flamapy official documentation

Introducing flamapy , the cutting-edge Python-based tool for Automated Analysis of Feature Models (AAFM) using UVL and more. flamapy revolutionizes feature model analysis by integrating the strengths of previous AAFM tools with advanced multi-solver and multi-metamodel capabilities.

Get started now View it on GitHub

Easily extensible

  • Plugin Generator: Simplifies the process of creating new plugins with a semi-automatic generator, making customization and expansion straightforward.
  • Variability modelling in the wild: Initially supports cardinality-based feature models, with the flexibility to easily incorporate other types like attributed feature models.

Robust solver support

  • PySAT Integration: Utilizes the PySAT metasolver, offering access to more than ten distinct solvers. This diversity allows for optimal solution finding across various complex scenarios.

  • BDD Integration: Utilizes the CU-BDD metasolver, offering efficient variability model analysis for some operations.

Easy to use, easy to integrate

  • Easy-to-use python facade: Designed with capabilities to analyse modes in Python with just a line of code.
  • Command line direct use: Easy to integrate in any ecosystem.
  • WASM support: Run analysis in your browser. Currently, both flamapy and PySAT are WASM compatible. Enable analysis with 0 configuration process.
  • REST / SWAGGER available: Integrate the tool in yours by means of a robust backend Rest API.

Large set of operations

You can find all set operations here

Changelog

Detailed changes for each release are documented in the release notes.

Contributing

When contributing to this repository, please first read contributing.