* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download PowerPoint
Go (programming language) wikipedia , lookup
Structured programming wikipedia , lookup
Java performance wikipedia , lookup
Java ConcurrentMap wikipedia , lookup
Reactive programming wikipedia , lookup
Abstraction (computer science) wikipedia , lookup
Falcon (programming language) wikipedia , lookup
Class (computer programming) wikipedia , lookup
Design Patterns wikipedia , lookup
Mathematics of radio engineering wikipedia , lookup
Name mangling wikipedia , lookup
Functional programming wikipedia , lookup
Corecursion wikipedia , lookup
C Sharp syntax wikipedia , lookup
Lattice model (finance) wikipedia , lookup
Object-oriented programming wikipedia , lookup
C Sharp (programming language) wikipedia , lookup
A Pragmatic Introduction to Scala Magnus Madsen Presenting Scala: An alternative to Java Why I like Scala: • object-orientated and functional • elegant and concise • unrestrictive – gives freedom of choice Scala makes me a happier programmer! Warning: Scala is the gateway drug to Haskell A Playground for Fun Stuff: • Engineering Perspective: – Actor-based Programming – Embedded DSLs, and more ... • Research Perspective: – Higher-Kinded Types – Delimited Continuations – Abstract Types, and more ... A Used Car Analogy class Car { var frontRight: Wheel; var frontLeft: Wheel; var backRight: Wheel; var backLeft: Wheel; } class Wheel { ... } Quote […] I can honestly say if someone had shown me the Programming in Scala book back in 2003 I'd probably have never created Groovy. James Strachan (creator of Groovy) Case Study: MiniTAJS An inter-procedural dataflow analysis – a scaled down version of TAJS – has lots of cool stuff: • abstract syntax trees, control flow graphs, etc. • lattices, transfer functions, etc. – about 4500 lines of code • of which 90-95% are in functional style Main.scala package dk.brics.minitajs object Main { def main(args: Array[String]) { val options = Options.read(args.toList) Analysis.run(options) } } Options.scala case class Options(inputFile: File, context: Boolean, recency: Boolean, lazyprop: Boolean, ...); Case Classes: The bread and butter • A case class declaration: – case class Options(inputFile: File, ...) • Automatically gives us: – getters and setters – – – – – .equals() and .hashCode() .toString() .copy() .apply() .unapply() Options.scala object Options { def read(args: List[String]): Options = { val context = args.exists(_ == "--context"); val lazyprop = args.exists(_ == "--lazy"); ... Options(new File(args.last), context, recency, ...); } } Bool.scala abstract sealed class Bool { def join(that: Bool): Bool = (this, that) match { case (TrueBool, TrueBool) => TrueBool; case (TrueBool, FalseBool) => AnyBool; ... } } case object AnyBool extends Bool; case object TrueBool extends Bool; case object FalseBool extends Bool; case object NotBool extends Bool; Value.scala case class Value(..., bool: Bool, undef: Undef, ...) { def isMaybeTrue: Boolean = (bool eq TrueBool) || (bool eq AnyBool); def joinUndef: Value = copy(undef = undef.join(MaybeUndef)); } LatticeOps.scala abstract class LatticeOps(...) extends ContextMixin with RecencyMixin with PropagationMixin trait PropagationMixin { def propagate(state: BlockState, info: PropagateInfo, lattice: Lattice): Lattice; } new LatticeOps(...) with CallSensitivity with RecencyAbstraction with LazyPropagation Arguments Arguments Problem: In functional programming argument lists grow and grow Solution: Wrap arguments up inside a data type. In Scala this translates to a case class. Example def propagate(state: BlockState, sourceContext: Context, sourceBlock: BasicBlock, targetContext: Context, targetBlock: BasicBlock, lattice: Lattice): Lattice def propagate(state: BlockState, info: PropagateInfo, lattice: Lattice): Lattice def propagate(s: BlockState, i: PropagateInfo, l: Lattice): Lattice = { lattice.getState(i.targetContext, i.targetBlock) match { case Reachable(targetState) => { if (state != targetState) { Mutability! queue.enqueue(i.targetContext, i.targetBlock); } lattice.putState(i.targetContext, i.targetBlock, targetState.join(s)); } case Unreachable => { queue.enqueue(i.targetContext, i.targetBlock); lattice.putState(i.targetContext, i.targetBlock, s); } } } Limited Mutability Problem: Whenever new flow enters a basicblock it must be added to the solver queue Potential Solution: We could modify all functions to return a pair where the last component is the set of basicblocks that must be enqueued But the stack is deep Solver.Solve -> BlockTransfer.transfer -> BlockTransfer.transferCallBlock -> LatticeOps.functionEntry -> LazyPropagation.functionEntry -> LazyPropagation.propagate • Not feasible to modify all return types • Instead we use a mutable queue! But the stack is still deep! How do we get a reference to the queue??? – We could use a global reference Or we could use Scala's implicits: class BlockTransfer(...)(implicit q: Queue) class LatticeOps(...)(implicit q: Queue) Scaladoc Some of the Bad Stuff • • • • Death Traps Debugging Compiler Warnings Compilation Times Death Trap case class BasicBlock(var successors: Set[BasicBlock]); val a = BasicBlock(Set.empty); a.succesors = Set(a); a == a; Difficult to Debug Cryptic Compiler Warnings Compilation is Slow • Compiling miniTAJS takes 35 seconds – 4500 lines of code – 113 classes + 40 objects = 580 .class files • Why? – Scalac is written in Scala - i.e. it runs on the JVM – Scalac must type-check both Java and Scala – Scalac must do local type inference Functions + Objects Does it work? No, not really (but...) Functions + Objects • Fundamental problem: – Functional Programming = Immutability – Object-orientated Programming = Mutability • Immutable objects are not really objects • Mutating functions are not really functions Functions + Objects A proposed solution: 1. Split the program into FP and OO parts 2. Decide whether some data should be immutable or mutable (i.e. targed for FP or OO programming) 3. Prefer immutable data, otherwise use mutable data Not a silver bullet Recent History • • • • Scala 2.10 Milestone 1 (Januar 2012) New Eclipse Plugin (January 2012) New IntelliJ IDEA Plugin (December 2011) Scala 2.9 (May 2011) – parallel collections • Scala 2.8 (July 2010) – new collections framework Critical Mass? • Introduction to the Art of Programming Using Scala (October 2012) • Scala for the Impatient (March 2012) • Scala in Action (April 2012) • Scala in Depth (April 2012) • Actors in Scala (Januar 2012) • Pro Scala: Monadic Design Patterns for the Web (August 2011) • Programming in Scala 2nd (Januar 2011) Recommended Books Recommended Websites • Official Scala website – http://scala-lang.org/ • Daily Scala – small code sniplets – http://daily-scala.blogspot.com/ • CodeCommit – "Scala for Java Refugees" – http://www.codecommit.com/blog/ • StackOverflow – http://stackoverflow.com/ Summary is viable alternative to Java – object-orientated and functional – has useful features not found in Java – runs on the JVM and interacts with Java – is fun! Thank You! (now go download Scala) Addendum Me> Erik> Me> I need [what turns out to be virtual types] You could use an extra-linguistic solution What do you mean "extra-linguistic"? Erik> A perl script... Last Code Slide: Real Code Embedded DSLs Scala has syntactic flexibility: object Button { def onClick(f: => Unit) { ... } } Button.onClick(() => println("Hello"!)); But you can also write: Button.onClick { println("Hello"); } Historical Anecdote BETA was supposed to be called Scala: For many years the name SCALA was a candidate for a new name – SCALA could mean SCAndinavian LAnguage, and in Latin it means ladder and could be interpreted as meaning something ‘going up’. The When, Why and Why Not of the BETA Programming Language