Programming Languages: Build, Prove, and Compare

800 Pages·2022·10.137 MB·

by  Norman Ramsey

ProgrammingLanguages
Computer scientists often need to learn new programming languages quickly. The best way to
prepareistounderstandthefoundationalprinciplesthatunderlieeventhemostcomplicatedindustrial
languages.
This text for an undergraduate programming-languages course distills great languages and their
designprinciplesdowntoeasy-to-learn“bridge”languagesimplementedbyinterpreterswhosekey
partsareexplainedinthetext.Thebookgoesdeepintotherootsofbothfunctionalandobject-oriented
programming,anditshowshowtypesandmodules,includinggenerics/polymorphism,contributeto
effectiveprogramming.
The book is not just about programming languages; it is also about programming. Through
concepts,examples,andmorethan300practiceexercisesthatexploittheinterpreters,studentslearn
not only what programming-language features are common but also how to do things with them.
Substantial implementation projects include Milner’s type inference, both copying and mark-and-
sweepgarbagecollection,andarithmeticonarbitrary-precisionintegers.
NormanRamseyisAssociateProfessorofComputerScienceatTuftsUniversity.Sinceearninghis
PhD at Princeton, he has worked in industry and has taught programming languages, advanced
functional programming, programming language implementation, and technical writing at Purdue,
theUniversityofVirginia,andHarvardaswellasTufts.HehasreceivedTufts’sLerman-Neubauer
Prize,awardedannuallytooneoutstandingundergraduateteacher.HehasalsobeenaHertzFellow
andanAlfredP.SloanResearchFellow.Hisimplementationcreditsincludeacodegeneratorforthe
StandardMLofNewJerseycompilerandanotherfortheGlasgowHaskellCompiler.

