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4/8/17

CSE341: Programming Languages

Lecture 1 Course Mechanics

ML Variable Bindings

Dan Grossman Fall 2011

CSEP590–ProgrammingSystemsUniversityofWashington

Lecture2:OverviewPartII–BackEnd

MichaelRingenburgSpring2017

CourseNews•  SubmitpresentaPontopicproposalsbyApril14

–  Ifyouwouldliketoworkwithapartner,bothofyouwillhavetopresent,andIwillexpectamoreindepth/longerpresentaPon

–  We’reupto19students–trickytofit>18intofinal3weeks.Letmeknowifyou’dbewillingtopresentMay9.

•  Otherwisemayhavetocomeearlyorstaylateoneclass(we’llvote)•  Todayandnextweek:

–  Finishcompileroverview–  Cover1or2advancedtopicsincompilers:

•  RegisterallocaPonviagraphcoloring•  PossiblySSAform

•  A]erthat,broadenourhorizonsabitandlookatothertypesofprogrammingsystems

Spring2017 UWCSEP590(PMPProgrammingSystems):Ringenburg 1

4/8/17

Reminder:CompilerStructure

Source Target

Scanner

Parser

OpPmizer

CodeGen

characters

tokens

IR (often different)

Machine code

SemanPcAnalysis

IR (may be different)

“FrontEnd”

“BackEnd”

IntermediateRepresenta.ons

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IntermediateRepresentaPons

•  TheparserbuildsanintermediaterepresentaPonoftheprogram– TypicallyanAST

•  RestofthecompilerchecksandtransformstheIRtoimprove(“opPmize”)it,andeventuallytranslatesittofinalcode– TypicallywilltransforminiPalIRtooneormorelowerlevelIRsalongtheway

IRDesignTaxonomy

•  Structure– Graphical(trees,graphs,etc.)– Linear(codeforsomeabstractmachine)– Hybridsarecommon(e.g.,control-flowgraphswithlinearcodeinbasicblocks)

•  AbstracPonLevel– High-level,neartosourcelanguage– Low-level,closertomachine

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Example:ArrayReference

Source:A[i,j]AST:

High-levellinear:t1 ← A[i,j]

Low-levellinear(3address):loadI 1 => r1sub rj,r1 => r2loadI 10 => r3mult r2,r3 => r4sub ri,r1 => r5add r4,r5 => r6loadI @A => r7add r7,r6 => r8load r8 => r9

subscript

GraphicalIRs

•  IRsrepresentedasagraph(ortree)•  Nodesandedgestypicallyreflectsomestructureoftheprogram–  E.g.,source,controlflow,datadependence

•  Maybelarge(especiallysyntaxtrees)•  High-levelexamples:

–  Syntaxtrees–  Controlflowgraphs– Datadependencegraphs– O]enusedinopPmizaPonandcodegeneraPon

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GraphicalIR:ConcreteSyntaxTrees

•  Thefullgrammarisneededtoguidetheparser,butcontainsmanyextraneousdetails–  E.g.,syntacPctokens,rulesthatcontrolprecedence

•  Typicallythefullsyntaxtreedoesnotneedtobeusedexplicitly

F Id(y)

Subscript

A [ i ]

GraphicalIR:AbstractSyntaxTrees

•  WantonlyessenPalstructuralinformaPon•  Canberepresentedexplicitlyasatreeorinalinearform,e.g.,

intheorderofadepth-firsttraversal.Fora[i+j],thismightbe:Subscript Id(A) Plus Id(i) Id(j)

•  Commonoutputfromparser;usedforstaPcsemanPcs(typechecking,etc.)andsomePmeshigh-levelopPmizaPons

Id(x) Id(y)

Subscript

A Plus

Id(i) Id(j)

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ControlFlowGraph(CFG)•  NodesareBasicBlocks

–  Codethatalwaysexecutestogether(i.e.,nobranchesintooroutofthemiddleoftheblock).

