Emacs ML let start ::= exp (1) exp ::= (2) fn id exp (3) ::= (4) (5) ::= id (6) const (7) (exp) (8) let val id = exp in

Size: px
Start display at page:

Download "Emacs ML let start ::= exp (1) exp ::= (2) fn id exp (3) ::= (4) (5) ::= id (6) const (7) (exp) (8) let val id = exp in"

Transcription

1 Emacs, Eclipse Visual Studio Standard ML Haskell Emacs 1 Eclipse Visual Studio variable not found LR(1) let Emacs Emacs Emacs Java Emacs JDEE [3] JDEE Emacs Java

2 Emacs ML let start ::= exp (1) exp ::= (2) fn id exp (3) ::= (4) (5) ::= id (6) const (7) (exp) (8) let val id = exp in exp end (9) 2 r6, r7 (1) (3) (5) (6) (7) (8) (9) (2) (4) let val x = 1 in let val y = fn x => fn y => x y in let val z = fn x => x in y x y y ( end let x, y, z x : int y : α, β. (α β) α β z : α. α α

3 y y z 2 x y z 2 3 EOF let, id, val, in, end, =,, fn, (, ), const, EOF id const id x const 2 EOF id id EOF id cursor 1 let id id EOF EOF id 1 let val x = 2 in x let, val, id x, =, exp, in, 1 1 cursor id cursor

4 id const fn ( ) let val = in end EOF 0 s15 r6 s16 r7 s6 s1 s7 1 s15 r6 s16 r7 s6 s1 s7 2 s15 r6 s16 r7 s6 s1 s7 3 s15 r6 s16 r7 s6 s1 s7 4 s15 r6 s16 r7 s6 s1 s7 5 s15 r6 s16 r7 r2 r2 s1 r2 s7 r2 r2 r2 r2 r2 6 s9 7 s11 8 acc 9 s2 10 s20 r8 11 s12 12 s3 13 s4 14 s22 r9 15 r6 r6 r6 r6 r6 r6 r6 r6 r6 r6 r6 r6 16 r7 r7 r7 r7 r7 r7 r7 r7 r7 r7 r7 r7 17 r1 r1 r1 r1 r1 r1 r1 r1 r1 r1 r1 r1 18 r4 r4 r4 r4 r4 r4 r4 r4 r4 r4 r4 r4 19 r5 r5 r5 r5 r5 r5 r5 r5 r5 r5 r5 r5 20 r8 r8 r8 r8 r8 r8 r8 r8 r8 r8 r8 r8 21 r3 r3 r3 r3 r3 r3 r3 r3 r3 r3 r3 r3 22 r9 r9 r9 r9 r9 r9 r9 r9 r9 r9 r9 r9 start exp 0 g8 g17 r1 g5 g18 r4 1 g8 g10 g5 g18 r4 2 g8 g21 r3 g5 g18 r4 3 g8 g13 g5 g18 r4 4 g8 g14 g5 g18 r4 5 r2 r2 r2 g19 r r6 r6 r6 r6 16 r7 r7 r7 r7 17 r1 r1 r1 r1 18 r4 r4 r4 r4 19 r5 r5 r5 r5 20 r8 r8 r8 r8 21 r3 r3 r3 r3 22 r9 r9 r9 r9 1.

5 let val id x = exp in id cursor const 2 id x 1. 4 [ ] ( ) id start ::= exp exp ::= fn id exp [ ] ::= ::= id const (exp) let val id = exp in exp end [ ] start,, id id 2 ::= (1) (9) start A ( ɛ ) α s s 1,..., s n (1) s 1 start s 1 start s 1 A α α s 1 α = α 1 s 1 α 2 α 1 α 1 = s i... s 2 α 2 As i+1... s n (2) (1)

6 let val id x = exp in exp const 2 id cursor id x ,5 2 ( 1) ( 2) let, val, id x, =, exp, in, exp 5 ( 3) let, val, id x, =, exp, in, exp exp exp 2 exp exp end ( 2) 9 let exp exp exp 1 4 start

7 let val id x = exp in [ ] const 2 id cursor id x start exp exp exp const 2 id cursor id x 4.

8 2 5 5 let val f = fn x => + x 1 in f (f + int int int ) end [ ]( ) ) end 5 4 e ::= x c cursor e e λx. e let x = e in e [ ] x c e λ, let Milner W [7] 5 U Cls Γ τ τ Γ σ := α 1... α n.τ τ := int α τ τ σ τ int τ := int α (τ τ) subst (S, τ) = τ := int (τ int ) τ := S(τ) (τ α ) subst(s, τ 1 ); subst(s, τ 2 ) (τ τ 1 τ 2 )

