glados 0.1.0

🍰 A property-based testing framework that tries to break your invariances.

Testing is tedious! At least that's what I thought before I stumbled over property-based testing – a simple approach that allows you to write less tests yet gain more confidence in your code.

Instead of defining concrete inputs and testing whether they result in the desired output, you define certain conditions that are always true (also called invariants). In mathematics, there's the ∀ operator for that. In Dart, now there's glados.

dev_dependencies:
  test: ...
  glados: ...

• Getting started
• Strengths
• How does it work?
• Customizing Glados testing
  • Multiple inputs
  • Arbitraries
  • Custom Arbitraries
  • Explore
• What's up with the name?
• Further info & resources

Getting started

Suppose you write a function that tries to find the maximum in a list. I know – that's pretty basic – but it's enough to get you started. Here's an obviously wrong implementation:

/// If the list is empty, return null, otherwise the biggest item.
int max(List<int> input) => null;

To be sure that the function does the right thing, you might want to write some tests. Here's how those would look like in traditional unit testing:

test('maximum of empty list', () {
  expect(max([]), equals(null));
});
test('maximum of non-empty list', () {
  expect(max([40, 2, 10]), equals(40));
});

Not familiar with the syntax of the test package? Here are the docs.

Executing pub run test path/to/tests.dart should show that the second test fails.

In property-based testing, you look for invariants – conditions that should be true for any input. For example, if max produces null, the list should be empty:

Glados<List<int>>().test('maximum is only null if the list is empty', (list) {
  if (max(list) == null) {
    expect(list, isEmpty);
  }
});

You can create a Glados instance and call it's test method instead of using the normal test function. Glados takes a generic type parameter – in this case, List<int>. It then tests your code with a variety of inputs of that type. All of them need to succeed for the whole test to succeed.

Running the test should produce something like this:

Tested 1 input, shrunk 25 times.
Failing for input: [0]
...

Glados discovered that a list containing 0 breaks the condition!

Let's modify our max function to pass this test:

int max(List<int> input) => 42;

We need to add another invariant to reject this function as well. Arguably the most obvious invariant for max is that the result should be greater than or equal to all items of the list:

Glados<List<int>>().test('maximum is >= all items', (list) {
  var maximum = max(list);
  if (maximum != null) {
    for (var item in list) {
      expect(maximum, greaterThanOrEqualTo(item));
    }
  }
});

Running the tests produces the following result:

Tested 35 inputs, shrunk 117 times.
Failing for input: [43]
...

Glados detected that the invariant breaks if the input list contains a 43.

Let's actually add a more reasonable implementation for max:

int max(List<int> input) {
  if (input.isEmpty) {
    return null;
  }
  var max = 0;
  for (var item in input) {
    if (item > max) {
      max = item;
    }
  }
  return max;
}

This fixes the tests, but still doesn't work for lists containing only negative values. So, let's add a final test:

Glados<List<int>>().test('maximum is in the list', (list) {
  var maximum = max(list);
  if (maxmium != null) {
    expect(list, contains(maximum));
  }
});

I'll leave implementing the function correctly to you, the reader.

But whatever solution you come up with, it'll be correct: Our tests aren't merely some arbitrary examples anymore. Rather, they correspond to the actual mathematical definition of max.

Strengths

• ⚡ You have to write fewer tests.
• 💪🏻 You increase confidence in your code.
• 🤯 You develop a better understanding for the problem domain.

How does it work?

Glados works in two phases:

• The exploration phase: Glados generates increasingly complex, random inputs until one breaks the invariant or the maximum number of runs is reached.
• The shrinking phase: This phase only happens if Glados found an input that breaks the invariant. In this case, the input is gradually simplified and the smallest input that's still breaking the invariant is returned.

Customizing Glados testing

Multiple inputs

You can use Glados2 and Glados3 for Glados tests with multiple inputs. If you need support for more inputs, don't hestitate to open an issue.

Glados2<int, int>().test('complicated stuff', (a, b) {
  ...
})

Arbitraries

Arbitrarys are responsible for generating and shrinking values. They have two methods:

• T generate(Random random, int size) generates a new value of type T, using random as a source for randomness. The size argument is used as a rough estimate on how big or complex the returned value should be.
  For example, the Arbitrary for int produces ints in the range from -size to size.
• Iterable<T> shrink(T input) takes a value and returns an Iterable containing similar, but smaller values. Smaller means that calling shrink repeatedly on the smaller values and their children etc., the program should eventually terminate (aka the transitive hull with regard to shrink should be finite and acyclic).

The basic types all have corresponding Arbitrarys implemented.

Glados also accepts an optional Arbitrary that can be used to customize the input values. Also, there's any, which provides a namespace for Arbitrarys.

For example, if you want to test some code only with lowercase letters, you can write:

Glados(any.lowercaseLetters).test('text test', (text) { ... });

Custom Arbitraries

Sometimes it makes sense to create custom Arbitrarys.

For example, if you test code that expects email addresses, it may be inefficient to test the code with random Strings; if the tested code contains some sanity checks at the beginning, only a tiny fraction of values actually passes through the rest of the code.

In that case, create a custom Arbitrary. To do that, add an extension on Any, which is a namespace for Arbitrarys:

extension EmailArbitrary on Any {
  Arbitrary<String> get email => arbitrary(
    generate: (random, size) => /* code for generating emails */,
    shrink: (input) => /* code for shrinking the given email */,
  );
}

Then, you can use that Arbitrary like this:

Glados(any.email).test('email test', (email) { ... });

If you create an Arbitrary for a type that doesn't have an Arbitrary yet (or you want to swap out a built-in Arbitrary for some reason), you can set it as the default for that type:

// Use the email arbitrary for all Strings.
Any.setDefault<String>(any.email);

Then, you don't need to explicitly provide the Arbitrary to Glados anymore. Instead, Glados will use it based on given type parameters:

// This will now use the any.email arbitrary, because it was set as the
// default for String before.
Glados<String>().test('blub', () { ... });

Explore

You can also customize the exploration phase. To do that, you can use Explore, which is a configuration for certain values used during that phase.

For example, if you want to test some code with very big inputs, you might adjust Explore's parameters so that Glados starts with very big inputs and generates much bigger inputs after just a few runs:

Glados(any.email, Explore(
  initialSize: 100, // Start quite big
  speed: 10,        // and increase the input size by 10 each run,
  numRuns: 10,      // but only do 10 runs instead of 100.
)).test('my test', (input) {
  ...
});

Explore also has a random parameter, which you can provide with a custom Random instance. By default, Explore uses a Random instance created with a fixed seed so that your tests are deterministic.

What's up with the name?

GLaDOS is a very nice robot in the Portal game series. She's the head of the Aperture Science Laboratory facilities, where she spends the rest of her days testing. So I thought that's quite a fitting name. 🍰

Further info & resources

• Here's the talk that got me into property-based testing.
• This article covers the topic in more detail.