MutPy-Pynguin 0.7.1
Mutation testing tool for Python 3.x source code.
Requires Python: >=3.8

MutPy-Pynguin
=============

This is a fork of the original `MutPy <https://github.com/mutpy/mutpy>`_.
It fixes the long-standing issue that MutPy did not work properly on Python
3.8+, which was caused by changes in Python's AST.
Furthermore, this fork drops support for Python < 3.8;
the respective code will be removed in the future.

|Python Versions|

MutPy is a mutation testing tool for Python 3.3+ source code. MutPy
supports standard unittest module, generates YAML/HTML reports and has
colorful output. It applies mutation on AST level. You could boost your
mutation testing process with high order mutations (HOM) and code
coverage analysis.

Mutation testing
----------------

From article at Wikipedia:

    **Mutation testing** (or Mutation analysis or Program mutation)
    evaluates the quality of software tests. Mutation testing involves
    modifying a program's source code or byte code in small ways. A test
    suite that does not detect and reject the mutated code is considered
    defective. These so-called mutations, are based on well-defined
    mutation operators that either mimic typical programming errors
    (such as using the wrong operator or variable name) or force the
    creation of valuable tests (such as driving each expression to
    zero). The purpose is to help the tester develop effective tests or
    locate weaknesses in the test data used for the program or in
    sections of the code that are seldom or never accessed during
    execution.

Installation
------------

You can easily install MutPy from PyPi:

::

    $ pip install mutpy

... or if you want to have latest changes you can clone this repository
and install MutPy from sources:

::

    $ git clone git@github.com:mutpy/mutpy.git
    $ cd mutpy/
    $ python3 setup.py install

Example
-------

Main code (``calculator.py``) - we will mutate it:

.. code:: python

    def mul(x, y):
        return x * y

Test (``test_calculator.py``) - we will check its quality:

.. code:: python

    from unittest import TestCase
    from calculator import mul

    class CalculatorTest(TestCase):

        def test_mul(self):
            self.assertEqual(mul(2, 2), 4)

Now we can run MutPy in the same directory where we have our sources
files:

::

    $ mut.py --target calculator --unit-test test_calculator -m

This command will produce the following output:

::

    [*] Start mutation process:
       - targets: calculator
       - tests: test_calculator
    [*] All tests passed:
       - test_calculator [0.00031 s]
    [*] Start mutants generation and execution:
       - [#   1] AOR calculator.py:2  :
    --------------------------------------------------------------------------------
     1: def mul(x, y):
    ~2:     return x / y
    --------------------------------------------------------------------------------
    [0.02944 s] killed by test_mul (test_calculator.CalculatorTest)
       - [#   2] AOR calculator.py:2  :
    --------------------------------------------------------------------------------
     1: def mul(x, y):
    ~2:     return x // y
    --------------------------------------------------------------------------------
    [0.02073 s] killed by test_mul (test_calculator.CalculatorTest)
       - [#   3] AOR calculator.py:2  :
    --------------------------------------------------------------------------------
     1: def mul(x, y):
    ~2:     return x ** y
    --------------------------------------------------------------------------------
    [0.01152 s] survived
       - [#   4] SDL calculator.py:2  :
    --------------------------------------------------------------------------------
     1: def mul(x, y):
    ~2:     pass
    --------------------------------------------------------------------------------
    [0.01437 s] killed by test_mul (test_calculator.CalculatorTest)
    [*] Mutation score [0.21818 s]: 75.0%
       - all: 4
       - killed: 3 (75.0%)
       - survived: 1 (25.0%)
       - incompetent: 0 (0.0%)
       - timeout: 0 (0.0%)

First of all we run MutPy with few parameters. The most important are:

-  ``--target`` - after this flag we should pass module which we want to
   mutate.
-  ``--unit-test`` - this flag point to our unit tests module.

There are few phases in mutation process which we can see on printed by
MutPy output (marked by star ``[*]``):

-  main code and tests modules loading,
-  run tests with original (not mutated) code base,
-  code mutation (main mutation phase),
-  results summary.

There are 4 mutants generated in main mutation phase - 3 of them are
killed and only 1 mutant survived. We can see all stats at the end of
MutPy output. In this case MutPy didn't generate any incompetent (raised
``TypeError``) and timeout (generated infinite loop) mutants. Our
mutation score (killed to all mutants ratio) is 75%.

