Scala by the Lagoon - Random Data Generation con ScalaCheck

Durante il talk verranno illustrate delle tecniche per sfruttare le caratteristiche di ScalaCheck per generare istanze random di tipi e ci sarà occasione di capire come queste istanze possano essere combinate per generare random case classes. Analizzeremo insieme le proprietà dei generatori di ScalaCheck attraverso degli esempi live di manipolazione di generatori esistenti per soddisfare le esigenze specifiche dei nostri casi di test.

Transcript

1. RANDOM DATA GENERATION WITH SCALACHECK @DANIELASFREGOLA SCALA BY THE LAGOON
2. HELLOOOOO > Scala Nerd > Based in London, UK > Scala-Italy slack channel lover! ❤
6. COMMON APPROACHES STATIC FIXTURES
7. COMMON APPROACHES SCALACHECK
8. 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: ""
9. PROPERTY BASED TESTING - PROS > Test data is less biased > On failing, counter-example provided > Higher confidence that our code probably works
10. PROPERTY BASED TESTING - CONS > Restructuring your tests as properties is not always immediate > Not always applicable with side effects > Configurations do affect the test result
12. COMMON APPROACHES
13. CAN WE COMPROMISE?
14. CAN WE REUSE SOME OF THE SCALACHECK MAGIC?
15. RANDOM DATA GENERATOR GITHUB.COM/DANIELASFREGOLA/RANDOM-DATA-GENERATOR
16. RANDOM DATA GENERATOR case class Example(text: String, n: Int) val example: Example = random[Example] // Example(ਈῒ
    !䑪⡨ᵅ䎎, 73967257)
17. 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) } }
18. 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
19. LESS BIASED TEST DATA For every session different test data will be randomly* selected * We can still fix the seed when needed!
20. BUGS BUGS EVERYWHERE
21. 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) } }
22. 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) } }
23. HOW DOES IT WORK?
24. SCALACHECK1 1 github.com/rickynils/scalacheck
25. LET'S LOOK AT THE CODE
26. 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
28. 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
29. MAKE SURE THAT THE GENERATED TEST DATA MAKES SENSE
30. 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
31. 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)
32. WHAT RANDOM DATA GENERATOR IS NOT FOR
33. WHAT'S NEXT?
34. WRAP UP > 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
35. Testing shows the presence, not the absence of bugs — Edsger W. Dijkstra, 1969
36. THANK YOU! > Random Data Generator: github.com/DanielaSfregola/random-data-generator > Twitter: @DanielaSfregola > Blog: danielasfregola.com