mealy-decompose
===============

Tools to investigate decomposition of Mealy machines, aka finite state
machines (FSMs). Notable entry points are:

* `app/Main.hs` is a heuristic to decompose finite state machines into
  multiple components, based on their outputs.

* `other/decompose_fsm_optimise.py` does the same, but optimally and with a
  SAT solver. This can only handle state spaces of at most a few hundred
  states.

* `app/RandomGen.hs` for generating FSMs which are decomposable.


## How to run

The the haskell tools (tested with ghc 9.2.8 and ghc 9.10.1):
```
cabal run mealy-decompose -- <path-to-fsm>
```

For the python tools (tested with python 3.12):
```
pip3 install python-sat
python3 decompose_fsm_optimise.py -h
```


## Notes on `copar`

In the first versions of this tool, I used the `copar` library:
[CoPaR (The Coalgebraic Partition Refiner)](https://git8.cs.fau.de/software/copar).
This is a great library and in particular very fast. Despite that, I switched
to my own partition refinement implementations because of the reasons below.
The last commit to use `copar` is `2b8b79a4`.

* I needed witnesses for some tasks. So I not only construct a partition,
  but also a splitting tree, where are track all the actions needed to
  separate states.

* I prefer to use the actual strings (or other data type) for the states,
  inputs and outputs as opposed to `Int`s. This makes it easier to debug, and
  less error-prone, as one cannot mix these entities anymore.

* `copar` comes with many dependencies, and it was a bit tricky to get the
  versioning correct.


## Copyright

(c) 2024 Joshua Moerman, Open Universiteit