qcheck - v0.0.6

qcheck

QuickCheck-inspired property-based testing with integrated shrinking

Overview

Rather than specifying test cases manually, you describe the invariants that values of a given type must satisfy (“properties”). Then, generators generate lots of values (test cases) on which the properties are checked. Finally, if a value is found for which a given property does not hold, that value is “shrunk” in order to find an nice, informative counter-example that is presented to you.

This module has functions for running and configuring property tests as well as generating random values (with shrinking) to drive those tests.

For usage examples, see the project README.

Running tests

Configuring test runs

Generators

Here is a list of generator functions grouped by category.

Combinators

Ints

Floats

Characters

Strings

Lists

Dicts

Sets

Other

Trees

There are functions for dealing with the Tree type directly, but they are low-level and you should not need to use them much.

Seeding generators

Shrinking

There are some public functions for dealing with shrinks and shrinking. Similar to the Tree functions, you often won’t need to use these directly.

Notes

Types

Config

</>

Configuration for the property-based testing.

  • test_count: The number of tests to run for each property.
  • max_retries: The number of times to retry the tested property while shrinking.
  • random_seed: The seed for the random generator.
pub type Config {
  Config(test_count: Int, max_retries: Int, random_seed: Seed)
}

Constructors 

  • Config(test_count: Int, max_retries: Int, random_seed: Seed)

Generator

</>

Generator(a) is a random generator for values of type a.

Note: Because it exposes the prng Seed type, it is likely that this type will become opaque in the future.

pub type Generator(a) {
  Generator(fn(Seed) -> #(Tree(a), Seed))
}

Constructors 

  • Generator(fn(Seed) -> #(Tree(a), Seed))

Seed

opaque </>

An opaque type representing a seed value used to initialize random generators.

pub opaque type Seed

TestError

opaque </> 
pub opaque type TestError(a)

TestErrorMessage

opaque </> 
pub opaque type TestErrorMessage

Tree

</> 
pub type Tree(a) {
  Tree(a, Iterator(Tree(a)))
}

Constructors 

  • Tree(a, Iterator(Tree(a)))

Try

</> 
pub type Try(a) {
  NoPanic(a)
  Panic(exception.Exception)
}

Constructors 

  • NoPanic(a)
  • Panic(exception.Exception)

Functions

apply

</> 
pub fn apply(
  f f: Generator(fn(a) -> b),
  generator x: Generator(a),
) -> Generator(b)

apply(f, x) applies a function generator, f, and an argument generator, x, into a result generator.

apply_tree

</> 
pub fn apply_tree(f: Tree(fn(a) -> b), x: Tree(a)) -> Tree(b)

bind

</> 
pub fn bind(
  generator generator: Generator(a),
  f f: fn(a) -> Generator(b),
) -> Generator(b)

bind(generator, f) generates a value of type a with generator, then passes that value to f, which uses it to generate values of type b.

bind_tree

</> 
pub fn bind_tree(tree: Tree(a), f: fn(a) -> Tree(b)) -> Tree(b)

bool

</> 
pub fn bool() -> Generator(Bool)

bool() generates booleans and shrinks towards False.

char

</> 
pub fn char() -> Generator(String)

char() generates characters with a bias towards printable ASCII characters, while still hitting some edge cases.

char_alpha

</> 
pub fn char_alpha() -> Generator(String)

char_alpha() generates alphabetic (ASCII) characters.

char_alpha_numeric

</> 
pub fn char_alpha_numeric() -> Generator(String)

char_alpha_numeric() generates alphanumeric (ASCII) characters.

char_digit

</> 
pub fn char_digit() -> Generator(String)

char_digit() generates digits from 0 to 9, inclusive.

char_from_list

</> 
pub fn char_from_list(chars: List(String)) -> Generator(String)

char_from_list(chars) generates characters from the given list of characters.

char_lowercase

</> 
pub fn char_lowercase() -> Generator(String)

char_lowercase() generates lowercase (ASCII) letters.

char_print

</> 
pub fn char_print() -> Generator(String)

char_print() generates printable ASCII characters, with a bias towards alphanumeric characters.

char_print_uniform

</> 
pub fn char_print_uniform() -> Generator(String)

char_print_uniform() generates printable ASCII characters.

char_uniform

</> 
pub fn char_uniform() -> Generator(String)

char_uniform() generates characters uniformly distributed across the default range.

char_uniform_inclusive

</> 
pub fn char_uniform_inclusive(
  low low: Int,
  high high: Int,
) -> Generator(String)

char_uniform_inclusive(low, high) generates “characters” uniformly distributed between low and high, inclusive. Here, “characters” are strings of a single codepoint.

Note: this function is slightly weird in that it takes the integer representation of the range of codepoints, not the strings themselves.
This behavior will likely change.

