Opening keynote of Scala Days 2018, Berlin

1. Preparing For Scala 3
Adrian Moors
Martin Odersky
Scala Days Berlin
April 2018

2. Roadmap (from previous years)
Scala 2.12
Scala 2.13
Scala 3.0
TASTY,
middle end?
stdlib
collections
Dotty 0.1
Dotty 0.x releases
2016
backend, classpath handling
Scala 2.14
2017
2018
This is open source work, depends on community’s contributions.
à Roadmap is tentative, no promises:
“MVP” = minimal
viable
prototype
Scala 2.15?
migration

3. Roadmap (now)
Scala 2.12
Scala 2.13
Scala 3.0
TASTY,
middle end?
stdlib
collections
Dotty 0.1
Dotty 0.x releases
2016
backend, classpath handling
Scala 2.14
2017
2018
This is open source work, depends on community’s contributions.
à Roadmap has held up pretty well so far!
“MVP” = minimal
viable
prototype
migration Early 2020
Early 2020

4. License Change
http://scala-lang.org/news/license-change.html
BSD 3 à Apache v2.0
Concerns? let us know by Aug 10

5. Developer Survey
http://scala-lang.org/news/survey-2018.html
Would love to hear from you!
Takes 15 min

6. Why Scala 3 ?

7. The Essence of Scala:
Fusion of functional and
object-oriented programming

8. The Essence of Scala:
Fusion of functional and
object-oriented programming
in a typed setting
• functions for the logic
• objects for the modularity

9. Success!
Starting from a statically typed OO core
language, Scala pioneered
closures, function types, expression orientation,
tuples, local type inference, pattern matching,
traits, lazy vals, by-name parameters, x:T syntax,
dependent types, implicit parameters, and more
Many other languages followed suit by
adopting some of these features:
C#, Kotlin, Swift, Java, …
🎉

10. Derailing It
• Scala as a worse Haskell for the JVM
• A better Java, without Scala’s deep parts
Both take one half of Scala’s features, but ignore
the synthesis

11. Derailing It
Haskalator: Scala as a worse Haskell for the JVM
• Haskell is a great language
• But Scala is not a good basis for emulating all
Haskell patterns
• If you choose to ignore Scala’s OOP parts,
there’s little point in using it at all!

12. Derailing It
A better Java, without Scala’s deep parts
• new languages such as Kotlin, Swift,
• improved languages such as C#, Java
• trade abstraction & composition for more ad-
hoc features,
• avoid the more esoteric FP parts by making it
less pleasant to express them.
à larger language, simpler programs?

13. 0
200
400
600
800
1000
1200
1400
1600
python haskell scala kotlin swift java8 c++ csharp
Grammar size in lines
Grammar size in lines

14. The Way Forward
We believe Scala’s fusion of FP and OOP is
still the most promising way forward for
general purpose software development.
But…

15. The Way Forward
But there are lots of things we have learned
since the inception of Scala, including
1. how to be pure without sacrificing
simplicity and performance
2. how to do meta programming, safely
3. how to cut down on boilerplate for new
idioms

16. The Way Forward
Incorporate these new techniques in the
language, to make it simpler, more focused,
and more pleasant to use.

17. Realizing Scala’s Potential
• become more opinionated
• simplify
• eliminate inconsistencies and puzzlers
• build on strong foundations
• consolidate language constructs to improve
consistency
safety
ergonomics
performance

18. Consistency
Improve orthogonality and eliminate restrictions:
• Intersection types A & B
• Union types A | B
• Implicit function types implicit A => B
• Dependent function types (x: A) => x.B
• Trait parameters trait T(x: A)
• Generic tuples (a, b, c)
== (a, (b, (c, ()))

19. Ergonomics
Make code readable and concise
• Enums enum Color {
case Red, Green, Blue
}
• Type lambdas [X] => F[X]

20. Safety
Enable precise domain modeling and safe refactoring.
• Multiversal equality List(“a”) == “b”
• Restrict implicit conversions
Also planned:
• Null safety String | Null
• Effect capabilities

21. Performance
Make abstractions cheaper:
• Opaque types opaque type A = B
• Erased parameters def f(erased x: A =:= B)

22. Removed
• existential types using forSome
• procedure syntax
• early initiliazers
• XML literals
• limit 22
• automatic () insertion
• weak conformance
• auto-tupling
• multi-parameter infix operators

23. Implicit Improvements
Implicits turned out to be where Scala innovated most.
They can be both a
blessing and a curse.
Goal for Scala 3:
Fewer curses!
à Simplicitly,
POPL 2018