To increase mutation score (100% is our target) we need to improve our
tests. This is a mutant which survived:

.. code:: python

    def mul(x, y):
        return x ** y

This mutant survived because our test check if ``2 * 2 == 4``. Also
``2 ** 2 == 4``, so this data aren't good to specify multiplication
operation. We should change it, eg:

.. code:: python

    from unittest import TestCase
    from calculator import mul

    class CalculatorTest(TestCase):

        def test_mul(self):
            self.assertEqual(mul(2, 3), 6)

We can run MutPy again and now mutation score is equal 100%.

Command-line arguments
----------------------

List of all arguments with which you can run MutPy:

-  ``-t TARGET [TARGET ...]``, ``--target TARGET [TARGET ...]`` - target
   module or package to mutate,
-  ``-u UNIT_TEST [UNIT_TEST ...]``,
   ``--unit-test UNIT_TEST [UNIT_TEST ...]`` - test class, test method,
   module or package with unit tests,
-  ``--runner RUNNER`` - currently supported are: unittest (default), pytest (experimental)
-  ``-m``, ``--show-mutants`` - show mutants source code,
-  ``-r REPORT_FILE``, ``--report REPORT_FILE`` - generate YAML report,
-  ``--report-html DIR_NAME`` - generate HTML report,
-  ``-f TIMEOUT_FACTOR``. ``--timeout-factor TIMEOUT_FACTOR`` - max
   timeout factor (default 5),
-  ``-d``, ``--disable-stdout`` - try disable stdout during mutation
   (this option can damage your tests if you interact with
   ``sys.stdout``),
-  ``-e``. ``--experimental-operators`` - use experimental operators,
-  ``-o OPERATOR [OPERATOR ...]``,
   ``--operator OPERATOR [OPERATOR ...]`` - use only selected operators,
-  ``--disable-operator OPERATOR [OPERATOR ...]`` - disable selected
   operators,
-  ``-l``. ``--list-operators`` - list available operators,
-  ``-p DIR``. ``--path DIR`` - extend Python path,
-  ``--percentage PERCENTAGE`` - percentage of the generated mutants
   (mutation sampling),
-  ``--coverage`` - mutate only covered code,
-  ``-h``, ``--help`` - show this help message and exit,
-  ``-v``, ``--version`` - show program's version number and exit,
-  ``-q``, ``--quiet`` - quiet mode,
-  ``--debug`` - debug mode,
-  ``-c``. ``--colored-output`` - try print colored output,
-  ``--order ORDER`` - mutation order,
-  ``--hom-strategy HOM_STRATEGY`` - HOM strategy,
-  ``--list-hom-strategies`` - list available HOM strategies,
-  ``--mutation-number MUTATION_NUMBER`` - run only one mutation (debug
   purpose).

Mutation operators
------------------

List of MutPy mutation operators sorted by alphabetical order:

-  AOD - arithmetic operator deletion
-  AOR - arithmetic operator replacement
-  ASR - assignment operator replacement
-  BCR - break continue replacement
-  COD - conditional operator deletion
-  COI - conditional operator insertion
-  CRP - constant replacement
-  DDL - decorator deletion
-  EHD - exception handler deletion
-  EXS - exception swallowing
-  IHD - hiding variable deletion
-  IOD - overriding method deletion
-  IOP - overridden method calling position change
-  LCR - logical connector replacement
-  LOD - logical operator deletion
-  LOR - logical operator replacement
-  ROR - relational operator replacement
-  SCD - super calling deletion
-  SCI - super calling insert
-  SIR - slice index remove

Experimental mutation operators:

-  CDI - classmethod decorator insertion
-  OIL - one iteration loop
-  RIL - reverse iteration loop
-  SDI - staticmethod decorator insertion
-  SDL - statement deletion
-  SVD - self variable deletion
-  ZIL - zero iteration loop

Supported Test Runners
----------------------

Currently the following test runners are supported by MutPy:

- `unittest <https://docs.python.org/3/library/unittest.html>`_
- `pytest <https://docs.pytest.org/en/latest/>`_

License
-------

Licensed under the Apache License, Version 2.0. See LICENSE file.

MutPy was developed as part of engineer's and master’s thesis at
Institute of Computer Science, Faculty of Electronics and Information
Technology, Warsaw University of Technology.

Maintenance of this fork is done at the Chair of Software Engineering II,
Faculty of Computer Science and Mathematics, University of Passau, Germany.

.. |Python Versions| image:: https://img.shields.io/pypi/pyversions/MutPy-Pynguin.svg
   :target: https://github.com/se2p/mutpy-pynguin