9 C(Γ, e) = cursortype := nil; cursorenv := Γ; C (Γ, e); return (cursortype, cursorenv) C (Γ, cursor) = cursortype := β; (β fresh) cursorenv := Γ; return cursortype C (Γ, x) = Γ(x) = α 1... α n.τ 1 return [β 1 /α 1 ]... [β n /α n ]τ 1 (β 1,..., β n fresh) Γ(x) = τ 1 return τ 1 C (Γ, c) = return int C (Γ, e 1 e 2 ) = τ 1 = C (Γ, e 1 ); τ 2 = C (Γ, e 2 ); S = U(τ 1, (τ 2 β)); (β fresh) subst(s, τ 1 ); subst(s, τ 2 ); return S(β) C (Γ, λx.e) = τ 1 = C (Γ{x : β}, e); (β fresh) return ( β τ 1 ) C (Γ, let x = e 1 in e 2 ) = τ 1 = C (Γ, e 1 ); σ = Cls(Γ, τ 1 ); return C (Γ{x : σ}, e 2 ) C (Γ, [ ]) = return β (β fresh) 5. C 6 5 C τ 1 β 1... β n. τ 2 τ 1 τ 2 = [α 1/β 1 ] [α n /β n ]τ 2 (α 1,..., α n fresh) U (τ 1, τ 2 ) let val ya = fn x => x in let val xb = fn x => x in let val xc = 1 in (fn x => x 1) x end 3 ya, xb, xc cursor : int α ya : γ. γ γ xb : γ. γ γ xc : int 3 ya xb xc xc ya xb x xb

10 7 Emacs[2] Emacs lambdamode lambda-mode web ( jp/complement/) 6 lambda-mode auto-complete.el [1] Emacs auto-complete.el 1 6 Emacs 6. auto-complete auto-complete lambda-mode auto-complete id const int +, -, /, * Emacs Lisp yacc kmyacc[4] EOF (1) start acc (2) s 1 start s 1

11 (3) s 1 s 2 s 1 s 2 (4) (2) s 2 (4-a) s 1 s 2 (2) (5) (2) s 2 (5-a) 1 s 1 1 s 1 = s (1) 1 s 1 2 s 2 (2) 1 s 1 2 s 2 acc (3) 1 s 1 2 s 2 s 1 s 1 (3-a) (4) (1) auto-complete.el Emacs lisp max-lisp-eval-depth maxspecpdl-size 400, 1000 lambda-mode lambda-mode 7 lambda-mode Emacs OS Windows XP Professional SP3 CPU Intel Core 2 Duo E GHz 3.25GByte Emacs Meadow(GNU Emacs )

12 7. lambda-mode

13 2 id const fn ( ) let val = in end start acc acc acc acc acc acc acc acc acc acc acc acc exp ,2 5,2 5,2 5,2 5,2 5,2 5,2 5,2 5,2 5,2 5,2 5,2 fn id const ( ) let val 9 = 9 in end 2 exp start acc acc acc exp ,2 5,2 5,2 5 fn id const ( ) 8 let val = in 9 end 9 2.

14 8 let Aditya [6] Haskell ML annotation [1] EmacsWiki: Auto complete. [2] GNU Emacs. [3] Java development environment for Emacs. [4] kmyacc. [5] Shail Aditya and Rishiyur S. Nikhil. Incremental polymorphism. In Proceedings of the 5th ACM Conference on Functional Programming Languages and Computer Architecture, pages , Cambridge, USA, August [6] Robin Milner. A theory of type polymorphism in programming. Journal of Computer and System Sciences, 17(3): , 1978.

Int Int 29 print Int fmt tostring 2 2 [19] ML ML [19] ML Emacs Standard ML M M ::= x c λx.m M M let x = M in M end (M) x c λx.

Int Int 29 print Int fmt tostring 2 2 [19] ML ML [19] ML Emacs Standard ML M M ::= x c λx.m M M let x = M in M end (M) x c λx. 1, 2 1 m110057@shibaura-it.ac.jp 2 sasano@sic.shibaura-it.ac.jp Eclipse Visual Studio ML Standard ML Emacs 1 ( IDE ) IDE C C++ Java IDE IDE IDE IDE Eclipse Java IDE Java Standard ML 1 print (Int. 1 Int

More information

Jacques Garrigue

Jacques Garrigue Jacques Garrigue Garrigue 1 Garrigue 2 $ print_lines () > for i in $1; do > echo $i > done $ print_lines "a b c" a b c Garrigue 3 Emacs Lisp (defun print-lines (lines) (dolist (str lines) (insert str)

More information

koba/class/soft-kiso/ 1 λ if λx.λy.y false 0 λ typed λ-calculus λ λ 1.1 λ λ, syntax τ (types) ::= b τ 1 τ 2 τ 1

koba/class/soft-kiso/ 1 λ if λx.λy.y false 0 λ typed λ-calculus λ λ 1.1 λ λ, syntax τ (types) ::= b τ 1 τ 2 τ 1 http://www.kb.ecei.tohoku.ac.jp/ koba/class/soft-kiso/ 1 λ if λx.λy.y false 0 λ typed λ-calculus λ λ 1.1 λ 1.1.1 λ, syntax τ (types) ::= b τ 1 τ 2 τ 1 τ 2 M (terms) ::= c τ x M 1 M 2 λx : τ.m (M 1,M 2

