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関数型プログラミングの世界
- 1. Welcome to the world of the functional programming Kenta Murata 2011.06.11 #osc11doMonday, June 13, 2011 1
- 2. Monday, June 13, 2011 2
- 3. mrkn Ruby Rubyhttp://www.flickr.com/photos/koichiroo/5244581973/Monday, June 13, 2011 3
- 4. Monday, 12010 3 June 13, 2011 4
- 5. Welcome to the world of the functional programming Kenta Murata 2011.06.11 #osc11doMonday, June 13, 2011 5
- 6. Functional ProgrammingMonday, June 13, 2011 6
- 7. Imperative Programming Procedural ProgrammingMonday, June 13, 2011 7
- 8. Fortran Basic Cobol Algol C C++ Java LISPMonday, June 13, 2011 8
- 9. Monday, June 13, 2011 9
- 10. Functional ProgrammingMonday, June 13, 2011 10
- 11. High-order Functions Lazy EvaluationMonday, June 13, 2011 11
- 12. Functions as Building Blocks for constructing programshttp://www.flickr.com/photos/stevendepolo/5597111652Monday, June 13, 2011 12
- 13. Functions as Glue for bonding functionshttp://www.flickr.com/photos/pseudoego/5417919481Monday, June 13, 2011 13
- 14. A lot of programming languages available for functional programminghttp://www.flickr.com/photos/32712959@N07/3222623206Monday, June 13, 2011 14
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- 16. Monday, June 13, 2011 16
- 17. Monday, June 13, 2011 17
- 18. High-order FunctionsMonday, June 13, 2011 18
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- 21. Haskell [ ] e.g. [] [1, 2, 3] (:) e.g. [1] => 1 : [] [1, 2, 3] => 1 : 2 : 3 : []Monday, June 13, 2011 21
- 22. (:) LISP cons cons Haskell cons :: a -> [a] -> [a] -- cons x [] = [x] -- cons x1 (x2:xs) = x1 : (cons x2 xs)Monday, June 13, 2011 22
- 23. cons :: a -> [a] -> [a] -- cons x [] = [x] -- cons x1 (x2:xs) = x1 : (cons x2 xs) // C++ template <typename a> std::list<a> cons(a const& x, std::list<a> const& xs);Monday, June 13, 2011 23
- 24. cons :: a -> [a] -> [a] -- cons x [] = [x] -- cons x1 (x2:xs) = x1 : (cons x2 xs) e.g. cons 0 [1,2,3,4] => x1 0, x2 1, xs [2,3,4]Monday, June 13, 2011 24
- 25. (Int) sum sum :: [Int] -> Int sum [] = 0 sum (n:ns) = n + (sum ns)Monday, June 13, 2011 25
- 26. cons sum cons :: a -> [a] -> [a] cons x [] = [x] cons x1 (x2:xs) = x1 : (cons x2 xs) sum :: [Int] -> Int sum [] = 0 sum (n:ns) = n + (sum ns)Monday, June 13, 2011 26
- 27. cons x [] = [x] sum [] = 0 cons x1 (x2:xs) = x1 : (cons x2 xs) sum (n :ns) = n + (sum ns)Monday, June 13, 2011 27
- 28. (Int) product product :: [Int] -> Int product [] = 1 product (n:ns) = n * product nsMonday, June 13, 2011 28
- 29. cons x [] = [x] sum [] = 0 product [] = 1 cons x1 (x2:xs) = x1 : (cons x2 xs) sum (n :ns) = n + (sum ns) product (n :ns) = n * (product ns)Monday, June 13, 2011 29
- 30. (Bool) allTrue allTrue :: [Bool] -> Bool allTrue [] = True allTrue (b:bs) = b && allTrue nsMonday, June 13, 2011 30
- 31. (Bool) anyTrue anyTrue :: [Bool] -> Bool anyTrue [] = False anyTrue (b:bs) = b || anyTrue nsMonday, June 13, 2011 31
- 32. cons x [] = [x] sum [] = 0 product [] = 1 allTrue [] = True anyTrue [] = False cons x1 (x2:xs) = x1 : (cons x2 xs) sum (n :ns) = n + (sum ns) product (n :ns) = n * (product ns) allTrue (b :bs) = b && (allTrue bs) anyTrue (b :bs) = b || (anyTrue bs)Monday, June 13, 2011 32
- 33. cons x [] = [x] sum [] = 0 product [] = 1 allTrue [] = True anyTrue [] = False cons x1 (x2:xs) = x1 : (cons x2 xs) sum (n :ns) = n + (sum ns) product (n :ns) = n * (product ns) allTrue (b :bs) = b && (allTrue bs) anyTrue (b :bs) = b || (anyTrue bs)Monday, June 13, 2011 32
- 34. reduce :: (a -> [a] -> a) -> a -> [a] -> a reduce f x0 [] = x0 reduce f x0 (x1:xs) = f x1 (reduce f x0 xs) sum = reduce (+) 0 product = reduce (*) 1 allTrue = reduce (&&) True anyTrue = reduce (||) FalseMonday, June 13, 2011 33
