Store best population during search

src/pynguin/configuration.py

@@ -294,6 +294,10 @@ class TestCaseOutputConfiguration:
     Only works when running in a subprocess. If set to "", the are stored in the
     output_path."""
 
+    store_best_population: bool = True
+    """Whether to store and update the current best population as pytest in the
+    output_path during the search."""
+
     export_strategy: ExportStrategy = ExportStrategy.PY_TEST
     """The export strategy determines for which test-runner system the
     generated tests should fit."""

src/pynguin/ga/generationalgorithmfactory.py

@@ -277,6 +277,12 @@ def get_search_algorithm(self) -> GenerationAlgorithm:
             if stop.observes_execution:
                 self._executor.add_observer(stop)
         strategy.add_search_observer(so.LogSearchObserver())
+
+        if config.configuration.test_case_output.store_best_population:
+            strategy.add_search_observer(
+                so.BestPopulationObserver(config.configuration.test_case_output.output_path)
+            )
+
         strategy.add_search_observer(sso.SequenceStartTimeObserver())
         strategy.add_search_observer(sso.IterationObserver())
         strategy.add_search_observer(sso.BestIndividualObserver())

src/pynguin/ga/searchobserver.py

@@ -17,12 +17,17 @@
 
 from abc import ABC
 from abc import abstractmethod
+from pathlib import Path
 from typing import TYPE_CHECKING
 
+from pynguin.testcase import export
+
 
 if TYPE_CHECKING:
     import pynguin.ga.testsuitechromosome as tsc
 
+BEST_POPULATION_FILE_NAME = "best_population.py"
+
 
 class SearchObserver(ABC):
     """Observes the execution of a search algorithm."""
@@ -85,3 +90,65 @@ def after_search_iteration(  # noqa: D102
 
     def after_search_finish(self) -> None:
         """Not used."""
+
+
+class BestPopulationObserver(SearchObserver):
+    """Observes the search and stores the best individuals in a file."""
+
+    _logger = logging.getLogger(__name__)
+
+    def __init__(self, store_path: str):
+        """Initialize the observer with the path to store the best population.
+
+        Args:
+            store_path: Path to the file where the best individuals will be stored.
+        """
+        self.store_path = Path(store_path + "/" + BEST_POPULATION_FILE_NAME)
+        self.best_coverage = -1.0
+        self.iteration = 0
+        self.store_path.parent.mkdir(parents=True, exist_ok=True)
+
+    def before_search_start(self, start_time_ns: int) -> None:  # noqa: D102
+        self.iteration = 0
+        self.best_coverage = -1.0
+        self._logger.debug("Best population observer started, storing to: %s", self.store_path)
+
+    def before_first_search_iteration(self, initial: tsc.TestSuiteChromosome) -> None:  # noqa: D102
+        current_coverage = initial.get_coverage()
+        if current_coverage > self.best_coverage:
+            self.best_coverage = current_coverage
+            self._store_best_population(initial)
+
+    def after_search_iteration(self, best: tsc.TestSuiteChromosome) -> None:  # noqa: D102
+        self.iteration += 1
+        current_coverage = best.get_coverage()
+
+        # Only store if this is better than our current best
+        if current_coverage > self.best_coverage:
+            self.best_coverage = current_coverage
+            self._store_best_population(best)
+            self._logger.debug(
+                "New best individual found at iteration %d with coverage %5f, stored to %s",
+                self.iteration,
+                current_coverage,
+                self.store_path,
+            )
+
+    def after_search_finish(self) -> None:  # noqa: D102
+        self._logger.debug("Best population observer finished")
+
+    def _store_best_population(self, chromosome: tsc.TestSuiteChromosome) -> None:
+        """Store the best population to the file.
+
+        Args:
+            chromosome: The chromosome containing the best individuals.
+        """
+        try:
+            export_visitor = export.PyTestChromosomeToAstVisitor(store_call_return=False)
+            chromosome.accept(export_visitor)
+            export.save_module_to_file(
+                export_visitor.to_module(), self.store_path, format_with_black=False
+            )
+
+        except Exception as e:  # noqa: BLE001
+            self._logger.warning("Failed to store best population: %s", e)

tests/ga/algorithms/test_randomalgorithm.py

@@ -56,6 +56,7 @@ def _combine_current_individual(*_):
 
     config.configuration.stopping.maximum_search_time = 1
     config.configuration.algorithm = config.Algorithm.RANDOM
+    config.configuration.test_case_output.store_best_population = False
     logger = MagicMock(Logger)
     algorithm = gaf.TestSuiteGenerationAlgorithmFactory(
         executor, MagicMock(ModuleTestCluster)

tests/utils/test_configuration_writer.py

@@ -35,6 +35,7 @@ def expected_toml(tmp_path):
 [test_case_output]
 output_path = ""
 crash_path = ""
+store_best_population = true
 export_strategy = "PY_TEST"
 max_length_test_case = 2500
 assertion_generation = "MUTATION_ANALYSIS"
@@ -220,8 +221,8 @@ def expected_txt(tmp_path):
     expected_txt = Path(tmp_path) / f"expected-{PYNGUIN_CONFIG_TXT}"
     expected = """("Configuration(project_path='', module_name='', "
  "test_case_output=TestCaseOutputConfiguration(output_path='', crash_path='', "
- "export_strategy=<ExportStrategy.PY_TEST: 'PY_TEST'>, "
- 'max_length_test_case=2500, '
+ 'store_best_population=True, export_strategy=<ExportStrategy.PY_TEST: '
+ "'PY_TEST'>, max_length_test_case=2500, "
  'assertion_generation=<AssertionGenerator.MUTATION_ANALYSIS: '
  "'MUTATION_ANALYSIS'>, allow_stale_assertions=False, "
  'mutation_strategy=<MutationStrategy.FIRST_ORDER_MUTANTS: '
@@ -532,6 +533,8 @@ def expected_parameters() -> str:
 FIRST_ORDER_MUTANTS
 --test_case_output.post_process
 True
+--test_case_output.store_best_population
+True
 --test_creation.any_weight
 0
 --test_creation.bytes_length