Adding unit testing section

doc/source/contribution_and_api/index.rst

@@ -123,7 +123,6 @@ MAPDL commands mapped to PyMAPDL, see :ref:`ref_mapdl_commands`.
 
    commands
    database
-   building_example
    geometry
    helper
    inline
@@ -138,3 +137,5 @@ MAPDL commands mapped to PyMAPDL, see :ref:`ref_mapdl_commands`.
    post
    solution
    xpl
+   building_example
+   unit_testing

doc/source/contribution_and_api/unit_testing.rst

@@ -0,0 +1,84 @@
+.. _ref_unit_testing_contributing:
+
+Unit Testing
+============
+
+Unit tests are testing functions which validate that the software
+logic implemented inside a certain method, class or module is
+working as expected. They should try to be as atomic and 
+independent as possible.
+
+Unit testing is highly important. It enables to check that the
+changes on the code are consistent with other parts of the code
+and verify that the changes are the expected in the implementation.
+
+Unit tests are in the ``tests`` directory inside this repository.
+All the tests that you will find in this  directory are not
+unit tests. Some of them are integration tests. The difference between
+a unit test and an integration one is that integration tests will
+test several units of the code and ensure that they work together.
+
+To verify that all the code is properly tested, `Codecov <https://github.com/codecov>`_
+generates a coverage report of the committed code. It details how
+merging the Pull Request will impact the coverage. It is one of
+the checks that must be approved to merge the code.
+
+Test Validation GitHub workflow
+-------------------------------
+
+Unit tests and integration tests are part of the Continuous Integration (CD) approach. 
+Combined with the Continuous Development (CD) one, they form the CI/CD approach. 
+The latter provides continuous automation and monitoring
+throughout the application lifecycle: from the coding and testing
+phases to the deployment phase.
+
+.. figure:: ../images/cicd.jpg
+    :width: 300pt
+
+Create a unit test 
+------------------
+
+In the PyMAPDL repository, tests run using ``pytest``. 
+
+To create a pytest file, its name must be in the form ``test_filename.py``.
+
+Here are some checks to create a good unit test: 
+
+1. The test method name is long and descriptive.
+2. The result of the test for PASS/FAIL is automatic. 
+3. The tests cover all the scenarios of the code. You can check it with **Codecov**.
+4. The test should return the same result each time. 
+5. The tests are independent.
+6. Each test verifies only one part of the code at a time.
+7. The test should run fast.
+
+`What makes a good unit test <https://stackoverflow.com/questions/61400/what-makes-a-good-unit-test>`_ 
+is an exhaustive list of tips for creating good unit tests.
+
+Since the majority of PyMAPDL tests imply server connection, most of the test are integration tests.
+
+`The unit tests and the integration tests <https://github.com/pyansys/pymapdl/blob/main/tests/test_math.py>`_ of the 
+**ansys.mapdl.core.math** library are one of the numerous tests that you can find in
+the `test directory <https://github.com/pyansys/pymapdl/tree/main/tests>`_ .
+You will find examples to understand how you can use the ``pytest`` package. Here is two of them: 
+
+.. code:: python
+
+    >>> import numpy as np
+    >>> import ansys.mapdl.core.math as apdl_math
+
+    >>> @pytest.fixture(scope="module")
+    >>> def mm(mapdl):
+    >>>     return mapdl.math
+
+    >>> def test_rand(mm):
+    >>>     w = mm.rand(10)
+    >>>     assert w.size == 10
+
+    >>> def test_matrix_addition(mm):
+    >>>     m1 = mm.rand(10, 10)
+    >>>     m2 = mm.rand(10, 10)
+    >>>     m3 = m1 + m2
+    >>>     assert np.allclose(m1.asarray() + m2.asarray(), m3.asarray())
+
+You can find the `pytest documentation <https://docs.pytest.org/en/7.2.x/>`_ for further explanations.