Random Data Generation with ScalaCheck - Scala By the Bay 2016

ScalaCheck is a well-known library for property-base testing. However, property-base testing is not always possible when side effects are involved, for example when writing an integration test that involves data being stored in a database. When writing non-property-base tests, we often need to initialise some data and then verify some assertions on it. However, manual data generation can make our data biased and preventing us from spotting bugs in our code. Having our data generated randomly not only it would make our test less biased, but it will also make it a lot more readable by highlighting what part of our data are actually relevant in our test.

In this talk we will discuss how to reuse some of the existing ScalaCheck code to generate random instances of given types and how these can be combined to generate random case classes. We will analyse the properties of a ScalaCheck generator and provide examples of how we can manipulate existing generators to meet our needs.

Transcript

1. RANDOM DATA GENERATION WITH SCALACHECK @DANIELASFREGOLA SCALA BY THE BAY 2016
2. COMMON APPROACHES
3. SCALACHECK - PROPERTY BASED TESTING property("startsWith") = forAll { (a: String, b: String) => (a+b).startsWith(a) } // + String.startsWith: OK, passed 100 tests. property("concatenate") = forAll { (a: String, b: String) => (a+b).length > a.length && (a+b).length > b.length } // ! String.concat: Falsified after 0 passed tests. // > ARG_0: "" // > ARG_1: ""
6. CAN WE COMPROMISE?
7. RANDOM DATA GENERATOR GITHUB.COM/DANIELASFREGOLA/RANDOM-DATA-GENERATOR
8. RANDOM DATA GENERATOR case class Example(text: String, n: Int) val example: Example = random[Example] // Example(ਈῒ
   !䑪⡨ᵅ䎎, 73967257)
9. RANDOM DATA GENERATOR case class User(name: String, surname: String) "create a user" { val user = random[User] Post("/users", creation) ~> check { status === StatusCodes.Created assertCreation(user) } }
10. FIX YOUR SEED Each session has a seed number associated Generating random data with seed -2481216758852790303 Use it to debug problematic tests export RANDOM_DATA_GENERATOR_SEED=-2481216758852790303 unset RANDOM_DATA_GENERATOR_SEED
11. LESS BIASED TEST DATA For every session different test data will be randomly* selected! * We can still fix the seed when needed
12. BUGS BUGS EVERYWHERE
13. EASIER TO MAINTAIN case class User(name: String, surname: String, age: Int) "create a user" { val user = random[User] Post("/users", user) ~> check { status === Created assertCreated(user) } }
14. IMPROVED READABILITY case class User(name: String, surname: String, age: Int) "reject user creation of an underage user" { val user = random[User].copy(age = 17) Post("/users", user) ~> check { status === BadRequest assertNotCreated(user) } }
15. HOW DOES IT WORK?
16. SCALACHECK1 1 github.com/rickynils/scalacheck
17. SCALACHECK-SHAPELESS2 AUTOMATICALLY INFERS ARBITRARY[T] IF: > T is a case class > T is an sealed trait ...BUT IT WILL IMPACT THE COMPILATION TIME 2 github.com/alexarchambault/scalacheck-shapeless
18. ARBITRARY OF CUSTOM TYPE import java.util.Currency import scala.collection.JavaConversions._ implicit val arbitraryCurrency: Arbitrary[Currency] = Arbitrary { Gen.oneOf(Currency.getAvailableCurrencies.toSeq) } random[Currency] // java.util.Currency = OMR
19. MAKE SURE THAT THE GENERATED TEST DATA MAKES SENSE
20. CUSTOMISE YOUR ARBITRARY Before: random[String] // !!ⳘԺ Ꙑ
     After: /** Generates a string of alpha characters */ implicit val arbitraryString: Arbitrary[String] = Arbitrary(Gen.alphaStr) random[String] // hqtbonxacrmvmuMpofwtasrojjnycwuoTfkrhOpli
21. CUSTOMISE YOUR ARBITRARY case class Person(name: String, age: Int) implicit val arbitraryPerson: Arbitrary[Person] = Arbitrary { for { name <- Gen.oneOf("Daniela", "John", "Martin") age <- Gen.choose(0, 100) } yield Person(name, age) } random[Person] // Person(John,16)
22. WHAT RANDOM DATA GENERATOR IS NOT FOR
23. SUMMARY > A compromise between using ScalaCheck and predefined fixtures > Customise the data generation to your context > Do not ignore random test failures > Use it only for test purposes
24. Testing shows the presence, not the absence of bugs — Edsger W. Dijkstra, 1969
25. THANK YOU! > Random Data Generator: github.com/DanielaSfregola/random-data-generator > Twitter: @DanielaSfregola > Blog: danielasfregola.com