UVL Reader

The Universal Variability Language (UVL) is a language designed to specify variability in software product lines (SPLs). It aims to provide a standardized way to describe the features and variations within a product line, facilitating the management of different configurations and enabling tool interoperability.

Key features

Key features of Universal Variability Language (UVL):

Standardization

UVL provides a common, standardized way to represent variability, making it easier to share and reuse models across different tools and organizations.

Expressiveness

It is designed to be expressive enough to capture complex variability, including hierarchical features, constraints, and dependencies between features.

Simplicity and Usability

UVL aims to be simple to use, with a syntax that is easy to understand for both humans and machines. This makes it accessible to a wide range of stakeholders, including developers, product managers, and other domain experts.

Tool Support

There is growing support for UVL in various SPL tools, which can interpret and manipulate UVL models. This includes tools for feature modeling, configuration, analysis, and visualization.

Interoperability

By using a common language like UVL, different tools and platforms can more easily interoperate, enabling a more integrated and efficient SPL engineering process.

flamapy relies on file extensions to identify which transformation is required. If you are not an expert we recommend to specify the correct extension for this file type. The file extension for this file is .uvl

A snipet of how it looks like

features
    Sandwich
        mandatory
            Bread
        optional
            Sauce
                alternative
                    Ketchup
                    Mustard
            Cheese
constraints
    Ketchup => Cheese

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Code Examples

from flamapy.core.discover import DiscoverMetamodels
# Initiallize the dicover metamodel
dm = DiscoverMetamodels()
# Get the fm metamodel representation using the transformation 
# required to get to the fm metamodel
# the transformation is identified by file extension .uvl
feature_model = dm.use_transformation_t2m("path/to/feature/model",'fm') 
# Call the operation, no automatic transformations will be needed
print(feature_model)