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Flama - A variability analysis tool written in Python.

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.

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Distributions

Flama Feature Model Distribution

Flama as a feature model analysis tool As we have shown, the Flama framework could be adapted to support other kinds of variability descriptions by creating new plugins that represent the meta-classes to define it and the transformation to any existing reasoning technique. This is, for example, the case of a plugin to analyze software dependencies with security concerns information. However, its main purpose is the analysis of feature models. Because of that, Flama provides a single Python package that installs all the required plugins and provides a more straightforward usage of the tooling. Concretely, this pip package provides the fol...

Plugins

Core

The core component is the main entry point of Flama Description The core component of this frame...

Feature model metamodel

The feature model plugin provides the metaclases required to work with feature models Descriptio...

SAT metamodel

The pysat model plugin provides the metaclases required to work with SAT models and to transform...

BDD metamodel

The BDD model plugin provides the metaclases required to work with SAT models and to transform f...

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University of Seville

The university of Seville is currently providing support for the core and the pysat plugins.
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University of Málaga

The university of Malaga is currently providing support for the core and the bdd plugins.
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University of Graz

The university of Graz is currently providing support for the operations regarding the explaination of errors in feature modeling.
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Universidad Nacional de Educación a Distancia

The UNED is currently providing support for the implementation of BDD techniques that cope with colosal feature models.