More information

O1-1 O1-2 O1-3 O1-4 O1-5 O1-6

O1-1 O1-2 O1-3 O1-4 O1-5 O1-6 O1-1 O1-2 O1-3 O1-4 O1-5 O1-6 O1-7 O1-8 O1-9 O1-10 O1-11 O1-12 O1-13 O1-14 O1-15 O1-16 O1-17 O1-18 O1-19 O1-20 O1-21 O1-22 O1-23 O1-24 O1-25 O1-26 O1-27 O1-28 O1-29 O1-30 O1-31 O1-32 O1-33 O1-34 O1-35

More information

1 911 9001030 9:00 A B C D E F G H I J K L M 1A0900 1B0900 1C0900 1D0900 1E0900 1F0900 1G0900 1H0900 1I0900 1J0900 1K0900 1L0900 1M0900 9:15 1A0915 1B0915 1C0915 1D0915 1E0915 1F0915 1G0915 1H0915 1I0915

More information

ViewSonic Corporation, Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic

ViewSonic Corporation, Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic PJ-PEN-003 IR VS15219 ViewSonic Corporation, 2013. Macintosh Power Macintosh Microsoft Windows Windows ViewSonic 3 OnView ViewMatch ViewMeter ViewSonic ViewSonic, ViewSonic ViewSonic i ViewSonic ViewSonic

More information

1. 1 A : l l : (1) l m (m 3) (2) m (3) n (n 3) (4) A α, β γ α β + γ = 2 m l lm n nα nα = lm. α = lm n. m lm 2β 2β = lm β = lm 2. γ l 2. 3

1. 1 A : l l : (1) l m (m 3) (2) m (3) n (n 3) (4) A α, β γ α β + γ = 2 m l lm n nα nα = lm. α = lm n. m lm 2β 2β = lm β = lm 2. γ l 2. 3 1. 1 A : l l : (1) l m (m 3) (2) m (3) n (n 3) (4) A 2 1 2 1 2 3 α, β γ α β + γ = 2 m l lm n nα nα = lm. α = lm n. m lm 2β 2β = lm β = lm 2. γ l 2. 3 4 P, Q R n = {(x 1, x 2,, x n ) ; x 1, x 2,, x n R}

More information

平成 19 年度 ( 第 29 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 19 ~8 年月 72 月日開催 30 日 ) 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy

平成 19 年度 ( 第 29 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 19 ~8 年月 72 月日開催 30 日 ) 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy 2 N X Y X Y f (x) f x f x y z (( f x) y) z = (( f (x))(y))(z) X Y x e X Y λx. e x x 2 + x + 1 λx. x 2 + x + 1 3 PCF 3.1 PCF PCF

More information

ML λ λ 1 λ 1.1 λ λ λ e (λ ) ::= x ( ) λx.e (λ ) e 1 e 2 ( ) ML λx.e Objective Caml fun x -> e x e let 1

ML λ λ 1 λ 1.1 λ λ λ e (λ ) ::= x ( ) λx.e (λ ) e 1 e 2 ( ) ML λx.e Objective Caml fun x -> e x e let 1 2005 sumii@ecei.tohoku.ac.jp 2005 6 24 ML λ λ 1 λ 1.1 λ λ λ e (λ ) ::= x ( ) λx.e (λ ) e 1 e 2 ( ) ML λx.e Objective Caml fun x -> e x e let 1 let λ 1 let x = e1 in e2 (λx.e 2 )e 1 e 1 x e 2 λ 3 λx.(λy.e)

More information

-1-1 1 1 1 1 12 31 2 2 3 4

-1-1 1 1 1 1 12 31 2 2 3 4 2007 -1-1 1 1 1 1 12 31 2 2 3 4 -2-5 6 CPU 3 Windows98 1 -3-2. 3. -4-4 2 5 1 1 1 -5- 50000 50000 50000 50000 50000 50000 50000 50000 50000 50000-6- -7-1 Windows 2 -8-1 2 3 4 - - 100,000 200,000 500,000

More information

untitled

untitled 16 4 1 17 1 50 -1- -2- -3- -4- -5- -6- -7- 1 2-8- -9- -10- -11- Web -12- (1) (2)(1) (3) (4) (1)()(2) (3)(4) -13- -14- -15- -16- -17- -18- -19- -20- -21- -22- -23- (2)(1) (3) -24- -25- -26- -27- -28- -29-

More information

FileMaker Server Getting Started Guide

FileMaker Server Getting Started Guide FileMaker Server 11 2004-2010 FileMaker, Inc. All Rights Reserved. FileMaker, Inc. 5201 Patrick Henry Drive Santa Clara, California 95054 FileMaker FileMaker, Inc. FileMaker, Inc. FileMaker FileMaker,

More information

imai@eng.kagawa-u.ac.jp No1 No2 OS Wintel Intel x86 CPU No3 No4 8bit=2 8 =256(Byte) 16bit=2 16 =65,536(Byte)=64KB= 6 5 32bit=2 32 =4,294,967,296(Byte)=4GB= 43 64bit=2 64 =18,446,744,073,709,551,615(Byte)=16EB

