Backbone

Description: Returns the backbone of the feature model: the set of features that must always be selected (core features) and those that must never be selected (dead features) across all valid configurations, grouped under core and dead keys.

Application: Provides a compact summary of the rigid parts of a product line in a single call, useful for model quality assessment.

Example: Obtaining all features that are mandatory or impossible in a smartphone product line model.

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Code Examples

Python easy to use facade usage

from flamapy.interfaces.python.flamapy_feature_model import FLAMAFeatureModel
# Load the feature model
fm = FLAMAFeatureModel("path/to/feature/model")
# Returns {'core': [...], 'dead': [...]}
result = fm.backbone()
print(result)

Python flamapy framework usage

from flamapy.core.discover import DiscoverMetamodels
# Initialize the discover metamodel
dm = DiscoverMetamodels()
# Call the operation. Transformations will be automatically executed
result = dm.use_operation_from_file("PySATBackbone", "path/to/feature/model")
print(result)

Python flamapy framework ADVANCED usage

from flamapy.core.discover import DiscoverMetamodels
# Initialize the discover metamodel
dm = DiscoverMetamodels()
# Get the fm metamodel representation
feature_model = dm.use_transformation_t2m("path/to/feature/model", 'fm')
# Manually call a M2M transformation to PySAT
sat_model = dm.use_transformation_m2m(feature_model, "pysat")
# Get the operation
operation = dm.get_operation(sat_model, 'PySATBackbone')
# Execute the operation
operation.execute(sat_model)
# Get and print the result
result = operation.get_result()
print(result)