README.md

Writing unit tests

This readme file describes steps to create unit tests for NiftyNet.

1. Find out which NiftyNet modules require unit tests

Go to Cmiclab pipeline page, click on the latest successful testing pipeline and check the test coverage report at the bottom of the test log, e.g. a coverage report is available at the last part of this log. The coverage report lists all untested files (with line numbers of specific statements) in the project.

2. File an issue on the issue list

Create a new issue indicating that you'll be working on the tests of a particular module.

To avoid duplicated effort, please check the issue list and make sure nobody is implementing the unit tests for that module at the moment. Also make sure the issue description is concise and has specific tasks.

3. Create a [name]_test.py file in NiftyNet/tests/ folder

Clone NiftyNet and create a dedicated branch (from dev) for the unit tests.

git clone git@cmiclab.cs.ucl.ac.uk:CMIC/NiftyNet.git
git checkout -b unit-test-for-xxx dev

Create a unit test Python script with file name ends with _test.py in NiftyNet/tests/ folder. (CI runner will automatically pick up the script and run it with Python 2.7&3)

A minimal working template for [name]_test.py is:

# -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function

import tensorflow as tf

class ModuleNameTest(tf.test.TestCase):
    def test_my_function(self):
        x = tf.constant(1.0)
        self.assertEqual(x.eval(), 1.0)
    # preferably using self.assert* functions from TensorFlow unit tests API
    # https://www.tensorflow.org/versions/r0.12/api_docs/python/test/unit_tests

if __name__ == "__main__":
    # so that we can run this test independently
    tf.test.main()

If the unit tests write files locally, please ensure it's writing to NiftyNet/testing_data folder.

4. Run the unit test locally

In NiftyNet source code folder, run:

python -m tests.[name]_test.py

make sure the test works locally. The test should finish in a few seconds (using CPU). If it takes significantly longer, please set it as slow test in the file:

...
@unittest.skipIf(os.environ.get('QUICKTEST', "").lower() == "true", 'Skipping slow tests')
class ModuleNameTest(tf.test.TestCase):
    def test_my_function(self):
        pass
    # preferably using self.assert* functions from tensorflow unit tests API
    # https://www.tensorflow.org/versions/r0.12/api_docs/python/test/unit_tests
...

5. Run all unit tests locally

Normally the newly created unit test should not depend on the outcome of the other unit tests. A Bash script is defined here for running all quick tests to confirm this.

(In run_test.sh, wget and tar are used to automatically download and unzip testing data. This can be done manually.)

6. Push to Cmiclab and send a merge request

After finishing the local tests, git-push the changes to a Cmiclab branch. This will trigger CI tests, which will run the unit tests on our test server with Ubuntu Linux + Python 2&3).

Please send a merge request with only relevant changes to a particular unit tests.

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Thanks for your contributions :)