More information

2 2.1 NPCMJ ( (Santorini, 2010) (NPCMJ, 2016) (1) (, 2016) (1) (2) (1) ( (IP-MAT (CONJ ) (PP (NP (D ) (N )) (P )) (NP-SBJ *

2 2.1 NPCMJ (  (Santorini, 2010) (NPCMJ, 2016) (1) (, 2016) (1) (2) (1) ( (IP-MAT (CONJ ) (PP (NP (D ) (N )) (P )) (NP-SBJ * Emacs Emacs : Emacs 1 Emacs Emacs ( ) (NPCMJ ) 1 Emacs NPCMJ 2 1 2 2.1 NPCMJ (http://npcmj.ninjal.ac.jp/) (Santorini, 2010) (NPCMJ, 2016) (1) (, 2016) (1) (2) (1) ( (IP-MAT (CONJ ) (PP (NP (D ) (N )) (P

More information

Parametric Polymorphism

Parametric Polymorphism ML 2 2011/04/19 Parametric Polymorphism Type Polymorphism ? : val hd_int : int list - > int val hd_bool : bool list - > bool val hd_i_x_b : (int * bool) list - > int * bool etc. let hd_int = function (x

More information

研修コーナー

研修コーナー l l l l l l l l l l l α α β l µ l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l l

More information

SmartLMSユーザーズガイド<講師編>

SmartLMSユーザーズガイド<講師編> SmartLearning Management System SmartLMS (1) (2) (3) (4) (3) (5) Microsoft MS PowerPoint DirectX Windows Windows NT Windows Media Microsoft Corporation Intel Pentium Intel Corporation NEC 2003-2004 NEC

More information

IPSJ SIG Technical Report Vol.2013-CE-119 No /3/15 enpoly enpoly enpoly 1) 2) 2 C Java Bertrand Meyer [1] 1 1 if person greeting()

IPSJ SIG Technical Report Vol.2013-CE-119 No /3/15 enpoly enpoly enpoly 1) 2) 2 C Java Bertrand Meyer [1] 1 1 if person greeting() enpoly enpoly enpoly ) 2) 2 C Java 2 6. Bertrand Meyer [] if person greeting() if person if Faculty of Informatics, Shizuoka University, Hamamatsu, Shizuoka, 432-80, Japan C Jone[2] 2. Java Anchor Garden

More information

LLG-R8.Nisus.pdf

LLG-R8.Nisus.pdf d M d t = γ M H + α M d M d t M γ [ 1/ ( Oe sec) ] α γ γ = gµ B h g g µ B h / π γ g = γ = 1.76 10 [ 7 1/ ( Oe sec) ] α α = λ γ λ λ λ α γ α α H α = γ H ω ω H α α H K K H K / M 1 1 > 0 α 1 M > 0 γ α γ =

More information

shift/reset [13] 2 shift / reset shift reset k call/cc reset shift k shift (...) k 1 + shift(fun k -> 2 * (k 3)) k 2 * (1 + 3) 8 reset shift reset (..

shift/reset [13] 2 shift / reset shift reset k call/cc reset shift k shift (...) k 1 + shift(fun k -> 2 * (k 3)) k 2 * (1 + 3) 8 reset shift reset (.. arisa@pllab.is.ocha.ac.jp asai@is.ocha.ac.jp shift / reset CPS shift / reset CPS CPS 1 [3, 5] goto try/catch raise call/cc [17] control/prompt [8], shift/reset [5] control/prompt, shift/reset call/cc (continuationpassing

More information

導入基礎演習.ppt

導入基礎演習.ppt Multi-paradigm Programming Functional Programming Scheme Haskell ML Scala X10 KL1 Prolog Declarative Lang. C Procedural Lang. Java C++ Python Object-oriented Programming / (root) bin home lib 08 09

More information

LR DEVICE Version 1.1 706434 / 01 04 / 2017 1................................................ 3 1.1............................................... 3 2................................................ 3

More information

untitled

untitled ( 9:: 3:6: (k 3 45 k F m tan 45 k 45 k F m tan S S F m tan( 6.8k tan k F m ( + k tan 373 S S + Σ Σ 3 + Σ os( sin( + Σ sin( os( + sin( os( p z ( γ z + K pzdz γ + K γ K + γ + 9 ( 9 (+ sin( sin { 9 ( } 4

More information

FileMaker Server 9 Getting Started Guide

FileMaker Server 9 Getting Started Guide FileMaker Server 10 2007-2009 FileMaker, Inc. All rights reserved. FileMaker, Inc. 5201 Patrick Henry Drive Santa Clara, California 95054 FileMaker Bento Bento FileMaker, Inc. Mac Mac Apple Inc. FileMaker

More information

., White-Box, White-Box. White-Box.,, White-Box., Maple [11], 2. 1, QE, QE, 1 Redlog [7], QEPCAD [9], SyNRAC [8] 3 QE., 2 Brown White-Box. 3 White-Box

