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Welcome to Flamapy Official Site |
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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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The cutting-edge Python-based tool for Automated Analysis of Feature Models using UVL and more {: .fs-6 .fw-500 .center-text}
Simplifies the process of creating new plugins with a semi-automatic generator, making customization and expansion straightforward.
Initially supports cardinality-based feature models, with the flexibility to easily incorporate other types like attributed feature models.
Utilizes the PySAT metasolver, offering access to more than ten distinct solvers. This diversity allows for optimal solution finding across various complex scenarios.
Utilizes the CU-BDD metasolver, offering efficient variability model analysis for some operations.
Designed with capabilities to analyse modes in Python with just a line of code.
Easy to integrate in any ecosystem.
Run analysis in your browser. Currently, both {% include flamapy.html %} and PySAT are WASM compatible. Enable analysis with 0 configuration process.
Integrate the tool in yours by means of a robust backend Rest API.
Examples of operations include:
Identifies features that cannot be included in any valid configuration due to constraints and dependencies in the model.
Identifies features that are present in all valid configurations of the feature model.
Provides an estimate of the total number of different configurations that can be produced from a feature model by considering all possible combinations of features.
This operation identifies atomic sets in a feature model. An atomic set is a group of features that always appear together across all configurations of the model.
This operation filters and selects a subset of configurations based on specified criteria. It helps in narrowing down the possible configurations to those that meet certain requirements.
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Detailed changes for each release are documented in the release notes.
When contributing to this repository, please first read contributing.