Pynguin v0.15.0

• Fix a bug for mutating a statement that is not in the current test case (see #17).
• Set default assertion generation to SIMPLE due to issues with the experimental
  new generation strategy.
• Add GitHub Actions that also runs our CI chain on GitHub.

Pynguin v0.14.0

• Breaking: Simplify the logging such that Pynguin uses different log levels also
  for the log file. This removes the -q option to make all outputs quiet.
• Pynguin now also supports field accesses during test generation. This is a
  preliminary feature.
• Fix a deadlock in the executor
• Pynguin now uses Python 3.10 as its default version for the provided Docker
  container as well as our CI. Still, Pynguin supports Python 3.8 and 3.9. Up to now,
  Python 3.11 is not yet supported.
• Refactor the state-trace implementation
• Remove the module-loader singleton
• Fix loading of mutated module for assertion generation. Caused that no assertion
  was generated because the mutants were not loaded properly. This is a regression
  from merging the assertion-generation strategy in Pynguin 0.13.0.

Pynguin v0.13.2

• Add the reference to the preprint of our EMSE journal submission to documentation.
• Clarify on the value of the PYNGUIN_DANGER_AWARE environment variable. One can
  set an arbitrary value for the variable, Pynguin only checks whether its defined (#16 ).

Pynguin v0.13.1

Fix documentation generation by adding our MutPy fork as a dependency

Pynguin v0.13.0

• Add an assertion-generation strategy based on mutation (thanks to @f-str).

  The new strategy is enabled by default (can be configured using the
  --assertion-generation parameter). It uses a custom
  fork of the mutation-testing framework
  MutPy, which mutates the subject under test and for
  each mutant traces the values of fields and returned by method calls. If these values
  differ between mutant and original code, an assertion is generated based on the result
  on the original subject under test. One can also control whether the strategy shall
  also generate assertions for unchanged values by the --generate-all-assertions flag.

  The release also updates the documentation accordingly.

  Note: This feature is an early prototype of such an assertion generation, which
  might cause unexpected behaviour. You can switch back to the previous strategy for
  assertion generation by setting --assertion-generation SIMPLE.

Pynguin v0.12.0

• Generate more reasonable variable names in tests.
  Before this release, Pynguin only generated variables named var0, var1, etc.
  A simple heuristics now attempts to generate more reasonable names depending on the
  type of the variable, such as int_0, bool_1, or str_2.
  We also adjusted the documentation to match this change.
• We updated all provided PyCharm run configurations the use the more sophisticated
  queue example instead of the simple example module to see an improved output.
• Prevent a potential regression when updating the dependencies to version 0.0.17 of the
  simple-parsing library for CLI argument
  parsing, which changed its API.

Pynguin v0.11.0

• Fix a control-dependency bug in DynaMOSA. Loops in the control-dependence graph
  caused DynaMOSA to not consider certain targets because they were control
  dependent on goals that had not yet been covered due to the loop.
• Improve documentation
• Split and extend FitnessValues to avoid expensive re-computations. This also
  extends the API of the FitnessValues and refactors large parts of the fitness
  handling.
• Fix for bumpiness of flaky tests. Whenever Pynguin generates a test that behaves
  flaky result could be that coverage over time looks like ventricular fibrillation
  especially for the MIO algorithm. The fix prevents this by carefully revisiting
  the equality of chromosomes.
• Improve handling of entry/exit nodes in the CFG; this fixes issues with Python 3.10

Pynguin v0.10.0

• Provide support for Python 3.10
• Pynguin now set typing.TYPE_CHECKING = True explicitly before parsing the
  subject under test in order to be able to collect also information about types
  that are only imported due to type checking/providing type annotations.
• Improved generation of collection statements
• Cleanup the implementation of the algorithms
• Add supports for enums in the test-generation process
• Cleanup the implementation of the dynamic value seeding
• Make Pynguin executions as deterministic as we possibly can
• Make DynaMOSA the default algorithm
• Allow the generation of an HTML coverage report similar to the one generated by
  Coverage.py. This allows to show the subject under test and the coverage achieved
  by the test cases generated by Pynguin in the web browser.
• Add a CITATION.cff file
• Improve the internal control-flow graph
• Improve the documentation
• Cleanup and remove unused code
• Fix a bug in post-processing
• Fix a bug in branch coverage instrumentation on for loops
• Add a variant of the whole-suite algorithm that uses an archive
• Guard imports that are only necessary for type checking in Pynguin's modules by
  if typing.TYPE_CHECKING conditions

Pynguin v0.9.2

• Add explicit code-execution prevention (thanks to @Wooza).

  Pynguin now requires you to set the PYNGUIN_DANGER_AWARE environment
  variable before it actually does test generation. This was added due
  to the fact that Pynguin executes the module under test, including its
  dependencies, which could potentially cause harm on the user's system.
  By requiring the variable to be set explicitly, a user confirms that
  they are aware of this issue. Inside the Docker container, the
  variable is set automatically; we highly recommend this way of
  executing Pynguin!

Pynguin v0.9.1

• Fix spelling errors in README