java pythoncs251/s17/slides/big-ideas_4up.pdfswift 1-5 programming languages: mechanical view a...

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Big Ideas for CS 251 Theory of Programming Languages Principles of Programming Languages CS251 Programming Languages Spring 2017, Lyn Turbak Department of Computer Science Wellesley College Discussion: Programming Languages What PLs have you used? Which PLs/PL features do you like/dislike. Why? Your experience: What is a PL? Why are new PLs created? What are they used for? Why are there so many? Why are certain PLs popular? What goes into the design of a PL? More generally: 1-2 PL is my passion! First PL project in 1982 as intern at Xerox PARC Created visual PL for 1986 MIT masters thesis 1994 MIT PhD on PL feature (synchronized lazy aggregates) 1996 – 2006: worked on types as member of Church project 1988 – 2008: Design Concepts in Programming Languages 2011 – current: lead TinkerBlocks research team at Wellesley 2012 – current: member of App Inventor development team 1-3 General Purpose PLs Python Fortran C/C++ Java Racket ML Haskell CommonLisp Perl Ruby 1-4 JavaScript

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Page 1: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

Big Ideas for CS 251Theory of Programming Languages

Principles of Programming Languages

CS251ProgrammingLanguagesSpring2017,LynTurbak

DepartmentofComputerScienceWellesleyCollege

Discussion: Programming Languages

•  What PLs have you used? •  Which PLs/PL features do you like/dislike. Why?

Your experience:

•  What is a PL? •  Why are new PLs created?

–  What are they used for? –  Why are there so many?

•  Why are certain PLs popular? •  What goes into the design of a PL?

More generally:

1-2

PLismypassion!

•  First PL project in 1982 as internat Xerox PARC

•  Created visual PL for 1986 MIT masters thesis

•  1994 MIT PhD on PL feature (synchronized lazy aggregates)

•  1996 – 2006: worked on types as member of Church project

•  1988 – 2008: Design Concepts in Programming Languages

•  2011 – current: lead TinkerBlocks research team at Wellesley

•  2012 – current: member of App Inventor development team

1-3

GeneralPurposePLs

Python Fortran

C/C++

Java

RacketML

Haskell

CommonLisp

Perl

Ruby

1-4

JavaScript

Page 2: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

DomainSpecificPLs

IDL

CSS

PostScript�

HTML

OpenGL

LaTeX

Excel

Matlab R

Swift 1-5

ProgrammingLanguages:MechanicalView

Acomputerisamachine.OuraimistomakethemachineperformsomespecifiedacEons.WithsomemachineswemightexpressourintenEonsbydepressingkeys,pushingbuIons,rotaEngknobs,etc.Foracomputer,weconstructasequenceofinstrucEons(thisisa``program'')andpresentthissequencetothemachine.

–LaurenceAtkinson,PascalProgramming 1-6

ProgrammingLanguages:LinguisEcView

Acomputerlanguage…isanovelformalmediumforexpressingideasaboutmethodology,notjustawaytogetacomputertoperformoperaEons.ProgramsarewriIenforpeopletoread,andonlyincidentallyformachinestoexecute.–HaroldAbelsonandGeraldJ.Sussman

1-7

�Religious�ViewsTheuseofCOBOLcripplesthemind;itsteachingshould,therefore,beregardedasacriminaloffense.–EdsgerDijkstra

ItispracEcallyimpossibletoteachgoodprogrammingtostudentsthathavehadapriorexposuretoBASIC:aspotenEalprogrammerstheyarementallymuElatedbeyondhopeofregeneraEon.–EdsgerDijstra

You'reintroducingyourstudentstoprogramminginC?Youmightaswellgivethemafrontallobotomy!–Acolleagueofmine

ALISPprogrammerknowsthevalueofeverything,butthecostofnothing.-AlanPerlis

Ihavenevermetastudentwhocuttheirteethinanyoftheselanguagesanddidnotcomeawayprofoundlydamagedandunabletocope.ImeanthisreadstomeverysimilarlytoteachingsomeonetobeacarpenterbystarEngthemoffwithplasEctoytoolsandtellingthemtogosculptsandonthebeach.-AlfredThompson,onblockslanguages

Alanguagethatdoesn'taffectthewayyouthinkaboutprogramming,isnotworthknowing.-AlanPerlis 1-8

Page 3: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

ProgrammingLanguageEssenEals

PrimiEves

MeansofCombinaEon

MeansofAbstracEon

1-9

Thinkofthelanguagesyouknow.WhatmeansofabstracEondotheyhave?

