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Version: 5.8

Generator Operations


If you want to use an Arb to just return a value (even outside of a property test), then you can call next on it.

val arbA: Arb<A> = ...
val a = // use Random.Default
val a2 = // pass in Random


If you have an arb and you want to create a new arb that provides a subset of values, you can call filter on the source arb. For example, one way of generating even numbers is to take the integer arb, and filter out odd values. Viz:

val evens = { it.value % 2 == 0 }
val odds = { it.value % 2 == 1 }


If you have an arb and you want to transform the value generated, you can use map.

val integerStrings: Arb<String> = { it.toString() }


If you have an arb whose emission or edge cases depends on the emission of the previous arbitraries, you can use flatMap.

val dependentArbs: Arb<String> = Arb.of("foo", "bar").flatMap { prefix -> { integer ->


Two generators can be merged together, so that the resulting elements are equally sampled from both generators.

val merged = arbA.merge(arbB)

So with the following example would have an equal chance to yield either "a" or "b" on each random sample:

val a = arbitrary { "a" }
val b = arbitrary { "b" }
val ab = a.merge(b)

println(ab.take(1000).groupingBy { it }.eachCount())
// {a=493, b=507}

For merging more than two arbitraries, Arb.choice or Arb.choose might be more appropriate. For instance we can use:

  • Arb.choice(arbA, arbB, arbC) for uniform sampling between arbA, arbB and arbC,
  • or Arb.choose(4 to arbA, 1 to arbB, 5 to arbC) for a more granular control of frequency of each arbitrary. In this example arbA, arbB, and arbC will be sampled 40%, 10%, and 50% of the time, respectively.


Bind is useful if you want to apply multiple arbitraries. We can take a look at how we might construct values for a data class using bind.

data class Person(val name: String, val age: Int)

val personArb: Arb<Person> = Arb.bind(
) { name, age -> Person(name, age) }