Taming the Scala type system

scala, types

Solution

For updated code.

The compiler is very fair with complaints. Algorithm use one subclass of State as denoted and state successor may return any other subclass of State[M]

You may declare IntegerOne class

trait Abstract[T]
class IntegerOne extends Abstract[Int]

but the compiler have no clue that all instances of AbstractOne[Int] would be IntegerOne. It assume that there may be another class that also implements Abstract[Int]

class IntegerTwo extends Abstract[Int]

You may try to use implicit conversion to cast from Abstract[Int] to IntegerOne, but traits have no implicit view bounds as they have no value parameters at all.

Solution 0

So you may rewrite your Algorithm trait as an abstract class and use implicit conversion:

abstract class MyAlgorithm[MT <: Move, ST <: State[MT]] (implicit val toSM : State[MT] => ST) extends Algorithm {
  override type M = MT // finalize types, no further subtyping allowed
  override type S = ST // finalize types, no further subtyping allowed
  def score(s : S) : Int = s.moves.size
  override def bestMove(s : S) : M = {
    val groups = s.moves.groupBy( m => score(toSM ( s.successor(m)) ) )
    val max = groups.keys.max
    groups(max).head
  }
}

implicit def toMyState(state : State[MyMove]) : MyState = state.asInstanceOf[MyState]

object ConcreteAlgorithm extends MyAlgorithm[MyMove,MyState]

object Main extends App {
  val s = new MyState(Map())
  val m = ConcreteAlgorithm.bestMove(s)
  println(m)
}

There are two drawbacks in this solution

- using implicit conversion with asInstanceOf

- tying types

You may extinguish first as the cost of further type tying.

Solution 1

Let use Algorithm as sole type parameterization source and rewrite type structure accordingly

trait State[A <: Algorithm] { _:A#S =>
  def moves : List[A#M]
  def successor(m : A#M): A#S
}

trait Algorithm{
  type M <: Move
  type S <: State[this.type]
  def bestMove(s : S) : M
}

In that case your MyAlgorithm may be used without rewriting

trait MyAlgorithm extends Algorithm {
  def score(s : S) : Int = s.moves.size
  override def bestMove(s : S) : M = {
    val groups = s.moves.groupBy(m => score(s.successor(m)))
    val max = groups.keys.max
    groups(max).head
  }
}

Using it:

class MyState(val s : Map[MyMove,Int]) extends State[ConcreteAlgorithm.type] {
  def moves = MyMove(1) :: MyMove(2) :: Nil
  def successor(p : MyMove) = new MyState(s.updated(p,1))
}

object ConcreteAlgorithm extends MyAlgorithm {
  override type M = MyMove
  override type S = MyState
}

object Main extends App {
  val s = new MyState(Map())
  val m = ConcreteAlgorithm.bestMove(s)
  println(m)
}

See more abstract and complicated usage example for this tecnique: Scala: Abstract types vs generics

Solution 2

There is also a simple solution to your question but I doubt it can solve your problem. You will eventually stuck upon type inconsistency once again in more complex use cases.

Just make MyState.successor return `this.type` instead of `State[M]`

trait State[M <: Move] {
  def moves : List[M]
  def successor(m : M): this.type
}

final class MyState(val s : Map[MyMove,Int]) extends State[MyMove] {
  def moves = MyMove(1) :: MyMove(2) :: Nil
  def successor(p : MyMove) = (new MyState(s.updated(p,1))).asInstanceOf[this.type]
}

other things are unchanged

trait Algorithm{
  type M <: Move
  type S <: State[M]
  def bestMove(s : S) : M
}

trait MyAlgorithm extends Algorithm {
  def score(s : S) : Int = s.moves.size
  override def bestMove(s : S) : M = {
    val groups = s.moves.groupBy(m => score(s.successor(m)))
    val max = groups.keys.max
    groups(max).head
  }
}

object ConcreteAlgorithm extends MyAlgorithm {
  override type M = MyMove
  override type S = MyState
}

object Main extends App {
  val s = new MyState(Map())
  val m = ConcreteAlgorithm.bestMove(s)
  println(m)
}

Pay attention to `final` modifier to MyState class. It ensures that conversion asInstanceOf[this.type] is correct one. Scala compiler may compute itself that final class keeps always `this.type` but it still have some flaws.

Solution 3

There is no need to tie Algorithm with custom State. As long as Algorithm does not use specific State function it may be written simpler without type bounding exercises.

trait Algorithm{
  type M <: Move
  def bestMove(s : State[M]) : M
}
trait MyAlgorithm extends Algorithm {
  def score(s : State[M]) : Int = s.moves.size
  override def bestMove(s : State[M]) : M = {
    val groups = s.moves.groupBy(m => score(s.successor(m)))
    val max = groups.keys.max
    groups(max).head
  }
}

This simple example doesn't come to my mind quickly because I've assumed that binding to different states are obligatory. But sometimes only part of system really should be parameterized explicitly and your may avoid additional complexity with it

Conclusion

Problem discussed reflects bunch of problems that arises in my practice very often.

There are two competing purposes that should not exclude each other but do so in scala.

- extensibility

- generality

First means that you can build complex system, implement some basic realization and be able to replace its parts one by one to implement more complex realization.

Second allows your to define very abstract system, that may be used for different cases.

Scala developers had very challenging task for creating type system for a language that can be both functional and object oriented while being limited to jvm implementation core with huge defects like type erasure. Co/Contra-variance type annotation given to users are insufficient for expressing types relations in complex system

I have my hard times every time I encounter extensiblity-generality dilemma deciding which trade-off to accept.

I'd like not to use design pattern but to declare it in the target language. I hopes that scala will give me this ability someday.

Problem

Original source

Related problems

• Scala: Abstract types vs generics