def test_fitness_values_two_fitness_functions(chromosome, fitness_function):
chromosome.add_fitness_function(fitness_function)
chromosome._update_fitness_values(fitness_function, ff.FitnessValues(0.42, 0.1))
fitness_func2 = MagicMock(ff.FitnessFunction)
fitness_func2.is_maximisation_function.return_value = False
chromosome.add_fitness_function(fitness_func2)
chromosome._update_fitness_values(fitness_func2, ff.FitnessValues(0.23, 0.5))
assert len(chromosome.fitness_values) == 2
def test_fitness_two_fitness_functions(chromosome, fitness_function):
chromosome.add_fitness_function(fitness_function)
chromosome._update_fitness_values(fitness_function, ff.FitnessValues(0.42, 0.1))
fitness_func2 = MagicMock(ff.FitnessFunction)
fitness_func2.is_maximisation_function.return_value = False
chromosome.add_fitness_function(fitness_func2)
chromosome._update_fitness_values(fitness_func2, ff.FitnessValues(0.23, 0.5))
chromosome.set_changed(False)
assert chromosome.get_fitness() == 0.65
assert chromosome.get_coverage() == 0.3
def test_values_for_fitness_function(chromosome, fitness_function):
chromosome.add_fitness_function(fitness_function)
chromosome._update_fitness_values(fitness_function,
ff.FitnessValues(5, 0.5))
chromosome.set_changed(False)
assert chromosome.get_fitness_for(fitness_function) == 5
assert chromosome.get_coverage_for(fitness_function) == 0.5
def chromosome():
chrom = tsc.TestSuiteChromosome()
fitness_func = MagicMock(ff.FitnessFunction)
chrom.add_fitness_function(fitness_func)
chrom._update_fitness_values(fitness_func, ff.FitnessValues(0, 0))
chrom.set_changed(False)
return chrom
def compute_fitness_values(
self, individual: tcc.TestCaseChromosome) -> ff.FitnessValues:
result = self._run_test_case_chromosome(individual)
merged_trace = analyze_results([result])
tracer: ExecutionTracer = self._executor.tracer
return ff.FitnessValues(
compute_branch_distance_fitness(merged_trace,
tracer.get_known_data()),
compute_branch_coverage(merged_trace, tracer.get_known_data()),
)
def compute_fitness_values(
self,
individual: tsc.TestSuiteChromosome,
) -> ff.FitnessValues:
results = self._run_test_suite(individual)
_, merged_trace = self.analyze_traces(results)
tracer: ExecutionTracer = self._executor.get_tracer()
return ff.FitnessValues(
self._compute_fitness(merged_trace, tracer.get_known_data()),
self._compute_coverage(merged_trace, tracer.get_known_data()),
)
def test_illegal_values(chromosome, fitness_function):
fitness_function.compute_fitness_values.return_value = ff.FitnessValues(
-1, 1.5)
chromosome.add_fitness_function(fitness_function)
with pytest.raises(RuntimeError):
chromosome.get_fitness()
def test_validation_both_wrong():
values = ff.FitnessValues(-1, 5)
assert len(values.validate()) == 2
def test_validation_wrong_coverage():
values = ff.FitnessValues(0, 5)
assert len(values.validate()) == 1
def test_validation_wrong_fitness():
values = ff.FitnessValues(-1, 0)
assert len(values.validate()) == 1
def test_validation_ok():
values = ff.FitnessValues(0, 0)
assert len(values.validate()) == 0
def compute_fitness_values(
self, individual: tcc.TestCaseChromosome) -> ff.FitnessValues:
result = self._run_test_case_chromosome(individual)
return ff.FitnessValues(fitness=self._get_fitness(result),
coverage=0.0)
def non_zero_fitness_function() -> ff.FitnessFunction:
fitness_function = MagicMock(ff.FitnessFunction)
result = ff.FitnessValues(fitness=42.0, coverage=0.0)
fitness_function.compute_fitness_values.return_value = result
return fitness_function