–  I.e.,“straightlinecode”•  Edgesrepresentpathsthatcontrolflowcouldtake.–  I.e.,possibleexecuPonorderings.–  EdgefromBasicBlockAtoBasicBlockBmeansBlockBcouldexecuteimmediatelya]erBlockAcompletes.

•  RequiredformuchoftheanalysisdoneintheopPmizer.

CFGExampleprint(“hello”);a = 7;if (x == y) { print(“equal”); b = 9;} else { b = 10;}while (a < b) { a++; print(“increase”);}print(“done”);Spring2017 UWCSEP590(PMPProgrammingSystems):

Ringenburg 11

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CFGExampleprint(“hello”);a = 7;if (x == y)

print(“hello”);a = 7;if (x == y) { print(“equal”); b = 9;} else { b = 10;}while (a < b) { a++; print(“increase”);}print(“done”);Spring2017 UWCSEP590(PMPProgrammingSystems):

Ringenburg 12

CFGExampleprint(“hello”);a = 7;if (x == y)

print(“equal”);b = 9;

print(“hello”);a = 7;if (x == y) { print(“equal”); b = 9;} else { b = 10;}while (a < b) { a++; print(“increase”);}print(“done”);Spring2017 UWCSEP590(PMPProgrammingSystems):

Ringenburg 13

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CFGExampleprint(“hello”);a = 7;if (x == y) { print(“equal”); b = 9;} else { b = 10;}while (a < b) { a++; print(“increase”);}print(“done”);

print(“hello”);a = 7;if (x == y)

b = 10;print(“equal”);b = 9;

while (a < b)

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while (a < b)

a++;print(“increase”);

while (a < b)

a++;print(“increase”);

print(“done”);Spring2017 UWCSEP590(PMPProgrammingSystems):

Ringenburg 17

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(Program/Data)DependenceGraph

•  O]enusedinconjuncPonwithanotherIR.•  Inadatadependencegraph,edgesbetweennodesrepresent“dependencies”betweenthecoderepresentedbythosenodes.–  IfAandBaccessthesamedata,andAmustoccurbeforeBtoachievecorrectbehavior,thenthereisadependenceedgefromAtoB.

–  AàBmeanscompilercan’tmoveBbeforeA.–  Granularityofnodesvaries.DependsonabstracPonlevelofrestofIR.E.g.,nodescouldbeloads/stores,orwholestatements.

–  E.g.,a=2;b=2;c=a+7;• Where’sthedependence?

Typesofdependencies•  Read-a]er-write(RAW)/“flowdependence”

–  E.g.,a=7;b=a+1;–  Thereadof‘a’mustfollowthewriteto‘a’,otherwiseitwon’tseethecorrectvalue.

•  Write-a]er-read(WAR)/“anPdependence”–  E.g.,b=a*2;a=5;–  Thewriteto‘a’mustfollowthereadof‘a’,otherwisethereadwon’tseethecorrectvalue.

•  Write-a]er-write(WAW)/“outputdependence”–  E.g.,a=1;…a=2;…–  Thewritesto‘a’musthappeninthecorrectorder,otherwise‘a’willhavethewrongfinalvalue.

•  WhataboutRAR/”inputdependence”??

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Loop-CarriedDependence

•  Loopcarrieddependence:AdependenceacrossiteraPonsofaloop

for(i=0;i<size;i++) x=foo(x);

•  RAWloopcarrieddependence:thereadof‘x’dependsonthewriteof‘x’inthepreviousiteraPon

•  IdenPfyingandunderstandingtheseiscriPcalforloopparallelizaPon/vectorizaPon–  Ifthecompiler“understands”thenatureofthedependence,itcansomePmesberemovedordealtwith

–  O]enusesophisPcatedarraysubscriptanalysisforthis

DependenceGraphExample

a = 7;print(“hello”);while (a < b) { print(“increase”); a++;}print(“done”);

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LCD:Loop-CarriedDependence

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LCD:Loop-CarriedDependence

LinearIRs

•  Pseudo-codeforsomeabstractmachine•  LevelofabstracPonvaries•  Simple,compactdatastructures

– Commonlyused:arrays,linkedstructures

•  Examples:3-addresscode,stackmachinecode T1ß2

T2ßbT3ßT1*T2T4ßaT5ßT4–T3

push2pushbmulPplypushasubtract

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WhatIRtoUse?

