An introduction to property-based testing with JUnit-Quickcheck

Even though I consider having an extensive set of unit and unit integration tests a good thing in almost any case, there is still a fundamental shortcoming with automated checks that I feel should be addressed more often. Almost all checks I come across are very much example-based, meaning that only a single combination of input values is being checked. This goes for unit-, API-level as well as UI-driven tests, by the way. Of course, this is already far better than not checking anything at all, but how do you make sure that your check passes (and thus your application works for all, or at least for a considerable subset of all possible input parameter combinations?

In most cases, it is computationally impossible to perform a check for every combination of all possible input values (have you ever tried to work out what all possible values for a single string input parameter are?), so we need an approach that is able to generate a lot of (preferably random) input values that satisfy a set of predicates, and subsequently verify whether the check holds for all these input values and value combinations. Enter property-based testing (see this post on Jessica Kerr’s blog for an introduction to the concept).

What is property based testing?
In short, property-based testing pretty much exactly addresses the problem described above: based on an existing check, randomly generate a lot of input parameter combinations that satisfy predefined properties and see if the check passes for each of these combinations. This includes using negative and empty parameter values and other edge cases, all to try and break the system (or prove its robustness, if you want to look at it from the positive side…). You can do this either manually – although this does constitute a lot of effort – or, and given the nature of this blog this is of course the preferred method, use a tool to do the menial work for you.

Why should you use property based testing?
Again, the answer is in the first paragraph: because property-based testing will give you far more information about the functional correctness and the robustness of your software than executing mere example-based checks. Especially when combined with mutation testing, property-based testing you will likely have you end up with a far more powerful and effective unit- and unit integration test suite.

Tool: JUnit-Quickcheck
So, what tools are available for property-based testing? The archetypical tool is QuickCheck for the Haskell language. Most other property-based testing tools are somehow derived from QuickCheck. This is also the case for JUnit-Quickcheck, the tool that will be used in the rest of this blog post. As the name suggests, it is a tool for the Java language, based on JUnit.

Our system under test: the Calculator class
For the examples in this blog post, we will use the same Calculator class that was used when we talked about mutation testing. In particular, we are going to perform property-based testing on the add() method of this simple calculator:

public class Calculator {

	int valueDisplayed;

	public Calculator() {
		this.valueDisplayed = 0;

	public void add(int x) {
		this.valueDisplayed += x;

	public int getResult() {
		return this.valueDisplayed;

An example-based unit test for the add() method of this admittedly very basic calculator could look like this:

public void testAdditionExampleBased() {
	Calculator calculator = new Calculator();
	assertEquals(calculator.getResult(), 2);		

Using JUnit-Quickcheck, we can replace this example-based unit test to a property-based test as follows:

@Property(trials = 5)
public void testAddition(int number) {
	System.out.println("Generated number for testAddition: " + number);
	Calculator calculator = new Calculator();
	assertEquals(calculator.getResult(), number);

The @Property annotation defines this test as a property-based test, while the @RunWith class-level annotation defines that these tests are to be run using JUnit-Quickcheck. Note that you can mix example-based and property-based tests in the same test class. As long as you run your test class using JUnit, all public void no-parameter methods annotated with @Test will be run just as plain JUnit would do, while all tests annotated with @Property will be run as property-based tests.

The trials = 5 attribute tells JUnit-Quickcheck to generate 5 random parameter values (also known as samples). Default is 100. The System.out.println call is used to write the generated parameter value to the console, purely for demonstrational purposes:

Output of basic JUnit-Quickcheck property

As you can see, JUnit-Quickcheck randomly generated integer values and performed the check using each of these values. The property passes, telling us that our add() method seems to work quite well, even with quite large or negative integers. This is information you wouldn’t get when using purely example-based tests. Sweet!

Constraining property values
Purely random integers seem to work well for our simple add() method, but obviously there are cases where you want to define some sort of constraints on the values generated by your property-based testing tool. JUnit-Quickcheck provides a number of options to do so:

1. Using the JUnit Assume class
Using Assume, you can define assumptions on the values generated by JUnit-Quickcheck. For example, if you only want to test your add() method using positive integers, you could do this:

@Property(trials = 5)
public void testAdditionUsingAssume(int number) {
	assumeThat(number, greaterThan(0));
	System.out.println("Generated number for testAdditionUsingAssume: " + number);
	Calculator calculator = new Calculator();
	assertEquals(calculator.getResult(), number);

When you run these tests, you can see that values generated by JUnit-Quickcheck that do not satisfy the assumption (in this case, three of them) are simply discarded:

Output of JUnit-Quickcheck using Assume

2. Using the @InRange annotation With this annotation, you can actually constrain the values that are generated by JUnit-Quickcheck:

@Property(trials = 5)
public void testAdditionUsingInRange(@InRange(minInt = 0) int number) {
	System.out.println("Generated number for testAdditionUsingInRange: " + number);
	Calculator calculator = new Calculator();
	assertEquals(calculator.getResult(), number);

Contrary to the approach that uses the Assume class, where values generated by JUnit-Quickcheck are filtered post-generation, when you’re using the @InRange approach you will always end up with the required number of samples:

Output of JUnit-Quickcheck using InRange

3. Using constraint expressions
Here, just like when you’re using the Assume approach, values generated by JUnit-Quickcheck are filtered after generation by using a satisfies predicate:

@Property(trials = 5)
public void testAdditionUsingSatisfies(@When(satisfies = "#_ >= 0") int number) {
	System.out.println("Generated number for testAdditionUsingSatisfies: " + number);
	Calculator calculator = new Calculator();
	assertEquals(calculator.getResult(), number);

The difference is that when the discard ratio (the percentage of generated values that do not satisfy the constraints defined) exceeds a certain threshold (0.5 by default), the property fails:

Output of JUnit-Quickcheck using the satisfies predicate

Error generated by JUnit-Quickcheck when discard threshold is not met

Depending on your preferences and project requirements, you can select any of these strategies for constraining your property values.

Additional JUnit-Quickcheck features
JUnit-Quickcheck comes with some other useful features as well:

  • Fixing the seed used to generate the random property values. You can use this to have JUnit-Quickcheck generate the same values for each and every test run. You may want to use this feature when a property fails, so that you can test the property over and over again with the same set of generated values that caused the failure in the first place.
  • When a property fails for a given set of values, JUnit-Quickcheck will attempt to find smaller sets of values that also fail the property, a technique called shrinking. See the JUnit-Quickcheck documentation for an example.

Download an example project
You can download a Maven project containing the Calculator class and all JUnit-Quickcheck tests that have been demonstrated in this post here. Happy property-based testing!

8 thoughts on “An introduction to property-based testing with JUnit-Quickcheck

  1. Pingback: Java Testing Weekly 10 / 2016

  2. So Quickcheck will generate input values, but what about the asserted output values? How would you generate those without duplicating the production code in your unit test? Which is basically what your calculator example is doing.

    Or: do you have a more complicated examples that demonstrates that this really works?

    • Hi Frans,

      I don’t have any other examples lying around as I haven’t applied PBT in any other projects so far. Looking back on this post I must say you’re absolutely right though, this calculator is a real bad example of how PBT works. It works much better when you’ve got a range of input values (equivalence classes) that all lead to the same output value (for example a boolean result). In that case, you can apply PBT to use a range of input values between the boundaries of a specific equivalence class and see whether the expected output is produced. With a calculator, every combination of input values leads to its own specific output value, which as you said requires you to sort of recreate the application logic in your tests, which is a VERY bad thing to do..

      Thanks for pointing this out!

  3. Pingback: Beautiful Property-Based Testing (Falling in Love with Testing)

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