Slides from Eric Bowman's talk at the Dutch Scala Enthusiast's (DUSE) meeting at Tomtom HQ in Amsterdam, 26 May 2010.

1. Scala @ TomTom Eric Bowman eric.bowman@tomtom.com 26 May 2010

2. What’s He Building In There? Not just PNDs Traffic Services Location Services Address & Local Search Tons of Data -> Tons of Analysis Deep Commitment to Server-Side Java 2

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6. 40 reams of paper

7. 5 laptops

8. 8 keyboards

9. 1 back operation

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13. Sorting (sort merge remove-duplicates)

14. Filtering (remove remove-if mapcan)

15. Mapping (map mapcarmapc)

16. Combining (reduce mapcan)

18. Self-documenting

19. Easy to understand

20. Often reusable

21. Usually efficient” From Peter Norvig’sTutorial on Good Lisp Programming Style, 1993 (http://www.norvig.com/luv-slides.ps)

22. But... “Lisp is good for: Exploratory programming Rapid prototyping Minimizing time-to-market Single-programmer (or single-digit team) projects Source-to-source or data-to-data transformation” (ibid.) 9

23. I Like Static types Refactoring Tools Lazy Sundays Paying Some Kid To Cut The Grass Spreadsheets Not Flying The Plane 10

24. What is this Scala thing? 11

25. Scala Is... An escaped research language from EPFL targeting JVM and CLR Object-oriented and functional Statically typed Lisp, ML, Haskell, Erlang, etc. DSL-friendly 12

26. Bi-Scalar Disorder 13

27. Functional Programming? Functions as first class objects Immutability Closures Binding free variables to enclosing lexical scope Higher-order Functions functions as input and/or output A different set of idioms... 14

28. Keep Back for (int i = 1; i <= 256; i++) { if (array[i-1] == ... 15

29. LOLCrash 16

30. Idioms Reduce cognitive overhead Reduce bugs Make intention clear Mini-Patterns 17

31. Java Idioms ++C++ No more 0xDEADBEEF Leads to lots of loops and copies, if you’re doing it right Hard programs get complex doing common things Nested loops begin to look Harmful... 18

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33. For Comprehensions for(inti=0; i<100; i++) { ... } for (i <- 0 until 100) { ... /* do something with i */ } (0.until(100)).foreach(i => /* something with i */) 20

34. For Comprehensions Lists algorithmic “sweet spot” Syntactic Sugar for: foreach map filter flatMap 21

35. The Easy Ones for (i <- 1 to 6) yield i * 2 (1 to 6).map(_ * 2) (2,4,6,8,10,12) for (i <- 1 to 6 if i % 2 == 0) yield i (1 to 6).filter(_ % 2 == 0) (2,4,6) for (i <- 1 to 6) { println(i + “ “) } (1 to 6).foreach { i => print(i + “ “) } 1 2 3 4 5 6 22

36. A Harder One... List<Integer> array = new ArrayList<Integer>(); for (i = 1; i <= 3; i++) { for (j = i; j <= 3; j++) { array.add(j); } } System.out.println(array); [1, 2, 3, 2, 3, 3] for (i <- 1 to 3; j <- i to 3) yield j (1, 2, 3, 2, 3, 3) (1 to 3).flatMap(i => (i to 3).map(j => j)) 23

37. flatMap Subtle thing... “Applies the given function f to each element, then concatenates the results” Turns a list of lists into a list List(List(1,2,3), List(4,5,6)).flatMap(x => x) List(1, 2, 3, 4, 5, 6) List(“tom”, “tom”).flatMap(_.capitalize).mkString TomTom “Special sauce” for nested looping constructs (Equivalent to Haskell’s monadic “bind”) 24

38. IteratorIterator package org.hyperic.sigar.util; public static class IteratorIteratorimplements java.util.Iterator { private java.util.ArrayListiterators; public IteratorIterator() {} public void add(java.util.Iteratoriterator) {} public booleanhasNext() {} public java.lang.Object next() {} public void remove() {} } 25

39. flatMapflatMap def foo(arg: Iterable[Int]) { ... Do something with arg } val some: Iterable[Int] = getSomeIterable foo(some) val more: Iterable[Int] = getMore foo(List(some, more).flatMap(x => x)) 26

