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QCheckThe library takes inspiration from Haskell's QuickCheck library. The rough idea is that the programmer describes invariants that values of a certain type need to satisfy ("properties"), as functions from this type to bool. She also needs to describe how to generate random values of the type, so that the property is tried and checked on a number of random instances.
This explains the organization of this module:
'aarbitrary is used to describe how to generate random values, shrink them (make counter-examples as small as possible), print them, etc. Auxiliary modules such as Gen, Print, and Shrink can be used along with make to build one's own arbitrary instances.Test is used to describe a single test, that is, a property of type 'a -> bool combined with an 'a arbitrary that is used to generate the test cases for this property. Optional parameters allow to specify the random generator state, number of instances to generate and test, etc.Examples:
let test =
QCheck.(Test.make ~count:1000
(list int) (fun l -> List.rev (List.rev l) = l));;
QCheck.Test.check_exn test;;let test = QCheck.(
Test.make
~count:10_000 ~max_fail:3
(list small_nat)
(fun l -> l = List.sort compare l));;
QCheck.Test.check_exn test;;Gen.fix :type tree = Leaf of int | Node of tree * tree
let leaf x = Leaf x
let node x y = Node (x,y)
let g = QCheck.Gen.(sized @@ fix
(fun self n -> match n with
| 0 -> map leaf nat
| n ->
frequency
[1, map leaf nat;
2, map2 node (self (n/2)) (self (n/2))]
))
Gen.generate ~n:20 g;;More complex and powerful combinators can be found in Gabriel Scherer's Generator module. Its documentation can be found here.
b1 ==> b2 is the logical implication b1 => b2 ie not b1 || b2 (except that it is strict and will interact better with Test.check_exn and the likes, because they will know the precondition was not satisfied.).
WARNING: this function should only be used in a property (see Test.make), because it raises a special exception in case of failure of the first argument, to distinguish between failed test and failed precondition. Because of OCaml's evaluation order, both b1 and b2 are always evaluated; if b2 should only be evaluated when b1 holds, see assume.
assume cond checks the precondition cond, and does nothing if cond=true. If cond=false, it interrupts the current test.
WARNING This function, like (==>), should only be used in a test, not outside. Example:
Test.make (list int) (fun l ->
assume (l <> []);
List.hd l :: List.tl l = l)assume_fail () is like assume false, but can take any type since we know it always fails (like assert false). This is useful to ignore some branches in if or match.
Example:
Test.make (list int) (function
| [] -> assume_fail ()
| _::_ as l -> List.hd l :: List.tl l = l)module Gen : sig ... endmodule Print : sig ... endmodule Iter : sig ... endmodule Shrink : sig ... endObservables are usable as arguments for random functions. The random function will observe its arguments in a way that is determined from the observable instance.
Inspired from https://blogs.janestreet.com/quickcheck-for-core/ and Koen Claessen's "Shrinking and Showing functions".
module Observable : sig ... endA value of type 'a arbitrary glues together a random generator, and optional functions for shrinking, printing, computing the size, etc. It is the "normal" way of describing how to generate values of a given type, to be then used in tests (see Test).
A statistic on a distribution of values of type 'a. The function MUST return a positive integer.
type 'a arbitrary = {gen : 'a Gen.t;print : ('a -> string) option;print values
*)small : ('a -> int) option;size of example
*)shrink : 'a Shrink.t option;shrink to smaller examples
*)collect : ('a -> string) option;map value to tag, and group by tag
*)stats : 'a stat list;statistics to collect and print
*)}A value of type 'a arbitrary is an object with a method for generating random values of type 'a, and additional methods to compute the size of values, print them, and possibly shrink them into smaller counter-examples.
NOTE the collect field is unstable and might be removed, or moved into Test.
val make :
?print:'a Print.t ->
?small:('a -> int) ->
?shrink:'a Shrink.t ->
?collect:('a -> string) ->
?stats:'a stat list ->
'a Gen.t ->
'a arbitraryBuilder for arbitrary. Default is to only have a generator, but other arguments can be added.
A test is a universal property of type foo -> bool for some type foo, with an object of type foo arbitrary used to generate, print, etc. values of type foo.
See Test.make to build a test, and Test.check_exn to run one test simply. For more serious testing, it is better to create a testsuite and use QCheck_runner.
module TestResult : sig ... endResult of running a test
module Test : sig ... endThe infrastructure used to find counter-examples to properties can also be used to find data satisfying a predicate, within a property being tested.