., White-Box, White-Box. White-Box.,, White-Box., Maple [11], 2. 1, QE, QE, 1 Redlog [7], QEPCAD [9], SyNRAC [8] 3 QE., 2 Brown White-Box. 3 White-Box White-Box Takayuki Kunihiro Graduate School of Pure and Applied Sciences, University of Tsukuba Hidenao Iwane ( ) / Fujitsu Laboratories Ltd. / National Institute of Informatics. Yumi Wada Graduate School

More information

u Θ u u u ( λ + ) v Θ v v v ( λ + ) (.) Θ ( λ + ) (.) u + + v (.),, S ( λ + ) uv,, S uv, SH (.8) (.8) S S (.9),

u Θ u u u ( λ + ) v Θ v v v ( λ + ) (.) Θ ( λ + ) (.) u + + v (.),, S ( λ + ) uv,, S uv, SH (.8) (.8) S S (.9), ML rgr ML ML ML (,, ) σ τ τ u + + τ σ τ v + + τ τ σ + + (.) uv,,,, σ, σ, σ, τ, τ, τ t (Hook) σ λθ + ε, τ γ σ λθ + ε, τ γ σ λθ + ε, τ γ λ, E ν ν λ E, E ( + ν)( ν) ( + ν) Θ Θ ε + ε + ε (.) ε, ε, ε, γ, γ,

More information

PC Development of Distributed PC Grid System,,,, Junji Umemoto, Hiroyuki Ebara, Katsumi Onishi, Hiroaki Morikawa, and Bunryu U PC WAN PC PC WAN PC 1 P

PC Development of Distributed PC Grid System,,,, Junji Umemoto, Hiroyuki Ebara, Katsumi Onishi, Hiroaki Morikawa, and Bunryu U PC WAN PC PC WAN PC 1 P PC Development of Distributed PC Grid System,,,, Junji Umemoto, Hiroyuki Ebara, Katsumi Onishi, Hiroaki Morikawa, and Bunryu U PC WAN PC PC WAN PC 1 PC PC PC PC PC Key Words:Grid, PC Cluster, Distributed

More information

InterSafe Personal_v2.3 ユーザーズガイド_初版

InterSafe Personal_v2.3 ユーザーズガイド_初版 InterSafe Personal v2.3 1. 3 1-1. 4 1-2. 5 InterSafe Personal 5 1-3. InterSafe Personal 6 6 7 8 2. 9 2-1. 10 2-2. 14 2-3. 17 17 17 2 18 19 21 3. 22 3-1. 23 23 3-2. [ ] 24 [ ] 24 [ ] 24 3-3. [ ] 25 [ ]

More information

FileMaker Server 9 Getting Started Guide

FileMaker Server 9 Getting Started Guide FileMaker Server 9 2007 FileMaker, Inc. All Rights Reserved. FileMaker, Inc. 5201 Patrick Henry Drive Santa Clara, California 95054 FileMaker FileMaker, Inc. ScriptMaker FileMaker, Inc. FileMaker FileMaker,

More information

y = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' =

y = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' = y x = α + β + ε =,, ε V( ε) = E( ε ) = σ α $ $ β w ( 0) σ = w σ σ y α x ε = + β + w w w w ε / w ( w y x α β ) = α$ $ W = yw βwxw $β = W ( W) ( W)( W) w x x w x x y y = = x W y W x y x y xw = y W = w w

More information

. IDE JIVE[1][] Eclipse Java ( 1) Java Platform Debugger Architecture [5] 3. Eclipse GUI JIVE 3.1 Eclipse ( ) 1 JIVE Java [3] IDE c 016 Information Pr

. IDE JIVE[1][] Eclipse Java ( 1) Java Platform Debugger Architecture [5] 3. Eclipse GUI JIVE 3.1 Eclipse ( ) 1 JIVE Java [3] IDE c 016 Information Pr Eclipse 1,a) 1,b) 1,c) ( IDE) IDE Graphical User Interface( GUI) GUI GUI IDE View Eclipse Development of Eclipse Plug-in to present an Object Diagram to Debug Environment Kubota Yoshihiko 1,a) Yamazaki

More information

第86回日本感染症学会総会学術集会後抄録(I)

第86回日本感染症学会総会学術集会後抄録(I) κ κ κ κ κ κ μ μ β β β γ α α β β γ α β α α α γ α β β γ μ β β μ μ α ββ β β β β β β β β β β β β β β β β β β γ β μ μ μ μμ μ μ μ μ β β μ μ μ μ μ μ μ μ μ μ μ μ μ μ β

More information

2012 M

2012 M 2012 M0109218 2012 : M0109218 36 1 1 1.1............................. 1 1.2................................. 5 2 6 2.1................... 6 2.2................ 8 2.3............ 12 3 15 3.1...................

