Generators are at the very heart of Quickcheck. They provide the test data the runner executes characteristics with.


A distribution is a function that returns values between -1.0 and 1.0. The concrete frequency of values is determined by the distribution function. All generators provided by Quickcheck use an implementation of Distribution to derive their respective values from.

From a technical point of view all generators could be run with the uniform distribution. Other distributions can be used to increase the likelihood of certain values. This is useful to increase the significance of generators.

The supported distributions are: uniform, inverted normal, positive normal and negative normal.

The diagram shows the different distribution functions supported by Quickcheck. It is an example output of an integer generator with values ranging from 0 to 10.

All values of the uniform distribution have the same probability to occur. The inverted normal distribution is a distribution function whose border values are the most likely. The function is defined based on the normal distribution. This function is inverted and cut. This is done to provide a pragmatic distribution function to test border cases where the lowest and highest values are of the most interest. For the positive normal distribution the values near 0.0 are the most probable and values near 1.0 respectively for the negative normal distribution.

Primitive generators

Primitive generator are the basic building blocks for custom generators. The static factory methods in the net.java.quickcheck.generator.PrimitiveGenerators class can be used to create primitive generators (Strings, Integer, Long, Double, Byte, Character, Date, Enum). Typically the factory provides methods to create a generator with minimum value, maximum value and distribution for each primitive type. Additionally there are convenience methods that use default values.

There are two special factory methods that do not denote a primitive type: fixed value and null. Fixed value generators will always return the given values. Null generator always returns null.

Combined Generators

Combined generators use other generators to build more complex generators. As with primitive generators there is the net.java.quickcheck.generator.CombinedGenerators class with static factory methods.

There are number of generators that create subtypes of java.util.Collection and arrays (List, Set, object Arrays, int arrays, byte array).

Two generators generate tuples: the pair and triple generators. (The Java generics somewhat discourages the creation of lager tuples).

The ensured values generator can be used to create a deterministic generator. This can be combined with a random generator that kicks in when the deterministic generator runs out of values.

The nullsAnd generator can be used to create a random mixture of null values and values returned by an other generator. (The generator has this funny name to form readable statements in test code. For example: nullsAnd(integers()).)

The unique values generator can be used to decorate another generator to ensure that a value is not created repeatedly. When the base generator returns a redundant value it will be retried. (At some point the unique generator will give up and throw an exception.)

The frequency generator can be used to combine multiple generators to one generator. Every added generator will have a weight and values are taken from of the generators according to their respective weight. The oneOf generator factory method is a convenience method to create a frequency generator from a set of generators with the same weight.

Building custom generators

Armed with this knowledge about primitive and combined generators you can now start to create your own custom generators.

The following example defines a generator for java.io.File objects.
class FileGenerator implements Generator<File> {

  Generator<File> roots = fixedValues(File.listRoots());
  Generator<List<String>> paths = nonEmptyLists(letterStrings());

  public File next() {
    File f = roots.next();

    for (String p : paths.next()) f = new File(f, p);
    return f;

An implementation of the Generator interface has to define the next method. This method returns the next generated value. It will be called by the Quickcheck runner when a test executes.

It uses the fixedValues generator to create the root node. The number of file system roots depends on the OS. Windows systems can have multiple roots whereas Unix systems have only one. The path of the file after the root is created from a list of strings. The nonEmptyList generator will create lists with at least one entry.

The next method implementation creates the file from a file representing the root node and adds to it the relative paths generated with the paths generator. The relative paths are repeatedly added in the for loop to create the absolute path of the resulting file.

It is always a good practice to keep the base generators as members and reuse these for multiple runs of the next method.