This document discusses factors that influence the evolution and adoption of programming languages like Scala. It argues that for a language to be evolutionarily stable, it needs to survive, be adopted by a user base that is more than 1%, and be attractive. Scala's main value proposition is its support for static metaprogramming, but it needs to improve concurrency support, reduce boilerplate code, and simplify its core to lower the learning curve. New developments like Dotty and Squid could help address current issues and support further language evolution.

1. SCALA:
— GROW OR SHRINK ?
FACTORS OF HATE/LOVE RELATIONSHIPS
SCALA WAY VS WAYS OF TECHNICAL EVOLUTION
// Ruslan Shevchenko
<ruslan@shevchenko.kiev.ua>
@rssh1

2. Disclaimer: %noassoc
I’m not associated with any organization, which have
influence on the language design.
Try to avoid:
complain on things, which you can’t change
speaking about decisions of others.
Instead:
Analyze technical/social/economics phenomenas

3. 80 vs Now =>
C / Objective-C / C++ / Objective - C++
Pascal / Modula 2
Algol 60 / Algol 68 / …
Java {1, 1.1, 1.2 … 1.5, 6, 7, 8, 9 ….. }
Scala { 2.7, .. 2.13 -> 3, … }
Smalltalk 80
C++ { __, 0x, 17, 19, 21 … }

4. Evolution (where is beast ?)
language usage ~ type of bacteria
software project ~ organism
people, money ~ resources
horizontal gene transfer.
gene: feature/idiom/(incapsulated into libraries …)
//biology evolution— decisions are accident
//technical evolution— decisions generated by committee
this difference is not very big.

5. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive

6. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive
Population > 1 %
∃ • EPFL Labs (Gov. financing)
• Lightbend ( Commercial financing)
• Community Center (Org ?)
• Support industry: Hydra, SoftwareMill,
etc..
• Monetization of PL ? (common problem)
• Oracle try to monetize JVM

7. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive
Static metaprogrammig.
• Unique, popular in PL academia world.
• Will be better in Dotty: Staging/Partial
Evaluation
• Can emulate most of the other language
features without (with little) compiler
change:
• RUST Derive: Scalaz-deriving
• coroutines - storm-enrote
• go : scala-gopher, etc.
// technical part will follow

8. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive
Static metaprogrammig.
• Unique, popular in PL academia world.
• Will be better in Dotty: Staging/Partial
Evaluation
• Can emulate most of the other language
features without (with little) compiler
change:
• RUST Derive: Scalaz-deriving
• coroutines - storm-enrote
• go : scala-gopher, etc.
// technical part will follow
• Metaprogramming still hard and incomplete.
• Distance between academic concept/real industrial API
• async/await
• storm/enroute
• monadless …..
• Now all stalled: wait new API in dotty/(squid in scala2)
• JVM (but exists scala-native & scala-js).

9. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive
Hello! I'm A .signature Virus.
Join In The Fun And Copy Me Into Yours!
//memes
Learning curve

10. What needed to be evolutionary stable ?
Survie
Adopt
Be attractive
//memes
Learning curve
({ type EF[X]=Either[S,X] })#EF
val x = 1
culture
Isolate subsets
Software development
is not scalable !
Education too……..
Kaa’s law ….

11. Non-Issues:
- FP/OOP (this is solved problem)
Unsolved problems:
- Distributed computing.
- Mass-parallelism (GPU, TPU)
Issues:
- concurrency support
- small boilerplate instead no-boilerplate
- big core //gene rubbish

12. Concurrency support.
Monad [Future, Task] (extra wrap)
Streams [Akka-Streams, Monix, fs2] (extra wrap)
2009. CPS [shift/reset]. Tiark Rompf, Ingo Maier Martin Odersky. Implementing First-Class Polymorphic Delimited
Continuations by a Type-Directed Selective CPS-Transform.: https://infoscience.epfl.ch/record/149136/files/icfp113-rompf.pdf
— deprecated, not prod. quality
2013. Async/Await. Philipp Haller and Jason Zaugg. SIP22-Async. https://docs.scala-lang.org/sips/async.html.
— dormant, not prod. quality (try/catch support is missing)
2017. Coroutines. Aleksandar Prokopec, Fengyun Liu. Theory and Practice of Coroutines with Snapshots. http://
aleksandar-prokopec.com/publications/theory-and-practice-of-coroutines-with-snapshots/
—- Yet not ready, not prod. quality.
using inside hight-order functions…. - theoretically possible (implemented in gopher)

13. Concurrency/Learning Curve
for{ x <- retrieveA()
y <- retrieveB() }
yield x+y
async{ retrieveA()! + retrieveB()! }
vs
• Monads
• Combinators
• Nesting
// in Go, C#, Kotlin, C++ (Karl!), Python, JavaScript
something is implemented.

14. small boilerplate instead no-boilerplate
pathEndOrSingleSlash {
getAll
} ~ pathPrefix(Segment) { name =>
pathEndOrSingleSlash {
put {
saveValue(name)
} ~ get {
findValue(name)
} ~ delete {
deleteValue(name)
}
}
}
def getAll():List[String] = ..
@JsonBin
@Path(“entities”)
class Service
{
List<String> getAll()
@Post
void saveValue(@Path name)
String findValue(@Path name)
@Delete
// Java version is cleaner
//too easy implement all directly

15. big core
any AST transformation => check all possible
variants.
Unroll syntax sugar themselves
Possible solutions:
IR layer, which will keep simplifier code (like in
Scala.JS)
Standard transform library.
// will be better in dotty

16. Conclusion
FP/OOP - non issue.
The unique value - static metaprogramming.
Will allow lower barrier to language extending, but need to
be done at first.
Where other mainstream languages outperform Scala:
Concurrency support
Tooling (smaller core)

17. Technical part: squid
next generation of macro
http://epfldata.github.io/squid/home.htm
Lionel Parreaux, Amir Shaikhha, and Christoph E. Koch. 2017. Squid: Type-Safe,
Hygienic, and Reusable Quasiquotes. In Proceedings of the 2017 8th ACM
SIGPLAN Symposium on Scala (SCALA 2017).
scala> def power(n: Int, x: ClosedCode[Double]):
ClosedCode[Double] = {
| if (n > 0) code"${power(n-1, x)} * $x"
| else code"1.0"
| }
scala> val pgrm = power(3, code”0.5")
scala> pgrm.compile

18. Technical part: dotty metaprogramming
https://dotty.epfl.ch/docs/reference/principled-meta-
programming.html
probably, next direction for squid
inline def power(inline n: Int, x: Double) =
~powerCode(n, '(x))
private def powerCode(n: Int, x: Expr[Double]): Expr[Double] =
if (n == 0) '(1.0)
else if (n == 1) x
else if (n % 2 == 0)
'{ { val y = ~x * ~x; ~powerCode(n / 2, '(y)) } }
else
‘{ ~x * ~powerCode(n - 1, x) }

19. Technical part: scalar-deriving
https://gitlab.com/fommil/scalaz-deriving
no dependency from scalar ;)
scalac plugin, to expand annotation into boilerplate
@deriving(Encoder, Decoder)
case class Bar(s: String)
case class Bar(s: String)
object Bar {
implicit val _deriving_encoder: Encoder[Bar] = deriving
implicit val _deriving_decoder: Decoder[Bar] = deriving
}

20. Thanks for attending
Ping me, if needed
ruslan@shevchenko.kiev.ua
@rssh1
https://github.com/rssh
//PWL-Kyiv tomorrow
PaxOS and CRDT
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