More information

compact compact Hermann compact Hermite ( - ) Hermann Hermann ( ) compact Hermite Lagrange compact Hermite ( ) a, Σ a {0} a 3 1

compact compact Hermann compact Hermite ( - ) Hermann Hermann ( ) compact Hermite Lagrange compact Hermite ( ) a, Σ a {0} a 3 1 014 5 4 compact compact Hermann compact Hermite ( - ) Hermann Hermann ( ) compact Hermite Lagrange compact Hermite ( ) 1 1.1. a, Σ a {0} a 3 1 (1) a = span(σ). () α, β Σ s α β := β α,β α α Σ. (3) α, β

More information

5 IO Haskell return (>>=) Haskell Haskell Haskell 5.1 Util Util (Util: Tiny Imperative Language) 1 UtilErr, UtilST, UtilCont, Haskell C

5 IO Haskell return (>>=) Haskell Haskell Haskell 5.1 Util Util (Util: Tiny Imperative Language) 1 UtilErr, UtilST, UtilCont, Haskell C 5 IO Haskell return (>>=) Haskell Haskell Haskell 5.1 Util Util (Util: Tiny Imperative Language) 1 UtilErr, UtilST, UtilCont,... 5.1.1 5.1.2 Haskell C LR ( ) 1 (recursive acronym) PHP, GNU V - 1 5.1.1

More information

…J…−†[†E…n…‘†[…hfi¯„^‚ΛžfiüŒå

…J…−†[†E…n…‘†[…hfi¯„^‚ΛžfiüŒå takuro.onishi@gmail.com II 2009 6 11 [A] D B A B A B A B DVD y = 2x + 5 x = 3 y = 11 x = 5 y = 15. Google Web (2 + 3) 5 25 2 3 5 25 Windows Media Player Media Player (typed lambda calculus) (computer

More information

プログラミングD - Java

プログラミングD - Java プログラミング D 講義資料 中田明夫 nakata@ist.osaka-u.ac.jp ML 教科書 プログラミング言語 Standard ML 入門 :1,2 章 講義のねらい 関数型プログラムを知る 関数型プログラムを知る利点 プログラムを統一的, 抽象的に捕らえる リスト処理, 高階関数, 再帰関数定義 リストやツリーなどのデータ構造は再帰的に定義 再帰関数で扱うとプログラミングが容易 数学的な裏付け

More information

3 3.1 algebraic datatype data k = 1 1,1... 1,n1 2 2,1... 2,n2... m m,1... m,nm 1 m m m,1,..., m,nm m 1, 2,..., k 1 data Foo x y = Alice x [y] B

3 3.1 algebraic datatype data k = 1 1,1... 1,n1 2 2,1... 2,n2... m m,1... m,nm 1 m m m,1,..., m,nm m 1, 2,..., k 1 data Foo x y = Alice x [y] B 3 3.1 algebraic datatype data 1 2... k = 1 1,1... 1,n1 2 2,1... 2,n2... m m,1... m,nm 1 m m m,1,..., m,nm m 1, 2,..., k 1 data Foo x y = Alice x [y] Bob String y Charlie Foo Double Integer Alice 3.14 [1,2],

More information

平成 28 年度 ( 第 38 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 ~8 28 月年 48 日開催月 1 日 semantics FB 1 x, y, z,... FB 1. FB (Boolean) Functional

平成 28 年度 ( 第 38 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 ~8 28 月年 48 日開催月 1 日 semantics FB 1 x, y, z,... FB 1. FB (Boolean) Functional 1 1.1 semantics F 1 x, y, z,... F 1. F 38 2016 9 1 (oolean) Functional 2. T F F 3. P F (not P ) F 4. P 1 P 2 F (P 1 and P 2 ) F 5. x P 1 P 2 F (let x be P 1 in P 2 ) F 6. F syntax F (let x be (T and y)

More information

106 4 4.1 1 25.1 25.4 20.4 17.9 21.2 23.1 26.2 1 24 12 14 18 36 42 24 10 5 15 120 30 15 20 10 25 35 20 18 30 12 4.1 7 min. z = 602.5x 1 + 305.0x 2 + 2

106 4 4.1 1 25.1 25.4 20.4 17.9 21.2 23.1 26.2 1 24 12 14 18 36 42 24 10 5 15 120 30 15 20 10 25 35 20 18 30 12 4.1 7 min. z = 602.5x 1 + 305.0x 2 + 2 105 4 0 1? 1 LP 0 1 4.1 4.1.1 (intger programming problem) 1 0.5 x 1 = 447.7 448 / / 2 1.1.2 1. 2. 1000 3. 40 4. 20 106 4 4.1 1 25.1 25.4 20.4 17.9 21.2 23.1 26.2 1 24 12 14 18 36 42 24 10 5 15 120 30

More information

連載講座 : 高生産並列言語を使いこなす (4) ゲーム木探索の並列化 田浦健次朗 東京大学大学院情報理工学系研究科, 情報基盤センター 目次 1 準備 問題の定義 αβ 法 16 2 αβ 法の並列化 概要 Young Brothers Wa

