -- Artefacts

Edd Barrett, Carl Friedrich Bolz, Lukas Diekmann, and Laurence Tratt

Download PyHyp

PyHyp can be downloaded, and build instructions found, on its its GitHub repository. It is recommended to use it with the Eco editor, which can be downloaded here.


The paper contains performance benchmarks. We believe strongly in repeatability in computing experiments, so we provide artefacts that allow others to repeat and inspect our experiments.

Our files are kindly hosted by The Internet Archive under the identifier ecoop16_pyhyp_artefacts.

The easiest way to see our experiments and demos in action is to download and run our VirtualBox VM image. Simply untar the archive and read the enclosed README file:

Full source code and build instructions for the benchmarks is available. Our hope is that others can easily run our experiments and study the output on their particular setup.