Pynguin 0.23.0

• Provide a naive inheritance graph to improve input generation.

• Improve killing of long-running test-case executions

• Add computation of mutation scores for MUTATION_ANALYSIS assertion generation.

  The output variables NumberOfCreatedMutants, NumberOfKilledMutants, NumberOfTimedOutMutants, and MutationScore allow to export those values.

• Do not enable typing.TYPE_CHECKING for SUT analysis as this may cause circular imports.

• Improve the black list of modules that shall not be incorporated into the test cluster.

• Annotate failing tests with @pytest.mark.xfail(strict=True).

• Improve log output of mutation-based assertion generation.

• Add instrumentation to mutated modules to easier kill them.

  This change is relevant only to the MUTATION_ANALYSIS assertion-generation strategy.

• Write errors in execution threads to the log instead of STDERR to avoid cluttering log output.

• Add limits for amount and size of constants in the constant pool.

  The configuration options max_dynamic_length and max_dynamic_pool_size allow to set sizes for the maximum length of strings/bytes that shall be stored in the dynamic constant pool and the maximum numbers of constants of a type, respectively. This prevents the constant pool from growing unreasonably large.

• Improve handling of type annotations.

• Fix computation of cyclomatic complexity.

  Computing cyclomatic complexity does not work for functions that are not present in the AST, e.g., default constructors. We now omit those from the computation of the cyclomatic-complexity output variables.

Pynguin 0.22.0

• Fix selection of type-inference strategy.

• Fix a bug in the type inference regarding cases where not type information is present.

• Add a PyLint checker for calls to print().

• Extend the blacklist of modules that shall not be analysed.

• Raise RuntimeError from tracer when called from another thread.

• Provide better exception messages for critical failures.

• Apply a further limit to the execution time of a single generated test case to at
  most 10 seconds.

• Exclude empty enum classes from test cluster to fix test generation.

  Parsing included modules raised an issue when the enum module is used: the test
  cluster then had a reference to the enum.Enum class, which obviously does not
  contain any fields. In the following, generating tests failed, as soon as this
  class was selected to fulfil parameter values because there was no field to select
  from, e.g., MyEnum.MY_FIELD. We now exclude empty enums from the test cluster.

Pynguin 0.21.0

• Fix a bug in the module analysis regarding nested functions

  Nested functions/closures caused Pynguin's module analysis to crash with an
  failing assertion.

• Improve the branch-distance computation for bool values

• Allow for more statistics variables regarding number of lines and cyclomatic
  complexity

Pynguin 0.20.1

• Fix a bug in terminating Pynguin due to threading

Pynguin 0.20.0

Breaking Changes

• Remove splitting into passing and failing test suite.

  Previously, we consider a test case passing if it did not raise any exception
  during its execution; it was considered failing otherwise. Pynguin did a split of
  the test cases into two test suites before exporting them. This was mainly an
  artefact from implementing the random algorithm in the very beginning of the
  project. Due to the improved assertion export for exception assertions we can now
  get rid of the split and export only one test module containing all generated test
  cases.

• Remove the option to use a log file (--log_file or --log-file).

  Pynguin writes its output to STDOUT/STDERR now, if requested by the -v/-vv switch.
  This output is formatted by @willmcgugan's amazing
  rich library. A user can disable the output
  formatting by setting the --no-rich flag. Of course, because we believe that rich
  is such an awesome library, we also provide an alias for this flag, called --poor😉

Further Changes

• Distinguish between expected and unexpected exceptions.

  We consider an exception to be expected if it is explicitly raised in the code
  under test or is documented in the code's docstring. For those exceptions we
  build an with pytest.raises block around the exception-raising statement. All
  other exceptions are considered to be unexpected. We decorate the test method
  with the @pytest.mark.xfail decorator and let the exception happen. It is up to
  the user to decide whether such an exception is expected. An exception here is
  the AssertionError: it is considered to be expected as soon as there is an
  assert statement in the code under test.

• Improve installation description to explicitly point to using a virtual environment
  (see GitHub issue #23, thanks to @tuckcodes).

• Improve variable names and exception assertions

  The assertion generation got an improved handling for asserting on exceptions,
  which creates more meaningful and (hopefully) better understandable assertions for
  exceptions.

• Enhance the module analysis

  This is basically a rewrite of our previously existing test cluster, which keeps
  track of all the callables from the subject under test as well as the subject's
  dependencies. It also incorporates an analysis of the subject's AST (if present)
  and allows for more and more precise information about the subject which can then
  improve the quality of the generated tests.

• To distinguish bytecode instructions during instrumentation we add an
  ArtificialInstr for our own added instructions.

• Fix a bug in the tracing of runtime types.

  During assertion generation Pynguin tracks the variable types to decide for which
  values it actually is able to generate assertions. Creating an assertion on a
  generator function does not work, as the type is not exposed by Python but only
  present during runtime—thus generating an object of this type always fail. We
  mitigate this by ignoring objects of type builtins.generator from the assertion
  generation.

• Improve documentation regarding coverage measurement and the coverage report

Pynguin 0.19.0

Breaking Change

• One can now use multiple stopping conditions at a time.

  This breaks the CLI in two ways:

  • The parameter --stopping-condition has been removed.
  • The parameter --budget was renamed to --maximum-search-time.

  Users have to change their run configurations accordingly!

  To specify stopping conditions, add one or many from --maximum-search-time, --maximum-test-executions, --maximum-statement-executions, and --maximum-iterations to your command line.

Further Changes

• Clarify log output for search phases
• Pynguin now uses the ast.unparse function from Python's AST library instead of the third-party astor library to generate the source code of the test cases.

Pynguin 0.18.0

Breaking Change

• We drop the support for Python 3.8 and Python 3.9 with this version!

  You need Python 3.10 to run Pynguin! We recommend using our Docker container,
  which is already based on Python 3.10, to run Pynguin.

Further Changes

• Add line coverage visualisation to the coverage report.
• Add a citation reference to our freshly accepted ICSE'22 tool demo paper “Pynguin:
  Automated Unit Test Generation for Python.
• Unify the modules for the analysis of the module under test.

Pynguin v0.17.0

• Add line coverage as another coverage type (thanks to @labrenz).
  The user can now choose between using either line or branch coverage or both by setting the parameter --coverage-metrics to LINE, BRANCH, or LINE,BRANCH.
  Default value is BRANCH.

Pynguin v0.16.1

• Update CITATION.cff information

Pynguin v0.16.0

• Refactor the assertion generation. This unifies the SIMPLE and the
  MUTATION_ANALYSIS approaches. Furthermore, Pynguin now uses the
  MUTATION_ANALYSIS approach again as the default.
• Update the type annotations in Pynguin's code to the simplified, future versions
  (e.g. instead of Dict[str, Set[int]] we can now write dict[str, set[int]]) and do
  not need any imports from Python's typing module.
• Fix a crash of the seeding when native modules are present. Fixes #20.
• Provide a hint in the documentation that PyCharm 2021.3 now integrates poetry
  support, thus no plugin is required for this (and newer) versions (thanks to
  @labrenz).