連載講座 : 高生産並列言語を使いこなす (4) ゲーム木探索の並列化 田浦健次朗 東京大学大学院情報理工学系研究科, 情報基盤センター 目次 1 準備 問題の定義 αβ 法 16 2 αβ 法の並列化 概要 Young Brothers Wa 連載講座 : 高生産並列言語を使いこなす (4) ゲーム木探索の並列化 田浦健次朗 東京大学大学院情報理工学系研究科, 情報基盤センター 目次 1 準備 16 1.1 問題の定義 16 1.2 αβ 法 16 2 αβ 法の並列化 17 2.1 概要 17 2.2 Young Brothers Wait Concept 17 2.3 段数による逐次化 18 2.4 適応的な待機 18 2. 強制終了

More information

( ) ( ) ( ) 2

( ) ( ) ( ) 2 (Basic Theory of Information Processing) 1 1 1.1 - - ( ) ( ) ( ) 2 Engineering Transformation or ( ) Military Transformation ( ) ( ) ( ) HDTV 3 ( ) or ( ) 4 5.609 (TSUBAME2.5, 11 (2014.6)) IP ( ) ( ) (

More information

July 28, H H 0 H int = H H 0 H int = H int (x)d 3 x Schrödinger Picture Ψ(t) S =e iht Ψ H O S Heisenberg Picture Ψ H O H (t) =e iht O S e i

July 28, H H 0 H int = H H 0 H int = H int (x)d 3 x Schrödinger Picture Ψ(t) S =e iht Ψ H O S Heisenberg Picture Ψ H O H (t) =e iht O S e i July 8, 4. H H H int H H H int H int (x)d 3 x Schrödinger Picture Ψ(t) S e iht Ψ H O S Heisenberg Picture Ψ H O H (t) e iht O S e iht Interaction Picture Ψ(t) D e iht Ψ(t) S O D (t) e iht O S e ih t (Dirac

More information

振動工学に基礎

振動工学に基礎 Ky Words. ω. ω.3 osω snω.4 ω snω ω osω.5 .6 ω osω snω.7 ω ω ( sn( ω φ.7 ( ω os( ω φ.8 ω ( ω sn( ω φ.9 ω anφ / ω ω φ ω T ω T s π T π. ω Hz ω. T π π rad/s π ω π T. T ω φ 6. 6. 4. 4... -... -. -4. -4. -6.

More information

2 ID POS 1... 1 2... 2 2.1 ID POS... 2 2.2... 3 3... 5 3.1... 5 3.2... 6 3.2.1... 6 3.2.2... 7 3.3... 7 3.3.1... 7 3.3.2... 8 3.3.3... 8 3.4... 9 4... 11 4.1... 11 4.2... 15 4.3... 27 5... 35... 36...

More information

0 1 1 @master q 3 1.1.......................................... 3 1.2....................................... 4 1.3....................................

0 1 1 @master q 3 1.1.......................................... 3 1.2....................................... 4 1.3.................................... 1 0!? Q.? A. Q. B. Q.? A.! 2 10 6 Scheme 80! λ 81!? λ ( ) 82!? λ ( ) 83!? λ 4 3! λ 0 1 1 @master q 3 1.1.......................................... 3 1.2....................................... 4 1.3............................................

More information

zsj2017 (Toyama) program.pdf

zsj2017 (Toyama) program.pdf 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

_170825_<52D5><7269><5B66><4F1A>_<6821><4E86><5F8C><4FEE><6B63>_<518A><5B50><4F53><FF08><5168><9801><FF09>.pdf

_170825_<52D5><7269><5B66><4F1A>_<6821><4E86><5F8C><4FEE><6B63>_<518A><5B50><4F53><FF08><5168><9801><FF09>.pdf 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

untitled

untitled 1 2 ...1 ...1...3...4...4...4...5...7...10 3-1...10 3-2...10 3-3...11 3-4 Windows2000 / XP...11 3-5 PC...13...14 4-1 SYSTEM...14 4-2 DISPLAY...15...17...20...22...23...24...25...25...25...25...26...28

More information

hotspot の特定と最適化

hotspot の特定と最適化 1 1? 1 1 2 1. hotspot : hotspot hotspot Parallel Amplifier 1? 2. hotspot : (1 ) Parallel Composer 1 Microsoft* Ticker Tape Smoke 1.0 PiSolver 66 / 64 / 2.76 ** 84 / 27% ** 75 / 17% ** 1.46 89% Microsoft*

More information

r3.dvi

r3.dvi 2012 3 / Lisp(2) 2012.4.19 1 Lisp 1.1 Lisp Lisp (1) (setq) (2) (3) setq defun (defun (... &aux...)...) ( ) ( nil ) [1]> (defun sisoku (x y &aux wa sa sho seki) (setq wa (+ x y)) (setq sa (- x y)) (setq

More information

( ) ( ) lex LL(1) LL(1)

( ) ( ) lex LL(1) LL(1) () () lex LL(1) LL(1) http://www.cs.info.mie-u.ac.jp/~toshi/lectures/compiler/ 29 5 14 1 1 () / (front end) (back end) (phase) (pass) 1 2 1 () () var left, right; fun int main() { left = 0; right = 10;

More information

TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit

TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit 28 29 2 16 TaskPit TaskPit TaskPit TaskPit 3 TaskPit Windows OS PC CPU 2 TaskPit TaskPit Windows OS CPU 1 10 TaskPit 1 3 2 4 3 6 3.1............... 6 3.2............................... 6 3.3...............................