- 35. reduce :: (a -> [a] -> a) -> a -> [a] -> a reduce f x0 [] = x0 reduce f x0 (x1:xs) = f x1 (reduce f x0 xs) sum = reduce (+) 0 product = reduce (*) 1 allTrue = reduce (&&) True anyTrue = reduce (||) FalseMonday, June 13, 2011 33
- 36. reduce :: (a -> [a] -> a) -> a -> [a] -> a reduce f x0 [] = x0 reduce f x0 (x1:xs) = f x1 (reduce f x0 xs) sum = reduce (+) 0 product = reduce (*) 1 allTrue = reduce (&&) True anyTrue = reduce (||) FalseMonday, June 13, 2011 33
- 37. reduce :: (a -> [a] -> a) -> a -> [a] -> a reduce f x0 [] = x0 reduce f x0 (x1:xs) = f x1 (reduce f x0 xs) sum = reduce (+) 0 product = reduce (*) 1 allTrue = reduce (&&) True anyTrue = reduce (||) FalseMonday, June 13, 2011 33
- 38. cons reduce append :: [a] -> [a] -> [a] append xs ys = reduce (:) ys xs append [1,2] [3,4] -> reduce (:) [3,4] [1,2] -> reduce (:) [3,4] (1:2:[]) -> 1 : (reduce (:) [3,4] (2:[])) -> 1 : 2 : (reduce (:) [3,4] []) -> 1 : 2 : [3,4] -> [1,2,3,4]Monday, June 13, 2011 34
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- 42. Functions as Building Blocks for constructing programshttp://www.flickr.com/photos/stevendepolo/5597111652Monday, June 13, 2011 38
- 43. Functions as Glue for bonding functionshttp://www.flickr.com/photos/pseudoego/5417919481Monday, June 13, 2011 39
- 44. Monday, June 13, 2011 40
- 45. -- Haskell reduce (+) 0 [1..10] // C++ int ns[] = {1,2,3,4,5,6,7,8,9,10}; std::accumulate(ns, ns + 10, 0, &std::plus<int>); # Ruby [*1..10].inject(0, :+)Monday, June 13, 2011 41
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- 47. Lazy EvaluationMonday, June 13, 2011 43
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- 49. Monday, June 13, 2011 45
- 50. http://www.sampou.org/haskell/article/whyfp.htmlMonday, June 13, 2011 46
- 51. http://www.infoq.com/interviews/john-hughes-fpMonday, June 13, 2011 47
- 52. http://weblog.raganwald.com/2007/03/why-why-functional-programming-matters.htmlMonday, June 13, 2011 48
- 53. language evaluation pureness Haskell lazy pure Concurrent Clean lazy pure OCaml strict impure F# strict impure Scheme strict impureMonday, June 13, 2011 49
- 54. language evaluation pureness Haskell lazy pure Concurrent Clean lazy pure OCaml strict impure F# strict impure Scheme strict impureMonday, June 13, 2011 50
- 55. Monday, June 13, 2011 51
- 56. Monday, 12010 3 June 13, 2011 52
- 57. Functional ProgrammingMonday, June 13, 2011 53
- 58. A lot of programming languages available for functional programminghttp://www.flickr.com/photos/32712959@N07/3222623206Monday, June 13, 2011 54
- 59. Monday, June 13, 2011 55
- 60. High-order FunctionsMonday, June 13, 2011 56
- 61. Functions as Building Blocks for constructing programshttp://www.flickr.com/photos/stevendepolo/5597111652Monday, June 13, 2011 57
- 62. Functions as Glue for bonding functionshttp://www.flickr.com/photos/pseudoego/5417919481Monday, June 13, 2011 58
- 63. Lazy EvaluationMonday, June 13, 2011 59
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末尾呼び出しの最適化は処理系の実装の問題ですから関数型’言語’の必須機能ではないです。評価機の問題です。
関数型プログラミングで必要となる機能はスライドに書いてあるように、高階関数と遅延評価です。だから、私はこの二つを自然に扱える言語という意味で LISP を関数型言語だと考えていないし、スライドでもそのように分類していません。
あくまでも私の解釈ですから、渡邊さんは御自身のご理解の下で御自由に解釈してください。
素のLISPとは何をさしているのでしょうか？
> ただし、LISP方言の一種である Scheme は末尾呼び出し最適化と遅延評価の機能が仕様化されていますから、最後の方の言語比較表では関数型言語として扱っています。
つまり、末尾呼び出し最適化と遅延評価の機能があるものを関数型言語と呼ぶということでしょうか？
ただし、LISP方言の一種である Scheme は末尾呼び出し最適化と遅延評価の機能が仕様化されていますから、最後の方の言語比較表では関数型言語として扱っています。
マルチパラダイム言語なので、確かに手続き型の特徴を併せ持ちますが、手続き型と関数型のどちらかに振り分けるとしたら関数型言語に分類される言語だと思うのです。
たとえばJonesらはその論文[1]の中で'Some mostly-functional languages, such as Lisp or SML.'と言うようにLISPが関数型言語であることを示唆していたりしますが。
[1] Simon L Peyton Jones, Philip Wadler, Imperative functional programming. 1992.