24. so far:
Implicit Conversions
Implicit Parameters

25. in the future:
Implicit Conversions
Implicit Parameters

26. Cutting-down on implicit conversions
Extension clauses can subsume most valid use cases:
case class Circle(x: Double, y: Double, radius: Double)
extension CircleOps for Circle {
def circumference = radius * Pi * 2
}
instead of
implicit class CircleOps(circle: Circle)
extends AnyVal {
def circumference = circle.radius * Pi * 2
}

27. Cutting-down on implicit conversions
Most other uses (not just definitions!) require a
language import:
import language.implicitConversions
implicit def str2int(x: String) = x.toInt
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
import language.implicitConversions
val x: Int = “123”
*exempted are only conversions co-defined with their target type

28. Making Implicit Parameters more Useful
Multiple implicit
clauses
Explicit
applications
Implicit function
types
def f(implicit x: A)
(y: B)
(implicit z: C) = …
f.explicitly(a)(b)
implicit A => B

29. Implicit Function Types:
get purity without sacrificing
simplicity and performance.

30. Tooling
So far, we have:
• a new compiler: dotc
• rich IDE support through LSP with direct
support for VS Code.
• REPL
• Doc-tool
Most tooling is built around Tasty

31. Tasty
Typed abstract syntax trees
• serialization format for Scala
• complete position and type information
• all implicits are expanded out
• surprisingly compact (~ same size as
source)

32. The Tasty Vision
Tasty
.scala (2.x)
.scala (3.x)
.class (Java 8)
.js
.class (Java 11)
.out
macros
analyzers
optimizers
IDE
LSP

33. Tasty Use Cases
• Separate compilation
• Language servers for IDEs (via LSP)
• Macros
• Cross-building
à escape the curse of binary compatibility

34. Meta Programming, So Far
• Def macros (experimental),
macro paradise (plugin).
- Both are thin veneers around nsc.
• Scala Meta: External tools that analyze
and transform programs.

35. Principled Meta Programming
2 + 2 fundamental operators:
‘( … ) (quote)
~(...) (splice)
run
inline
Quote, splice + inline : macros
Quote, splice + run : staging

36. Principled Meta Programming
T Expr[T]
Restriction: Can’t look inside an Expr.
splice ~(…)
quote ‘(…)

37. Principled Meta Programming
T Expr[T] tasty.Tree
Solution: Bijection between Expr[T] (high-level)
and tasty.Tree (low-level)
reflect
reifysplice ~(…)
quote ‘(…)

38. The Tasty Vision
Tasty
.scala (2.x)
.scala (3.x)
.class (Java 8)
.js
.class (Java 11)
.out
macros
analyzers
optimizers
IDE
LSP

39. New Macros are “Blackbox”
They get expanded after type checking.
à Program must typecheck before
macros are expanded
à Macros always work on typed trees
à Hygienic by definition
à Drastically reduces # things that can
go wrong

40. Language-Level Solutions for
Lazy implicits ✔
Type lambdas ✔
Context injection ✔
Typeclass derivation (still to do)
Typelevel functions (to be explored)

41. Migration
• Despite many differences, Scala 2 and 3 are
still fundamentally the same language
• Source compatibility for common subset.
• Rewrite tools can handle much of the rest
(macros are the big exception here).
• Situation better than for Python 2 vs 3 because
of static typing & binary compatibility.

42. Binary Compatibility
today:
Dotty can link with
Scala-2.12 class files.
Scala 2 module
Dotty module

43. Binary Compatibility
today:
Dotty can link with
Scala-2.12 class files.
planned:
Two way compatibility
using Tasty as common
intermediate format.
Scala 2 module
Scala 3 module
Scala 2 module
Scala 3 module

44. Roadmap
2018 Flesh out design Dotty 0.x
Get feedback
Refinements
2019, first half -------------- Feature freeze ---------------
Scala 3
Stabilization dev previews
2020, first half Scala 3.0

45. Stability
So far:
• Most Scala 2 regression tests are in the Scala 3
test suite.
• Community build for core libraries and tools.
• All tools are built using Scala 2 first, and then
again with dotc.

46. Stability
Planned:
• Once there are developer previews, ensure that
core projects are published for Scala 3.
• Use dotc itself as the bootstrap root.
à“eat our own dogfood”
should use Scala 3 features in our own tools.

47. Try It Out Today!
dotty.epfl.ch
New versions are released every 6 weeks.

48. Questions,
Suggestions,
Concerns?
Talk to us anytime.
Also, there’s a panel where we will
respond to questions at the end of the
conference.
Plus, a contributors workshop on Friday.
Talk to Heather if you want to go.