PL Parts Syntax: form of a PL

•  What a P in a given L look like as symbols? •  Concrete syntax vs abstract syntax trees (ASTs)

Semantics: meaning of a PL •  Static Semantics: What can we tell about P before running it?

–  Scope rules: to which declaration does a variable reference refer? –  Type rules: which programs are well-typed (and therefore legal)?

•  Dynamic Semantics: What is the behavior of P? What actions does it perform? What values does it produce? –  Evaluation rules: what is the result or effect of evaluating each language

fragment and how are these composed?

Pragmatics: implementation of a PL (and PL environment)

1-10

•  How can we evaluate programs in the language on a computer? •  How can we optimize the performance of program execution?

Syntax (Form) vs. Semantics (Meaning)in Natural Language

Furiously sleep ideas green colorless.

Colorless green ideas sleep furiously.

Little white rabbits sleep soundly.

1-11

ConcreteSyntax:AbsoluteValueFuncEon

Logo: to abs :n ifelse :n < 0 [output (0 - :n)] [output :n] end

Javascript: function abs (n) {if (n < 0) return -n; else return n;}

Java: public static int abs (int n) {if (n < 0) return -n; else return n;}

Python: App Inventor: def abs(n): if n < 0: return -n else: return n

Scheme: (define abs (lambda (n) (if (< n 0) (- n) n)))

PostScript: /abs {dup 0 lt {0 swap sub} if} def

1-12

Page 4: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

AbstractSyntaxTree(AST):AbsoluteValueFuncEon

varref

return

n

return

intlit

0

relaEonalOperaEon

varref

n

condiEonalStatement

funcEonDeclaraEon

abs

ntest

then

bodyparamsfuncDo

nName

rand1

name

name

1-13

arithmeEcOperaEon

value

subtract

varref

n

name

value

intlit

0

lessThan

valuerand1

ThisASTabstractsovertheconcretesyntaxfortheLogo,JavaScript,andPythondefiniEons.TheotherdefiniEonswouldhavedifferentASTs.

DynamicSemanEcsExample1

1-14

Whatisthemeaningofthefollowingexpression?

(1 + 11) * 10

DynamicSemanEcsExample2

1-15

Whatisprintedbythefollowingprogram?

a = 1;

b = a + 20;

print(b);

a = 300

print(b);

count = 0;

fun inc() { count = count + 1; return count; }

fun dbl(ignore, x) { return x + x; }

print(dbl(inc(), inc())

DynamicSemanEcsExample3

1-16

Supposeaisanarray(orlist)containingthethreeintegervalues10,20,and30inthefollowinglanguages.Whatisthemeaningofthefollowingexpressions/statementsinvariouslanguages(thesyntaxmightdifferfromwhat’sshown).

a[1] a[3] a[2] = "foo" a[3] = 17

Java

C

Python

JavaScript

Pascal

AppInventor

Page 5: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

StaEcSemanEcsExample1

1-17

WhichofthefollowingJavaexamplesiswell-typed(i.e.,passesthetypechecker)?Howdoyouknow?WhatassumpEonsareyoumaking?

2 * (3 + 4)

2 < (3 + 4)

2 < True

if (a < b) { c = a + b; } else { c = a * b; }

if (a) { c = a + b; } else { c = a * b; }

if (a < b) { c = a + b; } else { c = a > b; }

public boolean f(int i, boolean b) { return b && (i > 0); }

public int g(int i, boolean b) { return i * (b ? 1 : -1); }

public int p(int w) { if (w > 0) { return 2*w; } }

public int q(int x) { return x > 0; }

public int r(int y) { return g(y, y>0); }

public boolean s(int z) { return f(z); }

A

B

C

D

E

F G

H

I

J

K

L

Static Semantics Example 2: Detecting Loops WhichofthesefollowingPythonprogramshasinputsforwhichitloopsforever?

