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We present 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 SAT and BDD metasolvers, which enables more than ten different solvers.
  • Support multiple operations. It is developed, having in mind multi-model operations and single-model operations. Currently, it provides more than ten operations for cardinality-based feature models

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  1. core core Public

    This repo will host the core components of Flama

    Python 4 6

  2. pysat_metamodel pysat_metamodel Public

    This repository will host the pysat metamode and its operation implementation

    Python 2 5

  3. fm_metamodel fm_metamodel Public

    This repo host the feature model concrete classes

    Python 3 5

  4. bdd_metamodel bdd_metamodel Public

    BDD plugin for the automated analysis of feature models using a BDD.

    Python 1 2

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