This repo contains two main components, the source code used to investigate our topic and the final paper describing our results.

Inside src/, there are two subdirectories, one for each approach we investigated, logical synthesis and voting theory.

See the readme here.

The second approach is based on parametrized hashing under the guise of a voting scheme. It is written in Python and may be run as:

python weighted_pearson.py

This code depends on numpy and matplotlib, which may be installed with the pip tool, or however your distro handles python packages.

The final paper is included in the report/ directory as a pdf with instructions for building it from scratch. You can also download it from here.