scalacheck

package scalacheck

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trait Checkers extends ScalaCheckConfiguration

Trait that contains several “check” methods that perform ScalaCheck property checks.

Trait that contains several “check” methods that perform ScalaCheck property checks. If ScalaCheck finds a test case for which a property doesn't hold, the problem will be reported as a ScalaTest test failure.

To use ScalaCheck, you specify properties and, in some cases, generators that generate test data. You need not always create generators, because ScalaCheck provides many default generators for you that can be used in many situations. ScalaCheck will use the generators to generate test data and with that data run tests that check that the property holds. Property-based tests can, therefore, give you a lot more testing for a lot less code than assertion-based tests. Here's an example of using ScalaCheck from a JUnitSuite:

import org.scalatest.junit.JUnitSuite
import org.scalatest.prop.Checkers
import org.scalacheck.Arbitrary._
import org.scalacheck.Prop._

class MySuite extends JUnitSuite with Checkers {
  @Test
  def testConcat() {
    check((a: List[Int], b: List[Int]) => a.size + b.size == (a ::: b).size)
  }
}

The check method, defined in Checkers, makes it easy to write property-based tests inside ScalaTest, JUnit, and TestNG test suites. This example specifies a property that List's ::: method should obey. ScalaCheck properties are expressed as function values that take the required test data as parameters. ScalaCheck will generate test data using generators and repeatedly pass generated data to the function. In this case, the test data is composed of integer lists named a and b. Inside the body of the function, you see:

a.size + b.size == (a ::: b).size

The property in this case is a Boolean expression that will yield true if the size of the concatenated list is equal to the size of each individual list added together. With this small amount of code, ScalaCheck will generate possibly hundreds of value pairs for a and b and test each pair, looking for a pair of integers for which the property doesn't hold. If the property holds true for every value ScalaCheck tries, check returns normally. Otherwise, check will complete abruptly with a TestFailedException that contains information about the failure, including the values that cause the property to be false.

For more information on using ScalaCheck properties, see the documentation for ScalaCheck, which is available from http://code.google.com/p/scalacheck/.

To execute a suite that mixes in Checkers with ScalaTest's Runner, you must include ScalaCheck's jar file on the class path or runpath.

Property check configuration

The property checks performed by the check methods of this trait can be flexibly configured via the services provided by supertrait Configuration. The five configuration parameters for property checks along with their default values and meanings are described in the following table:

Configuration Parameter	Default Value	Meaning
minSuccessful	100	the minimum number of successful property evaluations required for the property to pass
maxDiscarded	500	the maximum number of discarded property evaluations allowed during a property check
minSize	0	the minimum size parameter to provide to ScalaCheck, which it will use when generating objects for which size matters (such as strings or lists)
maxSize	100	the maximum size parameter to provide to ScalaCheck, which it will use when generating objects for which size matters (such as strings or lists)
workers	1	specifies the number of worker threads to use during property evaluation

The check methods of trait Checkers each take a PropertyCheckConfiguration object as an implicit parameter. This object provides values for each of the five configuration parameters. Trait Configuration provides an implicit val named generatorDrivenConfig with each configuration parameter set to its default value. If you want to set one or more configuration parameters to a different value for all property checks in a suite you can override this val (or hide it, for example, if you are importing the members of the Checkers companion object rather than mixing in the trait.) For example, if you want all parameters at their defaults except for minSize and maxSize, you can override generatorDrivenConfig, like this:

implicit override val generatorDrivenConfig =
  PropertyCheckConfiguration(minSize = 10, sizeRange = 10)

Or, if hide it by declaring a variable of the same name in whatever scope you want the changed values to be in effect:

implicit val generatorDrivenConfig =
  PropertyCheckConfiguration(minSize = 10, sizeRange = 10)

In addition to taking a PropertyCheckConfiguration object as an implicit parameter, the check methods of trait Checkers also take a variable length argument list of PropertyCheckConfigParam objects that you can use to override the values provided by the implicit PropertyCheckConfiguration for a single check invocation. You place these configuration settings after the property or property function, For example, if you want to set minSuccessful to 500 for just one particular check invocation, you can do so like this:

check((n: Int) => n + 0 == n, minSuccessful(500))

This invocation of check will use 500 for minSuccessful and whatever values are specified by the implicitly passed PropertyCheckConfiguration object for the other configuration parameters. If you want to set multiple configuration parameters in this way, just list them separated by commas:

check((n: Int) => n + 0 == n, minSuccessful(500), maxDiscardedFactor(0.6))