•  Commonchoice:all(!)–  ASTorotherstructuralrepresentaPonbuiltbyparserandusedinearlystagesofthecompiler

•  Closertosourcecode•  GoodforsemanPcanalysis•  Facilitatessomehigher-levelopPmizaPons

–  Lowertolow-levellinearIRforlaterstagesofcompiler•  Closertomachinecode•  Exposesmachine-relatedopPmizaPons•  GoodforresourceallocaPonandscheduling

Seman.cAnalysis

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Whatdoweneedtochecktocompilethis?

classC{inta;C(intiniPal){ a=iniPal;}voidsetA(intval){ a=val;}

classMain{publicstaPcvoid

main(String[]args){ Cc=newC(17); c.setA(42);

BeyondSyntax

•  Thereisalevelofcorrectnessthatisnotcapturedbyacontext-freegrammar–  Hasavariablebeendeclared?–  Aretypesconsistentinanexpression?–  Intheassignmentx=y,isyassignabletox?–  Doesamethodcallhavetherightnumberandtypesofparameters?

–  Inaselectorp.q,isqamethodorfieldofclassinstancep?–  IsvariablexguaranteedtobeiniPalizedbeforeitisused?–  Inp.q,couldpbenull?–  Etc.

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CheckedProperPes

•  SomeenforcedatcompilePme,othersatrunPme(typicallydependsonlanguagespec).

•  Differentlanguageshavedifferentrequirements–  E.g.,Cvs.Javatypingrules,iniPalizaPonrequirements–  SomeoftheseproperPesareo]endesirableinprograms,evenifthelanguagedoesn’trequirethem.

–  Compilersshouldn’tenforceapropertythatisnotrequiredbythelanguage(butcanwarn).

– However,therearestaPccheckersforsomeoftheseproperPesthatusecompiler-stylealgorithms.

Whatelsedoweneedtoknowtogeneratecode?

•  Wherearefieldsallocatedinanobject?•  Howbigareobjects?(i.e.,howmuchstorageneedstobeallocated)

•  Wherearelocalvariablesstoredwhenamethodiscalled?–  Stack?Whatoffset?Orexclusivelyinregister?Whichregister?

•  Whichmethodsareassociatedwithanobject/class?–  InparPcular,howdowefigureoutwhichmethodtocallbasedontherun-Pmetypeofanobject?

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SemanPcAnalysis•  Maintasks:

–  ExtracttypesandotherinformaPonfromtheprogram–  Checklanguagerulesthatgobeyondthecontext-freegrammar–  Resolvenames

•  RelatedeclaraPonsandusesofeachvariable–  “Understand”theprogramwellenoughforsynthesis

•  E.g.,sizes,layoutsofclasses/structs•  Keydatastructure:Symboltables

–  MapeachidenPfierintheprogramtoinformaPonaboutit(kind,type,etc.)

•  Thisistypicallyconsideredthefinalpartofthe“frontend”ofthecompiler(oncecomplete,knowwhetherornotprogramislegal).

SomeKindsofSemanPcInformaPon

Information Generated From Used to process

Symbol names (variables, methods)

Declarations Expressions, statements

Type information Declarations, expressions

Operations

Memory layout information

Assigned by compiler Target code generation

Values Constants Expressions (constant folding)

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ASamplingofSemanPcChecksandComputaPons

•  Appearanceofanameinanexpression:id– Check:Symbolhasbeendeclaredandisinscope– Compute:Inferredtypeisthedeclaredtypeofsymbol

•  Constant:v– Compute:Inferredtypeandvalueareexplicit– Example:42.0hastypedoubleandvalue42.0

ASamplingofSemanPcChecksandComputaPons

•  Binaryoperator:exp1opexp2– Check:exp1andexp2havecompaPbletypes

•  EitheridenPcal,orwell-definedconversiontoappropriatetypes

•  TypesarecompaPblewithop•  Example:42 + truefails,20 + 21.9999passes

– Compute:InferredtypeofexpressionisafuncPonoftheoperatorandoperandtypes

•  Example:20 + 21.999hastypedouble,42 + “, the answer”hastypeString(inJava).