2-18

def f(x): return x+1

def g(x): while True: pass return x

def h2(x): if x <= 0: return x else: return h(x+1)

def h(x): while x > 0: x = x+1 return x

def g2(x): return g2(x)

def k(x): while x != 1: if (x % 2) == 0: x = x/2 else: x = 3*x + 1 return 1

A

B C

E F

G

Static Semantics and Uncomputability ItisgenerallyimpossibletoansweranyinteresEngquesEonaboutstaEcprogramanalysis!ThisisaconsequenceofRice’sTheorem(seeCS235).

For example, will this program ever: •  halt on certain inputs •  encounter an array index out of bounds error? •  throw a NullPointerException? •  access a given object again? •  send sensitive information over the network? •  divide by 0? •  run out of memory, starting with a given amount available? •  try to treat an integer as an array?

2-19

•  Church-TuringThesis:ComputabilityisthecommonspiritembodiedbythiscollecEonofformalisms.

•  ThisthesisisaclaimthatiswidelybelievedabouttheintuiEvenoEonsofalgorithmandeffecEvecomputaEon.Itisnotatheoremthatcanbeproved.

•  Becauseoftheirsimilaritytolatercomputerhardware,Turingmachines(CS235)havebecomethegoldstandardforeffecEvelycomputable.

•  We�llseeinCS251thatChurch’slambda-calculusformalismisthefoundaEonofmodernprogramminglanguages.

•  Aconsequence:programminglanguagesallhavethe�same�computaEonal�power�intermofwhattheycanexpress.AllsuchlanguagesaresaidtobeTuring-complete.

TheChurch-TuringThesisandTuring-Completeness

2-20

Page 6: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

ExpressivenessandPower

•  About:–  ease–  elegance–  clarity– modularity–  abstracEon–  ...

•  Notabout:computability•  Differentproblems,differentlanguages

–  Facebookorwebbrowserinassemblylanguage?

2-21

Pragmatics: Raffle App In App Inventor

DesignerWindow BlocksEditor

22

Toentertheraffle,textmenowwithanemptymessage:339-225-0287

hIp://ai2.appinventor.mit.edu

HowhardisthistodoinmoretradiEonaldevelopmentenvironmentsforAndroid/iOS?

Pragmatics: Metaprogramming

1-23

PLsareimplementedintermsofmetaprogams=programsthatmanipulateotherprograms.

Thismaysoundweird,butprogramsarejusttrees(ASTs),soametaprogramisjustaprogramthatmanipulatestrees(thinkamorecomplexversionofCS230binarytreeprograms).

ImplementaEonstrategies:

•  Interpreta(on:interpretaprogramPinasourcelanguageSintermsofanimplementaEonlanguageI.

•  Transla(on(compila(on):translateaprogramPinasourcelanguageStoaprogramP’inatargetlanguageTusingatranslatorwriIeninimplementaEonlanguageI.

•  Embedding:expressprogramPinsourcelanguageSintermsofdatastructuresandfuncEonsinimplementaEonlanguageI.

Metaprogramming:InterpretaEon

InterpreterforlanguageLonmachineM

MachineMPrograminlanguageL

1-24

Page 7: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

Metaprogramming:TranslaEon

InterpreterforlanguageBonmachineM

MachineM

PrograminlanguageA AtoBtranslator

PrograminlanguageB

1-25

Metaprogramming:Embedding

InterpreterforlanguageBonmachineM

MachineMPrograminlanguageAembeddedinlanguageB

1-26

Metaprogramming:BootstrappingPuzzles

1-27

HowcanwewriteaJava-to-x86compilerinJava?

We’lllearnhowtounderstandsuchpuzzles!

Metaprogramming:ProgrammingLanguageLayers

kernel

syntacEcsugar

primiEvevalues/datatypes

systemlibraries

userlibraries

1-28

Page 8: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

PL Dimensions

1-29

PLsdifferbasedondecisionslanguagedesignersmakeinmanydimensions.E.g.:

•  First-classvalues:whatvaluescanbenamed,passedasargumentstofuncEons,returnedasvaluesfromfuncEons,storedindatastructures.Whichofthesearefirst-classinyourfavoritePL:arrays,funcEons,variables?

