Test Case Generator

This code generator produces an automated test suite for the Python domain model of a Structural model. The generated suite combines plain pytest structural checks with Hypothesis property-based tests.

The generated test_hypothesis.py contains three sections:

  • Structural tests — assert that each class is concrete, exposes the expected constructor parameters, and declares each attribute as a property; enumerations are checked for their literals.

  • Property-based tests — build instances with hypothesis.strategies.builds and assert instantiation, attribute setter round-trips, and association multiplicity contracts.

  • OCL post-condition tests — for each method post-condition, a test calls the operation with sample arguments and asserts the post-condition, translated from OCL to Python (@pre capture, collection operations such as ->size() / ->includes(), and = to ==).

You should create a TestCaseGenerator object, provide the Structural model, and use the generate method as follows:

from besser.generators.testgen import TestCaseGenerator

generator: TestCaseGenerator = TestCaseGenerator(model=library_model)
generator.generate()

The test_hypothesis.py file will be generated in the <<current_directory>>/output folder (or in output_dir if you provide one).

The generated suite imports the domain classes with from classes import ..., matching the default output module of the Python Classes Generator generator. If your domain model lives in a different module, set the module_name argument:

from besser.generators.testgen import TestCaseGenerator

generator = TestCaseGenerator(model=library_model, module_name="my_domain")
generator.generate()

This changes the import line of the generated file to from my_domain import ....

Note

Running the generated suite requires pytest and hypothesis to be installed, and the domain model classes to be importable from the configured module_name module (e.g. the classes.py produced by the Python Classes Generator generator).