The previous configuration approach works the same in Checkers as it does in GeneratorDrivenPropertyChecks. Trait Checkers also provides one check method that takes an org.scalacheck.Test.Parameters object, in case you want to configure ScalaCheck that way.

import org.scalacheck.Prop
import org.scalacheck.Test.Parameters
import org.scalatest.prop.Checkers._

check(Prop.forAll((n: Int) => n + 0 == n), Parameters.Default { override val minSuccessfulTests = 5 })

For more information, see the documentation for supertrait Configuration.

trait ScalaCheckDrivenPropertyChecks extends Whenever with ScalaCheckConfiguration

Trait containing methods that faciliate property checks against generated data using ScalaCheck.

This trait contains forAll methods that provide various ways to check properties using generated data. Use of this trait requires that ScalaCheck be on the class path when you compile and run your tests. It also contains a wherever method that can be used to indicate a property need only hold whenever some condition is true.

For an example of trait ScalaCheckDrivenPropertyChecks in action, imagine you want to test this Fraction class:

class Fraction(n: Int, d: Int) {

  require(d != 0)
  require(d != Integer.MIN_VALUE)
  require(n != Integer.MIN_VALUE)

  val numer = if (d < 0) -1 * n else n
  val denom = d.abs

  override def toString = numer + " / " + denom
}

To test the behavior of Fraction, you could mix in or import the members of ScalaCheckDrivenPropertyChecks (and Matchers) and check a property using a forAll method, like this:

forAll { (n: Int, d: Int) =>

  whenever (d != 0 && d != Integer.MIN_VALUE
      && n != Integer.MIN_VALUE) {

    val f = new Fraction(n, d)

    if (n < 0 && d < 0 || n > 0 && d > 0)
      f.numer should be > 0
    else if (n != 0)
      f.numer should be < 0
    else
      f.numer should be === 0

    f.denom should be > 0
  }
}

Trait ScalaCheckDrivenPropertyChecks provides overloaded forAll methods that allow you to check properties using the data provided by a ScalaCheck generator. The simplest form of forAll method takes two parameter lists, the second of which is implicit. The first parameter list is a "property" function with one to six parameters. An implicit Arbitrary generator and Shrink object needs to be supplied for The forAll method will pass each row of data to each parameter type. ScalaCheck provides many implicit Arbitrary generators for common types such as Int, String, List[Float], etc., in its org.scalacheck.Arbitrary companion object. So long as you use types for which ScalaCheck already provides implicit Arbitrary generators, you needn't worry about them. Same for Shrink objects, which are provided by ScalaCheck's org.scalacheck.Shrink companion object. Most often you can simply pass a property function to forAll, and the compiler will grab the implicit values provided by ScalaCheck.

The forAll methods use the supplied Arbitrary generators to generate example arguments and pass them to the property function, and generate a GeneratorDrivenPropertyCheckFailedException if the function completes abruptly for any exception that would normally cause a test to fail in ScalaTest other than DiscardedEvaluationException. An DiscardedEvaluationException, which is thrown by the whenever method (defined in trait Whenever, which this trait extends) to indicate a condition required by the property function is not met by a row of passed data, will simply cause forAll to discard that row of data.

Supplying argument names

You can optionally specify string names for the arguments passed to a property function, which will be used in any error message when describing the argument values that caused the failure. To supply the names, place them in a comma separated list in parentheses after forAll before the property function (a curried form of forAll). Here's an example:

forAll ("a", "b") { (a: String, b: String) =>
  a.length + b.length should equal ((a + b).length + 1) // Should fail
}

When this fails, you'll see an error message that includes this:

Occurred when passed generated values (
  a = "",
  b = ""
)

When you don't supply argument names, the error message will say arg0, arg1, etc.. For example, this property check:

forAll { (a: String, b: String) =>
  a.length + b.length should equal ((a + b).length + 1) // Should fail
}

Will fail with an error message that includes:

Occurred when passed generated values (
  arg0 = "",
  arg1 = ""
)

Supplying generators

ScalaCheck provides a nice library of compositors that makes it easy to create your own custom generators. If you want to supply custom generators to a property check, place them in parentheses after forAll, before the property check function (a curried form of forAll).

