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Some time ago, in between working on Zend Framework, I booted up a couple of libraries that I really wanted to integrate into my workflow. Recently, I’ve been being putting these through the grindmill so they can be properly released and supported for public consumption across PEAR. Just as Mockery fell out of older work on PHPMock, Mutagenesis will fall out of another project called MutateMe. This is a short introductory article as to what Mutagenesis will do and why. In other words, what the heck is Mutation Testing?

First, some background.

The most common means of measuring confidence in a test suite is the Code Coverage metric. Code Coverage essentially checks, on a per class basis, how many of the lines of code in the class are executed by a test suite and expresses this as a percentage. For example, a Code Coverage of 85% means 85% of the lines of code in a class was executed and 15% were not. The greater the number of lines of code executed, the more confidence one can presumably have that a test suite is doing its job, i.e. verifying class behaviour, preventing the introduction of bugs, supporting refactoring, and so on.

I have a huge and insurmountable problem with Code Coverage. For starters, my average Code Coverage is closer to 80% than the 90% expected of projects such as Zend Framework. The gap is explained by me not testing what I call “braindead” functions, i.e. methods which are either ridiculously simple, where a malfunction would quickly become self-evident, or which are marginalised (on the borders of deprecation). So Code Coverage actually increases the amount of work I need to do for very little gain and a lot of frustration.

Secondly, Code Coverage is easy to spoof or misinterpret. Since it’s a metric measuring the execution of source code, you need only…well…execute the source code. It’s a simple matter to construct a series of wonderfully useless tests to do just that and obtain a high Code Coverage result – it’s done all the time in my experience once someone’s patience in writing quality unit test runs out. It is particularly evident in cases where unit tests are written after the source code is completed – a still too common practice in PHP. The less villainous flipside is that certain nuggets of source code are fundamentally difficult to test. For example, a complex algorithm suffering from poor documentation may make composing a suitable unit test near impossible. The rollout of OAuth was filled with such examples.

This leads into my opinion of Code Coverage. I view the venerable Code Coverage metric as a near pointless exercise. While it may tell how much source code a test suite exercises, it tells you nothing about the actual quality of those unit tests. They could be good tests, sort-of-good tests or absolutely horrendous tests – Code Coverage will never tell you either way. I say near pointless because there are precious few alternatives. We need something to give us a reason to trust and have confidence in test suites and Code Coverage is easy to implement and has been a part of PHPUnit since forever. So, by and large, we make do. We measure Code Coverage just to make certain some kind of unit testing was performed.

Is there nothing better?

A good unit test serves a simple purpose. It verifies a behaviour of an object. In PHP, we’re more likely to verify umpteen million behaviours in a single test (count your assertions!) but we’ll let that slide. Since a test verifies behaviour, it follows that a test should fail when that behaviour is changed. If a test does not fail when class behaviour is changed, it also follows that the original behaviour was not fully tested, i.e. there is a gaping hole in our test suite whether due to a flawed or missing test that could allow bugs entry into our application. So, to really stick unit tests under a microscope to assess their quality and our confidence in them, we need to introduce changes into the source code under test and see if the unit test suite can or cannot detect them.

This process is known as Mutation Testing. Mutagenesis is a Mutation Testing framework for PHP 5.3+.

Mutation Testing, as you have probably surmised, is not a super-complex activity. You take a set of source code and compile a list of possible “mutations” that are likely to break the behaviour of the source code. Then, you apply one mutation to that source to create a “mutant”, i.e. a copy of the source code with the mutation change applied. Next, you run the source code’s test suite against the mutant and see if any tests fail. If a test fails, celebrate – the mutation was detected so your tests were, in this instance, adequate. If no test fails, curse the Gods – the mutation was not detected and you’ll need to figure out whether a new test is needed or an old one modified/corrected. Rinse and repeat the above for each mutation you’ve compiled.

Mutations are typically quite simple such as replacing operators, booleans, strings and other scalar values with either an opposing form or a random value. Expressions might also be reversed or driven to zero to give an opposing boolean or zero value. Making such minor changes seems like a minor irritation but behind every serious flaw in an application is one or more smaller contributing errors. If your test cases can detect the potentially contributing errors, then there’s an excellent chance it would detect the bigger ones anyway. This is known as the Coupling Effect in Mutation Testing.

Some of you will be vaguely aware of Mutation Testing. In terms of implementations, Ruby has heckler, Python has Pester, and Java has Jumbler, Jester and a couple of others. Those who prefer Microsoft’s technologies can use Nester. There’s a running ryhme apparent since so much is inspired by the original Jester framework for Java. To my knowledge, Mutagenesis will be the only Mutation Testing framework for PHP (though I sincerely wish I was wrong).

Examining those libraries, you eventually realize a few problems with Mutation Testing which explain its lack of popularity until relatively recently: performance is a concern and Mutation Testing requires a Human Brain to complete the process.

Performance is a concern because each mutation requires a test suite to be executed. Imagine a set of classes from which you extract 100 possible mutations, coupled with a test suite that takes 5 minutes to run. A basic Mutation Testing framework (e.g. Ruby’s heckler) would therefore take 500 minutes to complete a Mutation Testing session. That’s 8.3 hours of continuous Mutation Testing. Mutation Testing for Zend Framework would be very interesting .

Similar to Jumbler for Java, Mutagenesis will utilise a few heuristics (shortcuts) to significantly improve performance without compromising results. We only need one single test to fail in order to rule that a mutation was detected and killed, so we can do a few things to boost performance:

1. Terminate the test suite on first failure/error or exception.
2. Execute test cases in order of execution time ascending (fastest first; slowest last).
3. Prioritise execution of last test case to detect a mutant to take advantage of same-class detection.
4. Log which tests detect which mutations, and prioritise those associations in subsequent runs.

The effect of the above is to speed up Mutation Testing by a significant degree. The final heuristic ensures that for gradually changing source code and tests, the first Mutation Testing process might take a while but subsequent runs will be significantly faster making them far more usable in a Test-Driven Development setting. Mutation Testing is best served with a healthy dose of efficiency.

The second reason for its lack of popularity is that Mutation Testing can’t analyse the logic of the source code under test. For example, an expression might accept any integer less than 10 to evaluate to TRUE. If the input from another class were 7, and a mutation were generated to swap this for a 9, then the associated unit test would still pass (the mutation of switching 7 for 9 still allows the <10 expression evaluate to TRUE). If you recall, if a mutant passes a test suite than we assume either the presence of a flawed test or the lack of a suitable test. Obviously, as the above suggests, this isn’t always the case. Mutation Testing can and often will report false positives.

Ruling out false positives, coupled with the need to improve test suites to detect more mutations, makes Mutation Testing a source of extra work. Who likes extra work least? Programmers, especially the lazy kind .

Mutation Testing is not a far fetched idea. The principles are sound and it beats the pants off Code Coverage when it comes to measuring what confidence we can have in our testing suites. It is still hampered, as a methodology, by the lack of good implementations in other programming languages. Mutagenesis, by adopting implementation heuristics from Java’s Jumbler, should avoid that fate and offer a decent framework in PHP that performs as well as can be expected.

Once it’s released…of course . Mutagenesis is in development but should see a fresh release in a couple of weeks alongside Mockery. I’ll be looking forward to seeing how people perceive it. Mutation Testing has zero presence in PHP to date but having something to complement Code Coverage can’t do any harm!