In 2018 I was taking a break from work. I wanted to upgrade my skills while looking for new opportunities. My previous job was working in a NodeJS environment which I certainly enjoy in many ways but PHP is actually my favorite language to work with so I wanted to challenge myself to learn something new.

I had two goals really. The first was to learn. I wanted to see what continuous integration was actually all about. The second was to prove the rock solid design of the ORM library I've been using for the past five years. It was passed around by a few local developers I knew but using it in production on new projects became an increasingly hard battle as most people wanted to use other ORMs that were more popular. It felt like without unit tests and a code coverage badge and a page on packagist I had no legitimacy. With that in mind I got to work.

With this post I hope to write down what I learned in a clear, concise, and easy to understand way for moderately experienced PHP developers and for myself.

Code Coverage

Code coverage is a line by line yes/no report from PHPUnit that simply says if that line has been tested or if it has not. You can get a code coverage report on your own computer just by running PHPUnit with XDebug enabled. Just add the command line switch --coverage-clover clover.xml when you run PHPUnit.

Here you can see I'm telling phpunit where to put the code coverage report. You will need Xdebug as well for the feature to be available. A clover.xml file by itself though is just raw data and without a proper interface to view it you won't really be able to make much use of it.

View the Code Coverage Report

One website which provides this is Codecov.io

They give you a simple to use bash install script.

You can run it right now with the report you already generated right in the terminal.

You can see it found my code coverage report but it still wants me to provide a repository token.

You should probably sign up at this point and claim your free private repository. If your project is open-source you can have as many as you want!

Once signed up you will find the token in the repository settings. They give you a few ways to specify the token there.

Personally for open source projects I prefer to use environmental variables since I won't have to .gitignore the codecov.yaml file.

Now you can run the report uploader script from above again.

Now that it uploaded you can take a look at the report.

As you can see my initial commit had terrible code coverage. The code was still not even organized as per PSR-4 and PHP League standards but at least I had base line and there's no where to go but up.

The PHP League

The PHP League of Extraordinary Packages make a slew of excellent packages but they also provide a skeleton template available in this Git repository that documents the proper modern way of organizing a PHP project. It was invaluable to me as a reference.

It shows you how to configure badges, continuous integration, organize your source code, and lots of other best practices.

Continuous Integration

Now that we know the code coverage report works we can setup continuous integration. I'd recommend TravisCI but if you have Bitbucket premium it comes with 500 free minutes of their continuous integration solution called Pipelines. Pipelines and TravisCI are basically just plugins for Github or Bitbucket or any other host of your Git repository. They get event hooks when your code gets pushed to your Git host and then they run a bash script in a container with your code. You can then run tests, do builds, and setup other automated solutions for your source code. But how you ask? Well there's a YAML file you have to create. In this example I will show my Travis file. The source is available here.

language: php
php:
  - '7.1'
  - '7.2'

addons:
  apt:
    sources:
      - mysql-5.7-trusty
    packages:
      - mysql-server
      - mysql-client

before_install:
  #- sudo mysql -e "use mysql; update user set authentication_string=PASSWORD('divergence_tests') where User='root'; update user set plugin='mysql_native_password';FLUSH PRIVILEGES;"
  #- sudo mysql_upgrade
  #- sudo service mysql restart
  - mysql -e 'CREATE DATABASE IF NOT EXISTS test;'

install:
    # Install composer packages
  - travis_retry composer update --no-interaction --no-suggest
  - travis_retry composer install --no-interaction --no-suggest
  # Install coveralls.phar
  - wget -c -nc --retry-connrefused --tries=0 https://github.com/php-coveralls/php-coveralls/releases/download/v2.0.0/php-coveralls.phar -O coveralls.phar
  - chmod +x coveralls.phar
  - php coveralls.phar --version

before_script:
    - mkdir -p build/logs
    - ls -al

script:
  - ./vendor/bin/phpunit --coverage-clover build/logs/clover.xml

after_success:
# Submit coverage report to Coveralls servers, see .coveralls.yml
 - travis_retry php coveralls.phar -v
# Submit coverage report to codecov.io
 - bash <(curl -s https://codecov.io/bash)

 # Tell Travis CI to monitor only 'master' branch
branches:
  only: master

# Specify where the cache is so you can delete it via the travis-ci web interface
cache:
  directories:
  - vendor
  - $HOME/.cache/composer

This file basically tells Travis what to do.