40. Real-Life Example “mntstamarg” Each term has aliases Need all permutations 27

41. Java Version static List<String> aliasReplace(String place) { String[] bits = nospaces.split(place); List<String> result = new ArrayList<String>(); List<StringBuilder> allAliases = new ArrayList<StringBuilder>(); for (String bit : bits) { String[] ales = aliases.get(bit); if (ales != null) { if (allAliases.size() == 0) { allAliases.add(new StringBuilder(bit)); for (String alias : ales) { allAliases.add(new StringBuilder(alias)); } } else { List<StringBuilder> clones = new ArrayList<StringBuilder>(); for (StringBuilder a : allAliases) { clones.add(new StringBuilder(a).append(" ").append( bit)); for (String alias : ales) { clones.add(new StringBuilder(a).append(" ").append( alias)); } } allAliases = clones; } } else { if (allAliases.size() == 0) { allAliases.add(new StringBuilder(bit)); } else { for (StringBuilder b : allAliases) { b.append(" ").append(bit); } } } } for (StringBuildermunge: allAliases) { result.add(munge.toString()); } return result; } 28

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43. Scala Version def alias(query: String, aliases: String => List[String]): List[String] = { def recurse(prefix: List[String], remainder: List[String]): List[List[String]] = { remainder match { case Nil => prefix :: Nil case head :: tail => aliases(head).flatMap(term => recurse(term :: prefix, tail)) } recurse(Nil,query.split(“s”).toList.reverse).map( _.mkString(“ “)) } 30

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45. Yeah yeahyeah but “Perl Whitespace Law” “Each line of perl should be surrounded by whitespace equivalent to what it would take to achieve the same functionality in a normal programming language.” -- Don Hopkins If it compiles, it nearly works. Really. Visual Plane-Oriented Programming I ♥ Idioms “But in Java, each little part is so very simple...” 32

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47. Discovering Fire 34

48. “Weak developers will move heaven and earth to do the wrong thing. You can’t limit the damage they do by locking up the sharp tools. They’ll just swing the blunt tools harder.” – Glenn Vandenburg 35

49. @TomTom Testing Middleware “Smart Content Switch” We needed it quickly... B2B/B2G Traffic Query Engine Clustering Algorithm DSL Templating Engine Content Cleanup Next-Generation Geocoder 36

50. How To Sneak It In Start with Testing ScalaCheckIS AWESOME. Specs, ScalaTest testing DSLs Start with something low risk Ok, well, we didn’t do that Prepare for steep learning curve ...followed by a productivity hockey stick 37

51. Another Example 8000 lines of broken Java -> 400 lines of broken Scala -> hyp.take(1).flatMap(_.dropDistricts) match { case Nil => hyp case head => { hyp.tail.foldLeft(head) { case (run: List[Hypothesis], h: Hypothesis) => { run.flatMap(_.merge(h)) match { case Nil => run case newRun => newRun.removeDuplicates } } } } } *Includes suggested improvements by Martin Odersky, I hope 38

52. Testing Functional architect wrote a bunch of test cases, like: Requirement R.17: D1 -> N1, L1 -> N1, N1, D2 -> L2, L3, N3, D3 should cluster as (L1,N1,D1), (L2,D2), (L3), (N3), (D3) Vim-macro’d into: it should “satisfy R.17” in { cluster(D1 -> N1,L1 -> N1,N1,D2 -> L2,L3,N3,D3) should equal { groups(group(L1,N1,D1),group(L2,D2),group(L3),group(N3), group(D3))) } 39

53. ScalaCheck The Dog’s Bollocks Steep Learning Curve object BinarySpecification extends Properties(“bin”) { specify(“toBinary”, Prop.forAllNoShrink( for{n <- Gen.choose(0d, 0.99999999d) m <- Gen.choose(20,31) } yield Pair(n, m)) { p => Math.abs(toDecimal(toBinary(p._1, p._2)) – p._1 < 1e-10 })} 40

54. So little time... Traits Case classes Pattern matching Structural types Self types XML Option Covariance/Contravariance @specialized 41

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