#MoonBit QuickCheck Package

MoonBit QuickCheck package provides property-based testing capabilities by generating random test inputs.

#Checking Properties

Use check for the common property shape (A) -> Bool raise?. The input type must implement Arbitrary, Shrink, and Debug.

///|
test "adding zero is an identity" {
  @quickcheck.check((x : Int) => x + 0 == x)
}

Returning true passes a case; returning false reports a logical counterexample. A raised error is reported separately as an exceptional counterexample. The first failure is greedily shrunk while preserving that distinction: a false result cannot shrink into an error, and an error cannot shrink into false.

Use the pure filter function for a precondition:

///|
test "division identity" {
  @quickcheck.check((x : Int) => x / x == 1, filter=x => x != 0)
}

Filtered cases do not count toward count. The driver gives up after ten discarded cases per requested test by default. During shrinking, a filtered candidate consumes one shrink attempt, its subtree is skipped, and shrinking continues with the next candidate.

The optional controls are deterministic:

///|
test "configured property run" {
  @quickcheck.check(
    (xs : Array[Int]) => xs.length() >= 0,
    count=200,
    max_size=50,
    max_shrinks=100,
    discard_ratio=10,
    seed=2026,
  )
}

count, max_size, max_shrinks, and discard_ratio are unsigned. A zero count performs no tests. discard_ratio defaults to ten discarded cases per requested test; zero gives up on the first discarded case. Generator size grows from zero to max_size; consecutive discards temporarily increase the requested size so filtering cannot leave the run stuck at size zero. Because Arbitrary receives an Int size, larger values saturate at Int::MAX_VALUE. max_shrinks counts every shrink candidate examined, including filtered candidates, so zero disables shrinking and even an infinite or cyclic shrink stream terminates at the limit. A failure report includes the final counterexample, error when applicable, size, and shrink counts.

If a test needs to inspect an expected failure, use report instead of catching the Failure raised by check:

///|
test "inspect a counterexample" {
  let report = @quickcheck.report(
    (_ : Int) => false,
    count=1,
    max_size=0,
    max_shrinks=0,
    seed=7,
  )
  debug_inspect(
    report,
    content=(
      #|Falsified(
      #|  counterexample=-1028290551,
      #|  tests=1,
      #|  size=0,
      #|  shrinks=0,
      #|  shrink_attempts=0,
      #|)
    ),
  )
}

report returns an abstract QuickCheckReport[A] whose Debug representation distinguishes Passed, GaveUp, Falsified, and Raised. Every error from the property is represented by Raised; the driver does not distinguish errors used by inspect or snapshot tests. Calling report itself does not raise and does not require the input type to implement Debug.

counterexample_context attaches a human-readable rendering of the shrunk counterexample to a failure — useful when the generated value's Debug form is not the most readable description of what failed (for example, a rendered document rather than its AST):

///|
test "context describes the shrunk counterexample" {
  let report = @quickcheck.report(
    (x : Int) => x < 3,
    counterexample_context=x => "rendered input <\{x}>",
    seed=7,
  )
  debug_inspect(
    report,
    content=(
      #|Falsified(
      #|  counterexample=3,
      #|  context="rendered input <3>",
      #|  tests=2,
      #|  size=1,
      #|  shrinks=30,
      #|  shrink_attempts=33,
      #|)
    ),
  )
}

Properties should be deterministic and should not mutate or consume their input. In particular, an Iter is single-use; generate an Array and create a fresh iterator inside the property when replayable sequence behavior matters.

#Observing Generated Data

Use the pure observe function to inspect the distribution of successful generated cases. label adds a string, collect adds a value's Debug representation, and classify counts a named condition:

///|
test "observe generated cases" {
  let report = @quickcheck.report(
    (_ : Unit) => true,
    observe=_ => {
      [@quickcheck.label("unit"), @quickcheck.classify(true, "generated")]
    },
    count=2,
  )
  debug_inspect(
    report,
    content=(
      #|Passed(
      #|  tests=2,
      #|  observations={ labels: { <List: ["unit"]>: 2 }, classes: { "generated": 2 } },
      #|)
    ),
  )
}

Labels produced by one case form one joint bucket; classes are counted independently. Only successful top-level cases run observe; filtered and failing cases, including shrink candidates, do not contribute observations.

After a successful run, check prints an aligned observation table when any observations were collected; otherwise it prints nothing. On failure, the aggregate from preceding successful cases is included in the failure message. Use report when the structured result should be handled without printing or raising.