For example, to create a generator of even integers between (and including) -2000 and 2000, you could write this:

import org.scalacheck.Gen

val evenInts = for (n <- Gen.choose(-1000, 1000)) yield 2 * n

Given this generator, you could use it on a property check like this:

forAll (evenInts) { (n) => n % 2 should equal (0) }

Custom generators are necessary when you want to pass data types not supported by ScalaCheck's arbitrary generators, but are also useful when some of the values in the full range for the passed types are not valid. For such values you would use a whenever clause. In the Fraction class shown above, neither the passed numerator or denominator can be Integer.MIN_VALUE, and the passed denominator cannot be zero. This shows up in the whenever clause like this:

whenever (d != 0 && d != Integer.MIN_VALUE
    && n != Integer.MIN_VALUE) { ...

You could in addition define generators for the numerator and denominator that only produce valid values, like this:

val validNumers =
  for (n <- Gen.choose(Integer.MIN_VALUE + 1, Integer.MAX_VALUE)) yield n
val validDenoms =
  for (d <- validNumers if d != 0) yield d

You could then use them in the property check like this:

forAll (validNumers, validDenoms) { (n: Int, d: Int) =>

  whenever (d != 0 && d != Integer.MIN_VALUE
      && n != Integer.MIN_VALUE) {

    val f = new Fraction(n, d)

    if (n < 0 && d < 0 || n > 0 && d > 0)
      f.numer should be > 0
    else if (n != 0)
      f.numer should be < 0
    else
      f.numer should be === 0

    f.denom should be > 0
  }
}

Note that even if you use generators that don't produce the invalid values, you still need the whenever clause. The reason is that once a property fails, ScalaCheck will try and shrink the values to the smallest values that still cause the property to fail. During this shrinking process ScalaCheck may pass invalid values. The whenever clause is still needed to guard against those values. (The whenever clause also clarifies to readers of the code exactly what the property is in a succinct way, without requiring that they find and understand the generator definitions.)

Supplying both generators and argument names

If you want to supply both generators and named arguments, you can do so by providing a list of (<generator>, <name>) pairs in parentheses after forAll, before the property function. Here's an example:

forAll ((validNumers, "n"), (validDenoms, "d")) { (n: Int, d: Int) =>

  whenever (d != 0 && d != Integer.MIN_VALUE
      && n != Integer.MIN_VALUE) {

    val f = new Fraction(n, d)

    if (n < 0 && d < 0 || n > 0 && d > 0)
      f.numer should be > 0
    else if (n != 0)
      f.numer should be < 0
    else
      f.numer should be === 0

    f.denom should be > 0
  }
}

Were this property check to fail, it would mention the names n and d in the error message, like this:

Occurred when passed generated values (
  n = 17,
  d = 21
)

Property check configuration

The property checks performed by the forAll methods of this trait can be flexibly configured via the services provided by supertrait Configuration. The five configuration parameters for property checks along with their default values and meanings are described in the following table:

Configuration Parameter	Default Value	Meaning
minSuccessful	100	the minimum number of successful property evaluations required for the property to pass
maxDiscarded	500	the maximum number of discarded property evaluations allowed during a property check
minSize	0	the minimum size parameter to provide to ScalaCheck, which it will use when generating objects for which size matters (such as strings or lists)
maxSize	100	the maximum size parameter to provide to ScalaCheck, which it will use when generating objects for which size matters (such as strings or lists)
workers	1	specifies the number of worker threads to use during property evaluation

The forAll methods of trait ScalaCheckDrivenPropertyChecks each take a PropertyCheckConfiguration object as an implicit parameter. This object provides values for each of the five configuration parameters. Trait Configuration provides an implicit val named generatorDrivenConfig with each configuration parameter set to its default value. If you want to set one or more configuration parameters to a different value for all property checks in a suite you can override this val (or hide it, for example, if you are importing the members of the ScalaCheckDrivenPropertyChecks companion object rather than mixing in the trait.) For example, if you want all parameters at their defaults except for minSize and maxSize, you can override generatorDrivenConfig, like this:

implicit override val generatorDrivenConfig =
  PropertyCheckConfiguration(minSize = 10, sizeRange = 10)

Or, hide it by declaring a variable of the same name in whatever scope you want the changed values to be in effect:

implicit val generatorDrivenConfig =
  PropertyCheckConfiguration(minSize = 10, sizeRange = 10)

In addition to taking a PropertyCheckConfiguration object as an implicit parameter, the forAll methods of trait ScalaCheckDrivenPropertyChecks also take a variable length argument list of PropertyCheckConfigParam objects that you can use to override the values provided by the implicit PropertyCheckConfiguration for a single forAll invocation. For example, if you want to set minSuccessful to 500 for just one particular forAll invocation, you can do so like this:

forAll (minSuccessful(500)) { (n: Int, d: Int) => ...