See https://github.com/c-cube/qcheck/issues/31
find_example ~f gen uses gen to generate some values of type 'a, and checks them against f. If such a value is found, it is returned. Otherwise an exception is raised. NOTE this should only be used from within a property in Test.make.
val find_example_gen :
?rand:Random.State.t ->
?name:string ->
?count:int ->
f:('a -> bool) ->
'a Gen.t ->
'aToplevel version of find_example. find_example_gen ~f arb ~n is roughly the same as Gen.generate1 (find_example ~f arb |> gen).
arbitraryChoose among the given list of generators. The list must not be empty; if it is Invalid_argument is raised.
val unit : unit arbitraryAlways generates (), obviously.
val bool : bool arbitraryUniform boolean generator.
val float : float arbitraryGenerates regular floats (no nan and no infinities).
val pos_float : float arbitraryPositive float generator (no nan and no infinities).
val neg_float : float arbitraryNegative float generator (no nan and no infinities).
val int : int arbitraryInt generator. Uniformly distributed.
val int_bound : int -> int arbitraryint_bound n is uniform between 0 and n included.
val int_range : int -> int -> int arbitraryint_range a b is uniform between a and b included. b must be larger than a.
val small_nat : int arbitrarySmall unsigned integers.
val small_int : int arbitrarySmall unsigned integers. See Gen.small_int.
val small_signed_int : int arbitrarySmall signed integers.
val int32 : int32 arbitraryInt32 generator. Uniformly distributed.
val int64 : int64 arbitraryInt64 generator. Uniformly distributed.
val pos_int : int arbitraryPositive int generator. Uniformly distributed.
val small_int_corners : unit -> int arbitraryAs small_int, but each newly created generator starts with a list of corner cases before falling back on random generation.
val neg_int : int arbitraryNegative int generator. The distribution is similar to that of small_int, not of pos_int.
val char : char arbitraryUniformly distributed on all the chars (not just ascii or valid latin-1).
val printable_char : char arbitraryUniformly distributed over a subset of chars.
val numeral_char : char arbitraryUniformly distributed over '0'..'9'.
Generates strings with a distribution of length of small_nat.
val string : string arbitraryGenerates strings with a distribution of length of small_nat and distribution of characters of char.
Generates strings with distribution of characters if char.
val printable_string : string arbitraryGenerates strings with a distribution of length of small_nat and distribution of characters of printable_char.
Generates strings with distribution of characters of printable_char.
val small_printable_string : string arbitraryval numeral_string : string arbitraryGenerates strings with a distribution of length of small_nat and distribution of characters of numeral_char.
Generates strings with a distribution of characters of numeral_char.
Generates lists with length from the given distribution.
Generates arrays with length from the given distribution.
Combines two generators into a generator of pairs. Order of elements can matter (w.r.t shrinking, see Shrink.pair)
Combines three generators into a generator of 3-tuples. Order matters for shrinking, see Shrink.pair and the likes
val quad :
'a arbitrary ->
'b arbitrary ->
'c arbitrary ->
'd arbitrary ->
('a * 'b * 'c * 'd) arbitraryCombines four generators into a generator of 4-tuples. Order matters for shrinking, see Shrink.pair and the likes
Choose between returning Some random value, or None.
Generator of functions of arity 1. The functions are always pure and total functions:
it never does side effects, like printing or never raise exceptions etc. The functions generated are really printable. renamed from fun1.
@since 0.6
Generator of functions of arity 2. The remark about fun1 also apply here. renamed from fun2.
A function packed with the data required to print/shrink it. See Fn to see how to apply, print, etc. such a function.
One can also directly pattern match on it to obtain the executable function.
For example:
QCheck.Test.make
QCheck.(pair (fun1 Observable.int bool) (small_list int))
(fun (Fun (_,f), l) -> l=(List.rev_map f l |> List.rev l))module Fn : sig ... endUtils on functions
val fun1 : 'a Observable.t -> 'b arbitrary -> ('a -> 'b) fun_ arbitraryfun1 o ret makes random functions that take an argument observable via o and map to random values generated from ret. To write functions with multiple arguments, it's better to use Tuple or Observable.pair rather than applying fun_ several times (shrinking will be faster).
module Tuple : sig ... endfun_nary makes random n-ary functions. Example:
let module O = Observable in
fun_nary Tuple.(O.int @-> O.float @-> O.string @-> o_nil) bool)val fun2 :
'a Observable.t ->
'b Observable.t ->
'c arbitrary ->
('a -> 'b -> 'c) fun_ arbitraryval fun3 :
'a Observable.t ->
'b Observable.t ->
'c Observable.t ->
'd arbitrary ->
('a -> 'b -> 'c -> 'd) fun_ arbitraryval fun4 :
'a Observable.t ->
'b Observable.t ->
'c Observable.t ->
'd Observable.t ->
'e arbitrary ->
('a -> 'b -> 'c -> 'd -> 'e) fun_ arbitraryPick an element randomly in the list.
Pick an element randomly in the array.
val frequency :
?print:'a Print.t ->
?small:('a -> int) ->
?shrink:'a Shrink.t ->
?collect:('a -> string) ->
(int * 'a arbitrary) list ->
'a arbitrarySimilar to oneof but with frequencies.
Same as oneofl, but each element is paired with its frequency in the probability distribution (the higher, the more likely).
Same as frequencyl, but with an array.
map f a returns a new arbitrary instance that generates values using a#gen and then transforms them through f.
Specialization of map when the transformation preserves the type, which makes shrinker, printer, etc. still relevant.
val map_keep_input :
?print:'b Print.t ->
?small:('b -> int) ->
('a -> 'b) ->
'a arbitrary ->
('a * 'b) arbitrarymap_keep_input f a generates random values from a, and maps them into values of type 'b using the function f, but it also keeps the original value. For shrinking, it is assumed that f is monotonic and that smaller input values will map into smaller values.