• Which versions of PHP to test with.
• Which branches of the git repo to run against.
• Sets up the localhost MySQL environment for our PHPUnit tests in the container.
• Runs composer dependency installer
• Runs PHPUnit
• Uploads the code coverage report.

The best part? You get an email at the end with what got fixed or any new problems. TravisCI also runs a rudimentary static analyzer on your code bringing up problems with the source as well as your PHPDoc notation which adds even more added value to having your unit tests run automatically every time you update a given branch.

In Github you even get this view available to you all in one place.

The Road to 90%

Initially you come to the realization that your ability to increase the score through your simple and basic helper classes lets you score a few easy wins early on. Ripping out old, unused, verbose, and unclean code also lowers your total code count thereby increasing your overall coverage score. Sometimes you actually have to edit your code to make it easier to test. Standalone global code in PHP files becomes even more onerous as testing that code becomes next to impossible. Let's take a look at a few examples.

Editing your code to make it easier to test.

Here I need to fake the stream php://input which is what we parse for raw JSON data sent via POST. Doable but only by creating your own fake stream and at a different address.

But it's okay because it enabled this simple test. Which increased the coverage of that one file by 13.33%. By the way virtual streams are pretty awesome. Check out the test below.

    /**
     * @covers Divergence\Helpers\JSON::getRequestData
     */
    public function testGetRequestData()
    {
        $json = '{"array":[1,2,3],"boolean":true,"null":null,"number":123,"object":{"a":"b","c":"d","e":"f"},"string":"Hello World"}';
        vfsStream::setup('input', null, ['data' => $json]);
        JSON::$inputStream = 'vfs://input/data';

        $x = json_decode($json,true);
        $A = JSON::getRequestData();
        $B = JSON::getRequestData('object');

        $this->assertEquals($A, $x);
        $this->assertEquals($B, $x['object']);
    }

Ripping Out Old Code

Here I found a function that was previously used to manually prettify JSON used way back when PHP didn't have this functionality built in. Sometimes it's sad to delete old code. Especially when it's will written, clean, and easy to understand. But sometimes it's just time to let it go and let someone else worry about it.

Lets just say I cut a lot of random old code. This obviously had a great impact on the readability and cleanliness of the code going forward.

What I did for Database Unit Testing

Eventually I ran out of low hanging fruit testing things that had nothing to do with the database and then... it was time for the database. A number of issues came up.

• A test database would need to be created on my laptop that mirrors the TravisCI config to avoid having to write extra logic. I added a new 'testing' default config to the default database config that comes with the framework.
• I needed to add some bash terminal commands to the TravisCI file above to make it reset the database every time.
• I need a way to run some code the unit tests need to run before all the unit tests would begin to setup a bunch of fake data.

To solve this I created a class which implements PHPUnit's PHPUnit_TestListener interface. I previously wrote a post on doing this in detail.

Now to make sure we run our code before all the tests run we do this.

So here we initialize our mock application and set the database connection to use the tests-mysql config.

App::setUp is actually where the mock data is created.

Fake it till you make test it

To make this database testing thing actually work I actually made a fake site that would live in the PHPUnit environment. I gave it a separate namespace in the tests namespace.

The App class from earlier? You can view it here.

As I wrote more unit tests I added more and more Tag creation stuff to this function. As I created more and more mock data attacking the more and more complex situations in my tests became easier and easier.

Lowering Code Complexity

As you get further and further into testing your code you will come to some code which has lots of complex conditional statements with multiple conditions which might potentially have any n-number of possible combinations. By breaking out your code into ever smaller and smaller methods it is possible to make every method have a very low number of combinations hopefully in the single digits.

For example the increased conditional complexity of the code below make it difficult to get tests which achieve 100% unit test coverage because you need to provide every possible permutation of conditionals and if there are more obviously there could be more conditions.

I changed the above to be a switch($options['type']) instead and broke out each type into it's own function. The new functions become much easier to test with fewer conditional permutations to keep track of.

Writing tests for these much simpler functions becomes almost trivial and the code looks much cleaner too.