This invocation of forAll will use 500 for minSuccessful and whatever values are specified by the implicitly passed PropertyCheckConfiguration object for the other configuration parameters. If you want to set multiple configuration parameters in this way, just list them separated by commas:

forAll (minSuccessful(500), maxDiscardedFactor(0.6)) { (n: Int, d: Int) => ...

If you are using an overloaded form of forAll that already takes an initial parameter list, just add the configuration parameters after the list of generators, names, or generator/name pairs, as in:

// If providing argument names
forAll ("n", "d", minSuccessful(500), maxDiscarded(300)) {
  (n: Int, d: Int) => ...

// If providing generators
forAll (validNumers, validDenoms, minSuccessful(500), maxDiscarded(300)) {
  (n: Int, d: Int) => ...

// If providing (<generators>, <name>) pairs
forAll ((validNumers, "n"), (validDenoms, "d"), minSuccessful(500), maxDiscarded(300)) {
  (n: Int, d: Int) => ...

For more information, see the documentation for supertrait Configuration.

trait ScalaCheckPropertyChecks extends TableDrivenPropertyChecks with ScalaCheckDrivenPropertyChecks
Trait that facilitates property checks on data supplied by tables and generators.
Trait that facilitates property checks on data supplied by tables and generators.
This trait extends both TableDrivenPropertyChecks and GeneratorDrivenPropertyChecks. Thus by mixing in this trait you can perform property checks on data supplied either by tables or generators. For the details of table- and generator-driven property checks, see the documentation for each by following the links above.
For a quick example of using both table and generator-driven property checks in the same suite of tests, however, imagine you want to test this Fraction class:
```
class Fraction(n: Int, d: Int) {

  require(d != 0)
  require(d != Integer.MIN_VALUE)
  require(n != Integer.MIN_VALUE)

  val numer = if (d < 0) -1 * n else n
  val denom = d.abs

  override def toString = numer + " / " + denom
}
```
If you mix in PropertyChecks, you could use a generator-driven property check to test that the passed values for numerator and denominator are properly normalized, like this:
```
forAll { (n: Int, d: Int) =>

  whenever (d != 0 && d != Integer.MIN_VALUE
      && n != Integer.MIN_VALUE) {

    val f = new Fraction(n, d)

    if (n < 0 && d < 0 || n > 0 && d > 0)
      f.numer should be > 0
    else if (n != 0)
      f.numer should be < 0
    else
      f.numer shouldEqual 0

    f.denom should be > 0
  }
}
```
And you could use a table-driven property check to test that all combinations of invalid values passed to the Fraction constructor produce the expected IllegalArgumentException, like this:
```
val invalidCombos =
  Table(
    ("n",               "d"),
    (Integer.MIN_VALUE, Integer.MIN_VALUE),
    (1,                 Integer.MIN_VALUE),
    (Integer.MIN_VALUE, 1),
    (Integer.MIN_VALUE, 0),
    (1,                 0)
  )

forAll (invalidCombos) { (n: Int, d: Int) =>
  an [IllegalArgumentException] should be thrownBy {
    new Fraction(n, d)
  }
}
```

Value Members

object Checkers extends Checkers
Companion object that facilitates the importing of Checkers members as an alternative to mixing it in.
Companion object that facilitates the importing of Checkers members as an alternative to mixing it in. One use case is to import Checkers members so you can use them in the Scala interpreter.
object ScalaCheckDrivenPropertyChecks extends ScalaCheckDrivenPropertyChecks
object ScalaCheckPropertyChecks extends ScalaCheckPropertyChecks
Companion object that facilitates the importing of PropertyChecks members as an alternative to mixing it in.
Companion object that facilitates the importing of PropertyChecks members as an alternative to mixing it in. One use case is to import PropertyChecks members so you can use them in the Scala interpreter.

Packages

scalacheck

package scalacheck

Type Members

Property check configuration

Supplying argument names

Supplying generators

Supplying both generators and argument names

Property check configuration

Value Members

Ungrouped

Packages

scalacheck 

package scalacheck

Type Members

Property check configuration

Supplying argument names

Supplying generators

Supplying both generators and argument names

Property check configuration

Value Members

Ungrouped

scalacheck