#Basic Usage

Generate random values of any type that implements the Arbitrary trait:

///|
test "basic generation" {
  let b : Bool = @quickcheck.gen()
  inspect(b, content="true")
  let x : Int = @quickcheck.gen()
  inspect(
    x,
    content=(
      #|1118850684
    ),
  )

  // Generate with size parameter
  let sized : Array[Int] = @quickcheck.gen(size=5)
  inspect(sized.length() <= 5, content="true")
}

#Multiple Samples

Generate multiple test cases using the samples function:

///|
test "multiple samples" {
  let ints : Array[Int] = @quickcheck.samples(5)
  debug_inspect(
    ints,
    content=(
      #|[1118850684, -99999, 846697896, -134217729, 67108863]
    ),
  )
  let strings : Array[String] = @quickcheck.samples(12)
  debug_inspect(
    strings[5:10],
    content=(
      #|<ArrayView: ["(K񁁛!", "", "vx2\b", "", "𶏱Hp9\u{18}Rx"]>
    ),
  )
}

#Built-in Types

QuickCheck provides Arbitrary implementations for all basic MoonBit types:

///|
test "builtin types" {
  // Basic types
  let v : (Bool, Char, Byte) = @quickcheck.gen()
  debug_inspect(
    v,
    content=(
      #|(false, '~', 0x4d)
    ),
  )
  // Numeric types
  let v : (Int, Int64, UInt, UInt64, Float, Double, BigInt) = @quickcheck.gen()
  debug_inspect(
    v,
    content=(
      #|(
      #|  -99999,
      #|  5259998046134461054,
      #|  228947857,
      #|  8766027650639656979,
      #|  0.23986786603927612,
      #|  0.7917029935679342,
      #|  -2,
      #|)
    ),
  )
  // Collections
  let v : (String, Bytes, Iter[Int]) = @quickcheck.gen()
  let (s, b, iter) = v
  debug_inspect(
    (s, b, iter.to_array()),
    content=(
      #|("", <Bytes: []>, [])
    ),
  )
}

Integer generation for Int16, UInt16, Int, UInt, Int64, and UInt64 intentionally ignores the size hint. Its default distribution combines full-width random bit patterns, common small values, values next to powers of two and ten, and type extrema. This keeps the entire scalar domain reachable while regularly exercising overflow, bit-width, and formatting boundaries. Byte remains uniformly distributed across all 256 bit patterns so Bytes and other byte-oriented workloads retain broad payload coverage. BigInt uses a separate portfolio: 35% arbitrary bit patterns, 25% canonical small values, 25% neighbors of common powers of two, and 15% neighbors of common powers of ten. Its random branch grows with the size hint up to 32 64-bit chunks, while boundary branches regularly cover important widths regardless of size. Fixed-width integer shrinkers try a midpoint first, then progressively finer candidates approaching the original value, with zero as the final fallback. With the greedy shrink driver, large failures still converge without linearly walking the numeric range while avoiding a likely rejected zero at every level.

#Custom Types

Implement the Arbitrary and Shrink traits for custom types. Both traits are available from the quickcheck facade; no separate quickcheck/shrink import is needed:

///|
priv struct Point {
  x : Int
  y : Int
} derive(Debug)

///|
impl @quickcheck.Arbitrary for Point with fn arbitrary(size, r0) {
  let r1 = r0.split()
  let y = @quickcheck.Arbitrary::arbitrary(size, r1)
  { x: @quickcheck.Arbitrary::arbitrary(size, r0), y, }
}

///|
impl @quickcheck.Shrink for Point with fn shrink(self) {
  @quickcheck.Shrink::shrink((self.x, self.y)).map(pair => {
    x: pair.0,
    y: pair.1,
  })
}

///|
test "custom type generation" {
  let point : Point = @quickcheck.gen()
  debug_inspect(
    point,
    content=(
      #|{ x: -99999, y: 2 }
    ),
  )
  let points : Array[Point] = @quickcheck.samples(10)
  debug_inspect(
    points[6:],
    content=(
      #|<ArrayView:
      #|  [
      #|    { x: 46354256, y: 1201652877 },
      #|    { x: 1, y: 2147483646 },
      #|    { x: 108552206, y: -1 },
      #|    { x: -1073741824, y: 2147483647 },
      #|  ]>
    ),
  )
}

///|
test "custom type shrinking" {
  let point : Point = { x: 2, y: 1, }
  debug_inspect(
    @quickcheck.Shrink::shrink(point).collect(),
    content=(
      #|[{ x: 1, y: 1 }, { x: 0, y: 1 }, { x: 2, y: 0 }]
    ),
  )
}

The package is useful for writing property tests that verify code behavior across a wide range of randomly generated inputs.

#MoonBit QuickCheck Package

#Checking Properties

#Observing Generated Data

#Basic Usage

#Multiple Samples

#Built-in Types

#Custom Types

#RandomState

#Shrink

#Arbitrary

#Generator

#Generator::Generator

#Generator::array_with_size

#Generator::flat_map

#Generator::map

#Generator::resize

#Generator::run

#Generator::sample

#Generator::samples

#Generator::scale

#Generator::zip

#Generator::zip_with

#Generator::zip_with3

#Observation

#Observation::to_string

#QuickCheckReport

#char_range

#check

#classify

#collect

#elements

#frequency

#gen

#int_range

#label

#one_of

#pure

#report

#samples

#sized

#spawn

Source Files

RandomState

Shrink

Arbitrary

Generator

Generator::Generator

Generator::array_with_size

Generator::flat_map

Generator::map

Generator::resize

Generator::run

Generator::sample

Generator::samples

Generator::scale

Generator::zip

Generator::zip_with

Generator::zip_with3

Observation

Observation::to_string

QuickCheckReport

char_range

check

classify

collect

elements

frequency

gen

int_range

label

one_of

pure

report

samples

sized

spawn