examples | ||
satuio | ||
.gitignore | ||
README.md |
satuio
Using SAT solvers to construct UIOs and ADSs for Mealy machines (aka finite state machines). Both problems are PSpace-complete, and so a SAT solver does not really make sense. However, with a given bound (encoded unary), the problems are in NP, and so can be encoded in SAT.
There are some Mealy machines in examples
directory. And even for the
machine with roughly 500 states, the encodings are efficient, and
sequences can be found within minutes.
Dependencies
This project uses Python3. It uses the following packages which can be
installed with pip
as follows:
pip3 install pysat tqdm rich
Usage
All scripts show their usage with the --help
flag. Note that the
flags and options are subject to change, since this is WIP. I
recommend to read the source code of these scripts to see what is
going on. (Or read the upcoming paper.)
# Finding UIO sequences of fixed length in a Mealy machine
python3 satuio/uio.py --help
# Finding UIO sequences while incrementing the length in a Mealy machine
python3 satuio/uio-incr.py --help
# Finding an ADS in a Mealy machine for a set of states
python3 satuio/ads.py --help
# Returning an unsat core in the case an ADS does not exist
python3 satuio/ads-core.py --help
The solver can be specified (as long as pysat supports it). The default is Glucose3, as that worked well on the examples.
Copyright
© Joshua Moerman, Open Universiteit, 2022