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FaMaPy is a Python-based AAFM framework that takes into consideration previous AAFM tool designs and enables multi-solver and multi-metamodel support for the integration of AAFM tooling on the Python ecosystem.

Project description

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FaMaPy is a Python-based AAFM framework that takes into consideration previous AAFM tool designs and enables multi-solver and multi-metamodel support for the integration of AAFM tooling on the Python ecosystem.

The main features of the framework are:

  • Easy to extend by enabling the creation of new plugins following a semi-automatic generator approach.
  • Support multiple variability models. Currently, it provides support for cardinality-based feature models. However, it is easy to integrate others such as attributed feature models
  • Support multiple solvers. Currently, it provides support for the PySAT metasolver, which enables more than ten different solvers.
  • Support multiple operations. It is developed, having in mind multi-model operations such as those depicted by Familiar and single-model operations.

Install development

Create virtualenv and install setup.py:

python3 -m venv env .
source env/bin/activate
pip install -e .  # Install package in development mode

IMPORTANT NOTE: this repository not work without metamodels, you need to install some metamodels

Execute tests

After you install the module, you can execute:

pytest

Install metamodels

There is at the moment two separate metamodels repository:

git clone git@github.com:diverso-lab/fm_metamodel.git
git clone git@github.com:diverso-lab/pysat_metamodel.git

You can install it inside the same virtualenv environment with:

pip install -e .

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