These char_* functions are mainly used for setting up the string generators.

Shrinks towards a when possible, but won’t go outside of the range.

char_uppercase

</> 
pub fn char_uppercase() -> Generator(String)

char_uppercase() generates uppercase (ASCII) letters.

char_whitespace

</> 
pub fn char_whitespace() -> Generator(String)

char_whitespace() generates whitespace (ASCII) characters.

default_config

</> 
pub fn default_config() -> Config

default() returns the default configuration for the property-based testing.

dict_generic

</> 
pub fn dict_generic(
  key_generator key_generator: Generator(a),
  value_generator value_generator: Generator(b),
  max_length max_length: Int,
) -> Generator(Dict(a, b))

dict_generic(key_generator, value_generator, max_len) generates dictionaries with keys from key_generator and values from value_generator with lengths up to max_len.

Shrinks on size then on elements.

failwith

</> 
pub fn failwith(
  original_value original_value: a,
  shrunk_value shrunk_value: a,
  shrink_steps shrink_steps: Int,
  error_msg error_msg: String,
) -> b

float

</> 
pub fn float() -> Generator(Float)

float() generates floats with a bias towards smaller values and shrinks towards 0.0.

float_uniform_inclusive

</> 
pub fn float_uniform_inclusive(
  low: Float,
  high: Float,
) -> Generator(Float)

from_float_weighted_generators

</> 
pub fn from_float_weighted_generators(
  generators: List(#(Float, Generator(a))),
) -> Generator(a)

from_float_weighted_generators(generators) chooses a generator from a list of generators weighted by the given float weights, then chooses a value from that generator.

You should generally prefer from_weighted_generators as it is much faster.

from_generators

</> 
pub fn from_generators(
  generators: List(Generator(a)),
) -> Generator(a)

from_generators(generators) chooses a generator from a list of generators weighted uniformly, then chooses a value from that generator.

from_weighted_generators

</> 
pub fn from_weighted_generators(
  generators: List(#(Int, Generator(a))),
) -> Generator(a)

from_float_generators(generators) chooses a generator from a list of generators weighted by the given integer weights, then chooses a value from that generator.

You should generally prefer this function over from_float_weighted_generators as this function is faster.

generate_tree

</> 
pub fn generate_tree(
  generator: Generator(a),
  seed: Seed,
) -> #(Tree(a), Seed)

generate(gen, seed) generates a value of type a and its shrinks using the generator gen.

You should not use this function directly. It is for internal use only.

given

</> 
pub fn given(
  generator generator: Generator(a),
  property property: fn(a) -> Bool,
) -> Nil

A specialized version of run that uses the default configuration.

given_result

</> 
pub fn given_result(
  generator generator: Generator(a),
  property property: fn(a) -> Result(b, c),
) -> Nil

A specialized version of run_result that uses the default configuration.

int_uniform

</> 
pub fn int_uniform() -> Generator(Int)

int_uniform() generates uniformly distributed integers across a large range and shrinks towards 0.

Note: this generator does not hit interesting or corner cases very often.

int_uniform_inclusive

</> 
pub fn int_uniform_inclusive(
  low low: Int,
  high high: Int,
) -> Generator(Int)

int_uniform_inclusive(low, high) generates integers uniformly distributed between low and high, inclusive.

Shrinks towards 0, but won’t shrink outside of the range [low, high].

list_generic

</> 
pub fn list_generic(
  element_generator: Generator(a),
  min_length min_len: Int,
  max_length max_len: Int,
) -> Generator(List(a))

list_generic(element_generator, min_len, max_len) generates lists of elements from element_generator with lengths between min_len and max_len, inclusive.

Shrinks first on the number of elements, then on the elements themselves.

make_primitive_tree

</> 
pub fn make_primitive_tree(
  root x: a,
  shrink shrink: fn(a) -> Iterator(a),
) -> Tree(a)

map

</> 
pub fn map(
  generator generator: Generator(a),
  f f: fn(a) -> b,
) -> Generator(b)

map(generator, f) transforms the generator generator by applying f to each generated value. Shrinks as generator shrinks, but with f applied.

map2

</> 
pub fn map2(
  f f: fn(a, b) -> c,
  g1 g1: Generator(a),
  g2 g2: Generator(b),
) -> Generator(c)

map2(f, g1, g2) transforms two generators, g1 and g2, by applying f to each pair of generated values.

map2_tree

</> 
pub fn map2_tree(
  f: fn(a, b) -> c,
  a: Tree(a),
  b: Tree(b),
) -> Tree(c)

map3

</> 
pub fn map3(
  f f: fn(a, b, c) -> d,
  g1 g1: Generator(a),
  g2 g2: Generator(b),
  g3 g3: Generator(c),
) -> Generator(d)

map3(f, g1, g2, g3) transforms three generators, g1, g2, and g3, by applying f to each triple of generated values.