•  Naming:Dovariables/parametersnameexpressions,thevaluesresulEngfromevaluaEngexpressions,ormutableslotsholdingthevaluesfromevaluaEngexpressions?Howarenamesdeclaredandreferenced?Whatdeterminestheirscope?

•  State:Whatismutableandimmutable;i.e.,whatenEEesinthelanguage(variables,datastructures,objects)canchangeoverEme.

•  Control:Whatconstructsarethereforcontrolflowinthelanguage,e.g.condiEonals,loops,non-localexits,excepEonhandling,conEnuaEons?

•  Data:Whatkindsofdatastructuresaresupportedinthelanguage,includingproducts(arrays,tuples,records,dicEonaries),sums(opEons,oneofs,variants),sum-of-products,andobjects.

•  Types:AreprogramsstaEcallyordynamicallytyped?Whattypesareexpressible?

ProgrammingParadigms

1-30

•  Impera(ve(e.g.C,Python):ComputaEonisstep-by-stepexecuEononastatefulabstractmachineinvolvingmemoryslotsandmutabledatastructures.

•  Func(onal,func(on-oriented(e.gRacket,ML,Haskell):ComputaEonisexpressedbycomposingfuncEonsthatmanipulateimmutabledata.

•  Object-oriented(e.g.Simula,Smalltalk,Java):ComputaEonisexpressedintermsofstatefulobjectsthatcommunicatebypassingmessagestooneanother.

•  Logic-oriented(e.g.Prolog):ComputaEonisexpressedintermsofdeclaraEverelaEonships.

Note:InpracEce,mostPLsinvolvemulEpleparadigms.E.g.

•  PythonsupportsfuncEonalfeatures(map,filter,listcomprehensions)andobjects

•  RacketandMLhaveimperaEvefeatures.

quicksort :: Ord a => [a] -> [a]quicksort [] = []quicksort (p:xs) = (quicksort lesser) ++ [p] ++ (quicksort greater) where lesser = filter (< p) xs greater = filter (>= p) xs

1-31

ParadigmExample:Quicksortvoid qsort(int a[], int lo, int hi) {

int h, l, p, t;

if (lo < hi) {

l = lo;

h = hi;

p = a[hi];

do {

while ((l < h) && (a[l] <= p))

l = l+1;

while ((h > l) && (a[h] >= p))

h = h-1;

if (l < h) {

t = a[l];

a[l] = a[h];

a[h] = t;

}

} while (l < h);

a[hi] = a[l];

a[l] = p;

qsort( a, lo, l-1 );

qsort( a, l+1, hi );

}

}

ImperaEveStyle(inC;Javawouldbesimilar)

FuncEonalStyle(inHaskell)

Why?Who?When?Where?DesignandApplicaEon

•  Historical context •  Motivating applications

–  Lisp: symbolic computation, logic, AI, experimental programming –  ML: theorem-proving, case analysis, type system –  C: Unix operating system –  Simula: simulation of physical phenomena, operations, objects –  Smalltalk: communicating objects, user-programmer,

pervasiveness •  Design goals, implementation constraints

–  performance, productivity, reliability, modularity, abstraction, extensibility, strong guarantees, …

•  Well-suited to what sorts of problems? 1-32

Page 9: Java Pythoncs251/s17/slides/big-ideas_4up.pdfSwift 1-5 Programming Languages: Mechanical View A computer is a machine. Our aim is to make the machine perform some specified acEons

WhystudyPL?•  CrossroadsofCS

•  Approachproblemsasalanguagedesigner.

–  "Agoodprogramminglanguageisaconceptualuniverseforthinkingaboutprogramming"--AlanPerlis

–  Evaluate,compare,andchooselanguages

–  BecomebeIeratlearningnewlanguages

–  becomeabeIerproblem-solver

–  viewAPIdesignaslanguagedesign•  Ask:

–  WhyarePLsarethewaytheyare?

–  Howcouldthey(orcouldn'tthey)bebeIer?–  Whatisthecost-conveniencetrade-offforfeatureX?

1-33

Administrivia

•  Schedule, psets, lateness policy, etc.:see http://cs.wellesley.edu/~cs251/

•  PS0 (introductions) will be posted this afternoon; due tomorrow

•  PS1 will be posted tomorrow; due next Friday •  install Dr. Racket for tomorrow •  visit me in office hours!

1-34