Homogeneity

Description: Measures the uniformity of feature distributions across all valid configurations.

Application: Useful for assessing whether certain features are consistently included or excluded in configurations, indicating stability or variability within the product line.

Example: Evaluating if certain features are consistently present in all configurations of a software product line.

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Code Examples

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("BDDHomogeneity", "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 using the transformation required to get to the fm metamodel
feature_model = dm.use_transformation_t2m("path/to/feature/model", 'fm')
# Manually call a M2M transformation to BDD
bdd_model = dm.use_transformation_m2m(feature_model, "bdd")
# Get the operation
operation = dm.get_operation(bdd_model, 'BDDHomogeneity')
# Execute the operation
operation.execute(bdd_model)
# Get and print the result
result = operation.get_result()
print(result)