map_tree

</> 
pub fn map_tree(tree: Tree(a), f: fn(a) -> b) -> Tree(b)

new_test_error

</> 
pub fn new_test_error(
  original_value orig: a,
  shrunk_value shrunk: a,
  shrink_steps steps: Int,
  error_msg error_msg: String,
) -> TestError(a)

nil

</> 
pub fn nil() -> Generator(Nil)

nil() is the Nil generator. It always returns Nil and does not shrink.

option

</> 
pub fn option(generator: Generator(a)) -> Generator(Option(a))

option(gen) is an Option generator that uses gen to generate Some values. Shrinks towards None then towards shrinks of gen.

option_tree

</> 
pub fn option_tree(tree: Tree(a)) -> Tree(Option(a))

parameter

</> 
pub fn parameter(f: fn(a) -> b) -> fn(a) -> b

parameter(f) is used in constructing curried functions for the applicative style of building generators.

Example

import qcheck

type Box {
  Box(x: Int, y: Int, w: Int, h: Int)
}

fn box_generator() {
  qcheck.return({
    use x <- qcheck.parameter
    use y <- qcheck.parameter
    use w <- qcheck.parameter
    use h <- qcheck.parameter
    Box(x:, y:, w:, h:)
  })
  |> qcheck.apply(qcheck.int_uniform_inclusive(-100, 100))
  |> qcheck.apply(qcheck.int_uniform_inclusive(-100, 100))
  |> qcheck.apply(qcheck.int_uniform_inclusive(1, 100))
  |> qcheck.apply(qcheck.int_uniform_inclusive(1, 100))
}

pub fn parameter_example__test() {
  use _box <- qcheck.given(box_generator())

  // Test some interesting property of boxes here.

  // (This `True` is a standin for your property.)
  True
}

rescue

</> 
pub fn rescue(thunk: fn() -> a) -> Result(a, TestErrorMessage)

This function should only be called to rescue a function that my call failwith at some point to raise an exception. It will likely raise otherwise.

rescue_error

</> 
pub fn rescue_error(f: fn() -> a) -> Result(a, String)

return

</> 
pub fn return(a: a) -> Generator(a)

return(a) creates a generator that always returns a and does not shrink.

return_tree

</> 
pub fn return_tree(x: a) -> Tree(a)

run

</> 
pub fn run(
  config config: Config,
  generator generator: Generator(a),
  property property: fn(a) -> Bool,
) -> Nil

run(config, generator, property) runs the property function against some test cases generated by the generator function according to the specified config

The run function returns Nil if the property holds (i.e., return True for all test cases), or panics if the property does not hold for some test case a (i.e., returns False or panics).

run_result

</> 
pub fn run_result(
  config config: Config,
  generator generator: Generator(a),
  property property: fn(a) -> Result(b, c),
) -> Nil

run_result(config, generator, property) is like run but the property function returns a Result instead of a Bool.

seed_new

</> 
pub fn seed_new(n: Int) -> Seed

seed_new(n) creates a new seed from the given integer, n`.

Example

Use a specific seed for the Config.

let config = 
  qcheck.default_config() 
  |> qcheck.with_random_seed(qcheck.seed_new(124))

seed_random

</> 
pub fn seed_random() -> Seed

seed_random() creates a new randomly-generated seed. You can use it when you don’t care about having specifically reproducible results.

Example

Use a random seed for the Config.

let config = 
  qcheck.default_config() 
  |> qcheck.with_random_seed(qcheck.seed_random())

sequence_list

</> 
pub fn sequence_list(l: List(Tree(a))) -> Tree(List(a))

sequence_list(list_of_trees) sequsences a list of trees into a tree of lists.

set_generic

</> 
pub fn set_generic(
  element_generator: Generator(a),
  max_length max_len: Int,
) -> Generator(Set(a))

set_generic(element_generator, max_len) generates sets of elements from element_generator.

Shrinks first on the number of elements, then on the elements themselves.

shrink_atomic

</> 
pub fn shrink_atomic() -> fn(a) -> Iterator(a)

The atomic shrinker treats types as atomic, and never attempts to produce smaller values.

shrink_float_towards

</> 
pub fn shrink_float_towards(
  destination destination: Float,
) -> fn(Float) -> Iterator(Float)

shrink_float_towards_zero

</> 
pub fn shrink_float_towards_zero() -> fn(Float) ->
  Iterator(Float)

shrink_int_towards

</> 
pub fn shrink_int_towards(
  destination destination: Int,
) -> fn(Int) -> Iterator(Int)

shrink_int_towards_zero

</> 
pub fn shrink_int_towards_zero() -> fn(Int) -> Iterator(Int)

small_positive_or_zero_int

</> 
pub fn small_positive_or_zero_int() -> Generator(Int)

small_positive_or_zero_int() generates small integers well suited for modeling the sizes of sized elements like lists or strings.