More information

# let rec sigma (f, n) = # if n = 0 then 0 else f n + sigma (f, n-1);; val sigma : (int -> int) * int -> int = <fun> sigma f n ( : * -> * ) sqsum cbsu

# let rec sigma (f, n) = # if n = 0 then 0 else f n + sigma (f, n-1);; val sigma : (int -> int) * int -> int = <fun> sigma f n ( : * -> * ) sqsum cbsu II 4 : 2001 11 7 keywords: 1 OCaml OCaml (first-class value) (higher-order function) 1.1 1 2 + 2 2 + + n 2 sqsum 1 3 + 2 3 + + n 3 cbsum # let rec sqsum n = # if n = 0 then 0 else n * n + sqsum (n - 1)

More information

MSAC-EX1

MSAC-EX1 3-218-418-02 (1) ExpressCard MSAC-EX1 b 2 MSAC-EX1 3 Program 2007 Sony Corporation Documentation 2007 Sony Corporation Memory Stick MagicGate Memory Stick Memory Stick Duo MagicGate Memory Stick Duo Memory

More information

SO(2)

SO(2) TOP URL http://amonphys.web.fc2.com/ 1 12 3 12.1.................................. 3 12.2.......................... 4 12.3............................. 5 12.4 SO(2).................................. 6

More information

2016 10 31 1. 1.1 20 1 1993 20 2 2 1 industrial society 2 2 169 2014 3 1.2 4 5 6 3 1.3 4 5 1973 6 170 7 8 9 7 ISO/IEC 9126 11 8 1 9 ABS ABS ABS ABS 171 2. 2.1 1960 10 11 12 13 10 1964 IBM S/360 11 16 FORTRAN

More information

IA hara@math.kyushu-u.ac.jp Last updated: January,......................................................................................................................................................................................

More information

16 3 1....1 2....3 3....5 4....6 1....7 2....8 3....11 4....13 1....15 2....17 PRTR...20...23...30...35 1. 1 2 2. / / 29 / / 29 29 3 PRTR () () 29 29 * 29 4 3. 4 1 6 30 (1) 35 13 (2) 14 (3) PRTR 23 ID

More information

iphone GPGPU GPU OpenCL Mac OS X Snow LeopardOpenCL iphone OpenCL OpenCL NVIDIA GPU CUDA GPU GPU GPU 15 GPU GPU CPU GPU iii OpenMP MPI CPU OpenCL CUDA OpenCL CPU OpenCL GPU NVIDIA Fermi GPU Fermi GPU GPU

More information

(Compton Scattering) Beaming 1 exp [i (k x ωt)] k λ k = 2π/λ ω = 2πν k = ω/c k x ωt ( ω ) k α c, k k x ωt η αβ k α x β diag( + ++) x β = (ct, x) O O x

(Compton Scattering) Beaming 1 exp [i (k x ωt)] k λ k = 2π/λ ω = 2πν k = ω/c k x ωt ( ω ) k α c, k k x ωt η αβ k α x β diag( + ++) x β = (ct, x) O O x Compton Scattering Beaming exp [i k x ωt] k λ k π/λ ω πν k ω/c k x ωt ω k α c, k k x ωt η αβ k α x β diag + ++ x β ct, x O O x O O v k α k α β, γ k γ k βk, k γ k + βk k γ k k, k γ k + βk 3 k k 4 k 3 k

More information

Formation process of regular satellites on the circumplanetary disk Hidetaka Okada Department of Earth Sciences, Undergraduate school of Scie

Formation process of regular satellites on the circumplanetary disk Hidetaka Okada Department of Earth Sciences, Undergraduate school of Scie Formation process of regular satellites on the circumplanetary disk Hidetaka Okada 22060172 Department of Earth Sciences, Undergraduate school of Science, Hokkaido University Planetary and Space Group

More information

付加情報をもったファイル共有システム

付加情報をもったファイル共有システム 1 2 1 6 1.1....................................... 6 1.2...................................... 6 1.3..................................... 6 1.4................................... 7 2 8 2.1 Annphony....................................

More information

製品価格 ( 新規購入 ) INT6531 インテル VTune Amplifier XE 2017 for Windows Floating 1-275, ,000 INT6532 インテル VTune Amplifier XE 2017 for Linux Floating 1-27

製品価格 ( 新規購入 ) INT6531 インテル VTune Amplifier XE 2017 for Windows Floating 1-275, ,000 INT6532 インテル VTune Amplifier XE 2017 for Linux Floating 1-27 製品価格 ( 新規購入 ) INT6499 インテル Parallel Studio XE 2017 Cluster Edition for Windows Floating 2- INT6500 インテル Parallel Studio XE 2017 Cluster Edition for Windows Floating 5-2,478,000 2,676,240 INT6501 インテル Parallel

More information

Happy Link LAN ------------------------------------------------------------------------------------------------------------ 3 -------------------------------------------------------------------------------------------------------

More information