Minitest-Proptest allows tests to be expressed in terms of universal properties, and will generate test cases to try to disprove them the cases listed automatically. This library is heavily inspired by QuickCheck and Hypothesis.
Tests should be written to express a universal property in the simplest manner
achievable. Properties can be expressed via property
within any context where
an assertion is allowed.
Property tests should aim to express universal properties of the code under test - the framework will generate test cases to try to find counter-examples to properties listed.
Tests should usually follow the following sequence:
- Allocate arbitrary primitives
- Build necessary data structures from the primitives
- Provide predicates to filter out inappropriate data generation
- Express assertions and return a boolean
- All Minitest assertions are available within a property. They will conveniently return a boolean.
- The block provided to the
property
method is an implicit assertion - the assertion will fail if the return value is not truthy.
A trivial example can be seen below:
class PropertyTest < Minitest::Test
def test_average_list
# Allocate a list of Integers
xs = arbitrary Array, UInt8
# The list must contain at least one value
where { !xs.empty? }
# Calculate the list's average
average = xs.reduce(&:+) / xs.length.to_f
# Conclude the block with the core assertion of universal property:
xs.min <= average <= xs.max
end
end
This can also be expressed with assert
:
class PropertyTest < Minitest::Test
def test_average_list
# Allocate a list of Integers
xs = arbitrary Array, UInt8
# The list must contain at least one value
where { !xs.empty? }
# Calculate the list's average
average = xs.reduce(&:+) / xs.length.to_f
# Conclude the block with the core assertion of universal property:
assert xs.min <= average <= xs.max
end
end
Using Minitest assertions is particularly useful when a long chain of logic would otherwise be necessary to express a success case.
In order for tests and shrinking to work as expected, the two following tips will set a test writer up for success:
- Allocate everything you might need up front
- Allocate everything you need in the same place
Allocating everything that will be needed up front avoids the possibility of predicating allocation on other allocations. This breaks the shrinking logic and must be avoided.
Allocating everything in the same place makes it easier to parse counter-examples when they're found.
The following types are provided by Minitest-Proptest:
- Unbounded
Integer
- Unsigned Integers
UInt8
UInt16
UInt32
UInt64
- Signed Integers
Int8
Int16
Int32
Int64
- Floating Point
Float32
Float64
Float
- identical toFloat64
Complex
numbersRational
numbers- Text types
Char
- any single character 0x00-0xffASCIIChar
- any character 0x00-0x7fString
- arbitrary length string ofChar
s
Time
- any time between 1901-12-13 20:45:52 and 2038-01-19 03:14:07 UTCBool
- Polymorphic types
Array a
- array of arbitrary length of another typeHash a b
- hash of arbitrary size from typea
to typeb
Range a
- range between two values whose classes implement<=>
Generators provide the machinery through which arbitrary values are provided, scored, and shrunk when a counterexample is found. It is typically only relatively primitive data which require generators, while non-primitive objects are generally constructed from arbitrary data.
Writing high quality generators for primitive types can make or break property tests' ability to provide reliable results. While a large number of built-in primitive generators are provided, cases will arise for which additional generators are required to improve tests' clarity.
Generators are written with the generator_for
method, which is available
globally. The simplest case is to create a generator for a type which generates
data directly.
- The
sized
method provides a random Integer from 0 to the provided value, inclusive. This provides direct access to entropy for the purpose of primitive generation.BoxedUInt8 = Struct.new(:value) generator_for(BoxedUInt8) do i = sized(0xff) BoxedUInt8.new(i) end # ... boxed = arbitrary BoxedUInt8
- The
one_of
method will produce a random selection of a set of values. The set may be given as any collection which implementsto_a
. This provides indirect access to entropy via the selection of value.Dice = Struct.new(:value) generator_for(Dice) do Dice.new(one_of(1..6)) end # ... one_d_six = arbitrary Dice
Finding counter-examples is made more helpful when the counter-examples are able
to be meaningfully reduced to an easier failure case about which to reason.
Built-in generators which provide numeric values will tend towards zero as they
are shrunk (n.b. Float
types will consider NaN
and Infinity
as having an
equal score to 0), and types which are list-like will try to drop elements while
shrinking the elements' respective values. The default behavior of any custom
generator will be to convert the value to an integer via to_i
and take its
absolute value.
If a scoring and shrink function are provided to the generator, any failure condition will be retried in forms which are generated according to the functions in question until the score closest to zero is obtained.
The BoxedUInt8
definition can be rewritten for shrinking with the following
shrink and score functions:
BoxedUInt8 = Struct.new(:value)
generator_for(BoxedUInt8) do
i = sized(0xff)
BoxedUInt8.new(i)
end.with_shrink_function do |i|
candidates = []
y = i.value
until y.zero?
candidates << BoxedUInt8.new(i.value - y)
candidates << BoxedUInt8.new(y)
y = (y / 2.0).to_i
end
candidates
end.with_score_function do |i|
i.value
end
In cases where a type might be inhabited by various other types, the block
provided to generator_for
can take arguments. This block will be treated as
equivalent to a curried constructor, e.g.
Twople = Struct.new(:fst, :snd) do
generator_for(Twople) do |fst, snd|
Twople.new(fst, snd)
end.with_shrink_function do |ffst, fsnd, t|
f_candidates = ffst.call(t.fst)
s_candidates = fsnd.call(t.snd)
f_candidates.reduce([]) do |candidates, fst|
candidates + s_candidates.map { |snd| Twople.new(fst, snd) }
end
end.with_score_function do |ffst, fsnd, t|
ffst.call(t.fst) + fsnd.call(t.snd)
end
# ...
tuple = arbitrary Twople, Int8, Int8
Note that the functions for shrinking and scoring should be parameterized to accept functions for shrinking or scoring the contained data. These can be used to further refine the generation of minimal counterexamples.
In cases where a given datatype can be arbitrarily sized and it's useful to
generate varying sizes of data for tests, functions for appending and generating
an empty/initial state of the datatype with the with_append
and with_empty
methods respectively.
The append and empty functions for generating Arrays can serve as a reasonable example:
generator_for(Array) do |x|
[x]
end.with_append(0, 0x10) do |xs, ys|
xs + ys
end.with_empty { [] }
Note that with_append
requires a minimum and maximum size which is acceptable
to generate to be supplied.
Additional examples of generators are available in lib/minitest/proptest/gen.rb
Minitest-Proptest is designed to work with Minitest 5.0 or greater. Non-EOL Rubies are tested to work; older rubies may work as well.
Minitest-Proptest is released under the MIT License
Whether the contribution concerns code, documentation, bug reports, or something else entirely, contributions are welcome and appreciated!
If the contribution is relating to a security concern, please see SECURITY.md.
For all other contributions, please see CONTRIBUTING.md. In short:
- Fork the project.
- Add tests for any new functionality/to verify that bugs have been fixed.
- Send a pull request on GitHub.
The Minitest-Proptest project is governed by a Code of Conduct.