qcheck

library qcheck

module QCheck_runner
Quickcheck inspired propertybased testing
The 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 counterexamples as small as possible), print them, etc. Auxiliary modules such asGen
,Print
, andShrink
can be used along withmake
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:
 List.rev is involutive:
let test =
QCheck.(Test.make ~count:1000
(list int) (fun l > List.rev (List.rev l) = l));;
QCheck.Test.check_exn test;;
 Not all lists are sorted (false property that will fail. The 15 smallest counterexample lists will be printed):
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;;
 generate 20 random trees using
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 ... end
Pretty printing
module Print : sig ... end
module Iter : sig ... end
module Shrink : sig ... end
Observe Values
Observables 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/quickcheckforcore/ and Koen Claessen's "Shrinking and Showing functions".
module Observable : sig ... end
Arbitrary
A 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 = private {
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 counterexamples.
NOTE the collect field is unstable and might be removed, or moved into Test
.
Made private
val make :
?print:'a Print.t >
?small:( 'a > int ) >
?shrink:'a Shrink.t >
?collect:( 'a > string ) >
?stats:'a stat list >
'a Gen.t >
'a arbitrary
Builder for arbitrary. Default is to only have a generator, but other arguments can be added.
Update shrinker by only keeping smaller values satisfying the given invariant.
Tests
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 ... end
Result of running a test
module Test : sig ... end
Subtests
The infrastructure used to find counterexamples to properties can also be used to find data satisfying a predicate, within a property being tested.
See https://github.com/ccube/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 >
'a
Toplevel version of find_example
. find_example_gen ~f arb ~n
is roughly the same as Gen.generate1 (find_example ~f arb > gen)
.
Combinators for
Choose among the given list of generators. The list must not be empty; if it is Invalid_argument is raised.
val unit : unit arbitrary
Always generates ()
, obviously.
val bool : bool arbitrary
Uniform boolean generator.
val float : float arbitrary
Generates regular floats (no nan and no infinities).
val pos_float : float arbitrary
Positive float generator (no nan and no infinities).
val neg_float : float arbitrary
Negative float generator (no nan and no infinities).
val int : int arbitrary
Int generator. Uniformly distributed.
val int_bound : int > int arbitrary
int_bound n
is uniform between 0
and n
included.
val int_range : int > int > int arbitrary
int_range a b
is uniform between a
and b
included. b
must be larger than a
.
val small_nat : int arbitrary
Small unsigned integers.
val small_int : int arbitrary
Small unsigned integers. See Gen.small_int
.
val small_signed_int : int arbitrary
Small signed integers.
val int32 : int32 arbitrary
Int32 generator. Uniformly distributed.
val int64 : int64 arbitrary
Int64 generator. Uniformly distributed.
val pos_int : int arbitrary
Positive int generator. Uniformly distributed.
val small_int_corners : unit > int arbitrary
As small_int
, but each newly created generator starts with a list of corner cases before falling back on random generation.
val neg_int : int arbitrary
Negative int generator. The distribution is similar to that of small_int
, not of pos_int
.
val char : char arbitrary
Uniformly distributed on all the chars (not just ascii or valid latin1).
val printable_char : char arbitrary
Uniformly distributed over a subset of chars.
val numeral_char : char arbitrary
Uniformly distributed over '0'..'9'
.
Generates strings with a distribution of length of small_nat
.
val string : string arbitrary
Generates 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 arbitrary
Generates 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 arbitrary
val numeral_string : string arbitrary
Generates 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 3tuples. Order matters for shrinking, see Shrink.pair
and the likes
val quad :
'a arbitrary >
'b arbitrary >
'c arbitrary >
'd arbitrary >
('a * 'b * 'c * 'd) arbitrary
Combines four generators into a generator of 4tuples. 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:
 when given the same argument (as decided by Pervasives.(=)), it returns the same value
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 ... end
Utils on functions
val fun1 : 'a Observable.t > 'b arbitrary > ( 'a > 'b ) fun_ arbitrary
fun1 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 ... end
fun_nary
makes random nary 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_ arbitrary
val fun3 :
'a Observable.t >
'b Observable.t >
'c Observable.t >
'd arbitrary >
( 'a > 'b > 'c > 'd ) fun_ arbitrary
val fun4 :
'a Observable.t >
'b Observable.t >
'c Observable.t >
'd Observable.t >
'e arbitrary >
( 'a > 'b > 'c > 'd > 'e ) fun_ arbitrary
Pick 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 arbitrary
Similar 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) arbitrary
map_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.