Diagnosis

Description: Analyzes the feature model to identify and explain inconsistencies or errors, providing insights into potential fixes.

Application: Useful for debugging and improving the reliability of feature models by diagnosing issues and suggesting corrective actions.

Example: Diagnosing a feature model of a software application to identify and resolve conflicting constraints or dependencies.

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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("PySATDiagnosis", "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(model_path, 'fm')
# Manually call a M2M transformation to Pysat
sat_model = dm.use_transformation_m2m(feature_model, "pysat_diagnosis")
# Get the operation
operation = dm.get_operation(sat_model, 'PySATDiagnosis')
# Execute the operation
operation.execute(sat_model)
# Get and print the result
result = operation.get_result()
print(result)