Smaller numbers are more likely than larger numbers.

Shrinks towards 0.

small_strictly_positive_int

</> 
pub fn small_strictly_positive_int() -> Generator(Int)

small_strictly_positive_int() generates small integers strictly greater than 0.

string

</> 
pub fn string() -> Generator(String)

`string() generates strings with the default character generator and the default length generator.

string_from

</> 
pub fn string_from(
  char_generator: Generator(String),
) -> Generator(String)

string_from(char_generator) generates strings from the given character generator using the default length generator.

string_generic

</> 
pub fn string_generic(
  char_generator: Generator(String),
  length_generator: Generator(Int),
) -> Generator(String)

string_generic(char_generator, length_generator) generates strings with characters from char_generator and lengths from length_generator.

string_non_empty

</> 
pub fn string_non_empty() -> Generator(String)

string_non_empty() generates non-empty strings with the default character generator and the default length generator.

string_non_empty_from

</> 
pub fn string_non_empty_from(
  char_generator: Generator(String),
) -> Generator(String)

string_non_empty_from(char_generator) generates non-empty strings from the given character generator using the default length generator.

string_with_length

</> 
pub fn string_with_length(length: Int) -> Generator(String)

string_with_length(length) generates strings of the given length with the default character generator.

string_with_length_from

</> 
pub fn string_with_length_from(
  generator: Generator(String),
  length: Int,
) -> Generator(String)

string_with_length_from(gen, length) generates strings of the given length from the given generator.

test_error_message_original_value

</> 
pub fn test_error_message_original_value(
  msg: TestErrorMessage,
) -> String

test_error_message_shrink_steps

</> 
pub fn test_error_message_shrink_steps(
  msg: TestErrorMessage,
) -> String

test_error_message_shrunk_value

</> 
pub fn test_error_message_shrunk_value(
  msg: TestErrorMessage,
) -> String

tree_to_string

</> 
pub fn tree_to_string(
  tree: Tree(a),
  a_to_string: fn(a) -> String,
) -> String

tree_to_string(tree, element_to_string) converts a tree into an unspecified string representation.

  • element_to_string: a function that converts individual elements of the tree to strings.

tree_to_string_

</> 
pub fn tree_to_string_(
  tree: Tree(a),
  a_to_string: fn(a) -> String,
  max_depth max_depth: Int,
) -> String

Like tree_to_string but with a configurable max_depth.

try

</> 
pub fn try(f: fn() -> a) -> Try(a)

tuple2

</> 
pub fn tuple2(
  g1: Generator(a),
  g2: Generator(b),
) -> Generator(#(a, b))

tuple2(g1, g2) generates a tuple of two values, one each from generators g1 and g2.

tuple3

</> 
pub fn tuple3(
  g1: Generator(a),
  g2: Generator(b),
  g3: Generator(c),
) -> Generator(#(a, b, c))

tuple3(g1, g2, g3) generates a tuple of three values, one each from generators g1, g2, and g3.

tuple4

</> 
pub fn tuple4(
  g1: Generator(a),
  g2: Generator(b),
  g3: Generator(c),
  g4: Generator(d),
) -> Generator(#(a, b, c, d))

tuple4(g1, g2, g3, g4) generates a tuple of four values, one each from generators g1, g2, g3, and g4.

tuple5

</> 
pub fn tuple5(
  g1: Generator(a),
  g2: Generator(b),
  g3: Generator(c),
  g4: Generator(d),
  g5: Generator(e),
) -> Generator(#(a, b, c, d, e))

tuple5(g1, g2, g3, g4, g5) generates a tuple of five values, one each from generators g1, g2, g3, g4, and g5.

tuple6

</> 
pub fn tuple6(
  g1: Generator(a),
  g2: Generator(b),
  g3: Generator(c),
  g4: Generator(d),
  g5: Generator(e),
  g6: Generator(f),
) -> Generator(#(a, b, c, d, e, f))

tuple6(g1, g2, g3, g4, g5, g6) generates a tuple of six values, one each from generators g1, g2, g3, g4, g5, and g6.

with_max_retries

</> 
pub fn with_max_retries(
  config: Config,
  max_retries: Int,
) -> Config

with_max_retries() returns a new configuration with the given max retries.

with_random_seed

</> 
pub fn with_random_seed(
  config: Config,
  random_seed: Seed,
) -> Config

with_random_seed() returns a new configuration with the given random seed.

with_test_count

</> 
pub fn with_test_count(config: Config, test_count: Int) -> Config

with_test_count() returns a new configuration with the given test count.

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