Programming Languages
Build, Prove, and Compare
Norman Ramsey
TuftsUniversity,Massachusetts
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CambridgeUniversityPressispartoftheUniversityofCambridge.
ItfurtherstheUniversity’smissionbydisseminatingknowledgeinthepursuitof
education,learning,andresearchatthehighestinternationallevelsofexcellence.
www.cambridge.org
Informationonthistitle:www.cambridge.org/highereducation/isbn/9781107180185
DOI:10.1017/9781316841396
©NormanRamsey2023
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithoutthewritten
permissionofCambridgeUniversityPress.
Firstpublished2023
AcataloguerecordforthispublicationisavailablefromtheBritishLibrary.
ISBN978-1-107-18018-5Hardback
Additionalresourcesforthispublicationatwww.cambridge.org/ramsey
CambridgeUniversityPresshasnoresponsibilityforthepersistenceoraccuracyof
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To Cory, who also knows joy in creation
CONTENTſ
PREFACE ix
ACĸNOWLEDGMENTſ xv
CREDıTſ xvii
TABLEſOFȷUDGMENTFORMſANDıMPORTANTFUNCTıONſ xviii
SYMBOLſANDNOTATıON xx
INTRODUCTıON 1
PART I. FOUNDATıONſ
1 ANıMPERATıVECORE 11
1.1 Lookingatlanguages 13 1.6 Theinterpreter 38
1.2 TheImpcorelanguage 17 1.7 Operationalsemantics 55
1.3 Abstractsyntax 27 revisited:Proofs
1.4 Environmentsandthe 28 1.8 ExtendingImpcore 66
meaningsofnames 1.9 Summary 67
1.5 Operationalsemantics 29 1.10 Exercises 72
2 SCHEME,S‐EXPREſſıONſ,ANDFıRſT‐CLAſſFUNCTıONſ 89
2.1 OverviewofµScheme… 90 2.8 PracticeIII:Higher‐order 127
2.2 LanguageI:Values,syntax, 91 functionsonlists
andinitialbasis 2.9 PracticeIV:Higher‐order 131
2.3 PracticeI:Recursivefunctions 98 functionsforpolymorphism
onlistsofvalues 2.10 PracticeV: 136
2.4 Recordsandtrees(moredata) 107 Continuation‐passingstyle
2.5 Combiningtheoryandpractice: 110 2.11 Operationalsemantics 144
Algebraiclaws 2.12 Theinterpreter 152
2.6 LanguageII:Localvariables 117 2.13 ExtendingµSchemewith 162
andlet syntacticsugar
2.7 LanguageIII:First‐class 120 2.14 Schemeasitreallyis 168
functions,lambda, 2.15 Summary 172
andlocations 2.16 Exercises 176
3 CONTROLOPERATORſANDAſMALL‐ſTEPſEMANTıCſ:µSCHEME+ 201
3.1 TheµScheme+language 202 3.5 AsemanticsofCoreµScheme+ 215
3.2 Proceduralprogramming 205 3.6 Theinterpreter 223
withcontroloperators 3.7 Stacks,control,andsemantics 239
3.3 Operationalsemantics: 210 astheyreallyare
Evaluationusingastack 3.8 Summary 243
3.4 Operationalsemantics: 213 3.9 Exercises 248
Loweringtoacorelanguage
4 AUTOMATıCMEMORYMANAGEMENT 257
4.1 Whatgarbageisand 258 4.6 Debuggingacollector 280
whereitcomesfrom 4.7 Mark‐compactcollection 283
4.2 Garbage‐collectionbasics 259 4.8 Referencecounting 283
4.3 Themanagedheapin 263 4.9 Garbagecollection 285
µScheme+ asitreallyis
4.4 Mark‐and‐sweepcollection 266 4.10 Summary 287
4.5 Copyingcollection 271 4.11 Exercises 292
5 INTERLUDE:µSCHEMEıNML 301
5.1 Namesandenvironments… 303 5.5 Notabledifferences 314
5.2 Abstractsyntaxandvalues 306 betweenMLandC
5.3 Evaluation 309 5.6 Freeandboundvariables… 315
5.4 Definingandembedding 312 5.7 Summary 317
primitives 5.8 Exercises 320
6 TYPEſYſTEMſFORIMPCOREANDµSCHEME 327
6.1 TypedImpcore:Astatically 329 6.4 Commontypeconstructors 348
typedimperativecore 6.5 Typesoundness 350
6.2 Atype‐checkinginterpreter 337 6.6 Polymorphictypesystems 351
forTypedImpcore andTypedµScheme
6.3 ExtendingTypedImpcore 343 6.7 Typesystemsastheyreallyare 383
witharrays 6.8 Summary 383
6.9 Exercises 386
7 MLANDTYPEıNFERENCE 401
Contents
7.1 Nano‐ML:Anearly 402 7.5 Fromtypingrules 417
applicativelanguage totypeinference vii
7.2 Abstractsyntaxandvalues 404 7.6 Theinterpreter 433
ofnano‐ML 7.7 Hindley‐Milnerasitreallyis 441
7.3 Operationalsemantics 405 7.8 Summary 441
7.4 Typesystemfornano‐ML 407 7.9 Exercises 443
PART II. PROGRAMMıNG AT ſCALE
8 UſER‐DEFıNED,ALGEBRAıCTYPEſ(ANDPATTERNMATCHıNG) 457
8.1 Caseexpressionsand 459 8.6 Abstractsyntaxandvalues… 485
patternmatching 8.7 Theoryandimplementation 486
8.2 AlgebraicdatatypesinµML 466 ofuser‐definedtypes
8.3 Equationalreasoning 476 8.8 Theoryandimplementation 490
withcaseexpressions ofcaseexpressions
8.4 Syntacticsugar: 480 8.9 Algebraicdatatypes 499
Patternseverywhere astheyreallyare
8.5 Typegenerativityand 483 8.10 Summary 501
typeequivalence 8.11 Exercises 503
9 MOLECULE,ABſTRACTDATATYPEſ,ANDMODULEſ 525
9.1 Thevocabulary 527 9.7 Keyfeature:Inspecting 555
ofdataabstraction multiplerepresentations
9.2 IntroductiontoMolecule, 528 9.8 Molecule’stypesystem: 558
partI:Writingclientcode Enforcingabstraction
9.3 Introduction,partII: 530 9.9 Notesontheinterpreter 579
Implementinganabstraction 9.10 Abstractdatatypes,modules, 580
9.4 TheMoleculelanguage 534 andoverloading
9.5 Molecule’sinitialbasis 544 astheyreallyare
9.6 Programdesign:Abstractions 545 9.11 Summary 585
9.12 Exercises 589
10 SMALLTALĸANDOBȷECT‐ORıENTATıON 609
10.1 Object‐orientedprogramming 610 10.8 TechniqueIII:Multiple 662
byexample representations…
10.2 Dataabstractionalloveragain 625 10.9 TechniqueIV:Invariantsin 673
10.3 TheµSmalltalklanguage 627 object‐orientedprogramming
10.4 TheinitialbasisofµSmalltalk 636 10.10 Operationalsemantics 677
10.5 Object‐orientedprogramming 654 10.11 Theinterpreter 685
techniques 10.12 Smalltalkasitreallyis 700
10.6 TechniqueI:Methoddispatch 654 10.13 Objectsandclasses 707
replacesconditionals astheyreallyare
10.7 TechniqueII:Abstractclasses 656 10.14 Summary 707
10.15 Exercises 713
AFTERWORD 727
BıBLıOGRAPHY 733
KEYWORDſANDPHRAſEſ 745
CONCEPTıNDEX 749