dcheck ~master
Library for generating random data sets and automated checking of test constraints
To use this package, put the following dependency into your project's dependencies section:
DCheck
Almost isn't usable until the DMD [feature](https://github.com/DProgrammingLanguage/dmd/pull/2417) is completed
Library for generating random data sets and automated checking of test constraints. The library design is inspired by Haskell one  QuickCheck. User define Arbitrary
template (behaves like typeclass in haskell) for a type to add random generating feature and result shrinking. Then the library can pass random sets of data into special functions called constraints and provide you fancy formatted minimal fail case.
Usage
First, consider simple example:
unittest
{
checkConstraint!((int a, int b) => a + b == b + a);
}
As the provided delegate is always true unittest passes clearly.
Negative result example:
unittest
{
import std.math;
checkConstraint!((int a, int b) => abs(a) < 100 && abs(b) < 100)
}
DCheck will find the fail case:
==============================
Constraint __lambda2 is failed!
Calls count: 1. Shrinks count: 24
Parameters:
0: int "" = 61
1: int "" = 30
Result shrinking is performed to provide you concise fail case.
DCheck can detect parameter names for regular functions:
bool foo(bool a, bool b)
{
return a && !b;
}
unittest
{
checkConstraint!foo;
}
Output:
core.exception.AssertError:
==============================
Constraint foo is failed!
Calls count: 1. Shrinks count: 0
Parameters:
0: bool "a" = true
1: bool "b" = true
Adding custom types
To be able to use checkConstrained
function all parameter types of a function should have Arbitrary!T
instance. This template includes three main components:
generate
function that takes nothing and returns range ofT
. The function is used to generate random sets of testing data. Size of required sample isn't passed thus use lazy ranges to generate possible infinite set of data.shrink
function that takes value ofT
and returns range of truncated variations. The function is used to reduce failing case data to minimum possible set. You can return empty array if you like to get large bunch of random data when constraint fails.specialCases
function that takes nothing and returns range ofT
. The function is used to test some special values for particular type likeNaN
ornull
pointer. You can return empty array if no testing on special cases is required. At the momentspecialCases
is not used, but it will change at future releases.
To generate lazy ranges there is handy function from dcheck.generator
. Consider Arbitrary!T
implementation for integral types:
template Arbitrary(T)
if(isIntegral!T)
{
// Helpfull to check your implementation, will print what exactly goes wrong
static assert(CheckArbitrary!T);
auto generate()
{
// dcheck.generator wraps delegate to produce finite and infinite lazy ranges
return (() => Maybe!T(uniform!"[]"(T.min, T.max))).generator;
}
auto shrink(T val)
{
// functor to encapsulate state
// to find minimal test case fast we half number each time
class Shrinker
{
T saved;
this(T firstVal)
{
saved = firstVal;
}
Maybe!T shrink()
{
if(saved == 0) return Maybe!T.nothing;
saved = saved/2;
return Maybe!T(saved);
}
}
return (&(new Shrinker(val)).shrink).generator;
}
T[] specialCases()
{
return [T.min, 0, T.max];
}
}
Building
To use DCheck as dependency in your project add the following in your dub.json
file:
"dependencies": {
"dcheck": ">=0.1.0"
}
To run unittests, clone the repo and run:
dub test
 Registered by Anton Gushcha
 ~master released 5 years ago
 NCrashed/DCheck
 MIT
 Copyright © 2014, Anton Gushcha
 Authors:
 Dependencies:
 none
 Versions:

0.1.0 2014Mar27 ~master 2014Nov04  Download Stats:


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 Short URL:
 dcheck.dub.pm