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AyributeGrammars

•  AsystemaPcwaytothinkaboutsemanPcanalysis

•  FormalizeproperPeschecked/computedduringsemanPcanalysisandrelatethemtogrammarproducPonsintheCFG.

•  SomePmesuseddirectly,butevenwhennot,AGsareausefulwaytoorganizetheanalysisandthinkaboutit

AyributeGrammars

•  Idea:associateayributeswitheachnodeinthesyntaxtree

•  Examplesofayributes–  TypeinformaPon–  StorageinformaPon– Assignable(e.g.,expressionvsvariable–lvaluevsrvalueforC/C++programmers)

–  Value(forconstantexpressions)–  etc.…

•  NotaPon:X.aifaisanayributeofnodeXSpring2017 UWCSEP590(PMPProgrammingSystems):

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InheritedandSynthesizedAyributes

•  GivenaproducPonX::=Y1Y2…Yn•  AsynthesizedayributeX.aisafuncPonofsomecombinaPonofayributesofYi’s(boyomup)–  E.g.,avalueayribute

•  AninheritedayributeYi.bisafuncPonofsomecombinaPonofayributesX.aandotherYj.c(topdown)– O]enrestrictedabit:onlyY’stothele]canbeused.–  E.g.,a“typeenvironment”ora“valueenvironment”–mappingsofsymbolstotypesorvalues(iftheyareknownconstants).

AyributeEquaPons

•  ForeachkindofnodewegiveasetofequaPonsrelaPngayributevaluesofthenodeanditschildren–  Example:

plus.val=exp1.val+exp2.val

•  AyribuPon(aka,evaluaPon)meansimplicitlyfindingasoluPonthatsaPsfiesalloftheequaPonsinthetree

exp1 exp2

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InformalExampleofAyributeRules

•  Supposewehavethefollowinggrammarforatriviallanguageprogram::=declListstmtdeclList::=declListdecl|decltwostmts::=stmtstmtdecl::=intid;stmt::=exp=exp;exp::=id|exp+exp|INTEGER_LITERAL

•  Wewanttogivesuitableayributesforbasictypeandlvalue/rvaluechecking,andconstantfolding

InformalExampleofAyributeRules

•  Ayributesofnodes–  env(typeenvironment)storesthetypesofalldeclaredvariables;synthesizedbydeclaraPons,inheritedbythestatement

•  Eachentrymapsanametoitstype–  envPre(fordeclaraPons)–Usedtobuilduptheenvironment

•  RepresentstheenvironmentpriortothedeclaraPon.•  E.g.,“intx;inty;”.TheenvPreof“inty”willmapxtoanint.Theenvof“inty”willmapxtointandytoint.

–  type(forexpressions);synthesizedfromchildren(andpossibleenvlookup)

–  kind:var(assignable)orval(notassignable);synthesized–  value(forexpressions):UNK(unknown)oranInteger,representscomputedconstantvalue;synthesized

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AyributesforDeclaraPons

•  decl::=intid;–  decl.env=decl.preEnvU{(id,int)}–  IntuiPon:add(id,int)mappingtoanenvironmentcontainingmappingsforpreviousdeclaraPons

•  Example:AyribuPonforint y,giventhatwepreviouslysawint x–  Sawint xearlier,soassumedecl.preEnv={(x,int)}–  decl::=int y;–  decl.env=decl.preEnvU{(y,int)}=

{(x,int)}U{(y,int)}= {(x,int),(y,int)}

•  declList1::=declList2decl– decl.preEnv=declList2.env– declList1.env=decl.env–  IntuiPon:declList2.envcontainsallofthepreviouslyseenmappings,souseitasthepre-environmentforournewdeclaraPon.Theenvironmentforthecombinedlist(list1)willbetheresultofaddingthemappingfordecltothemappingsofthesublist(list2).

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•  declList::=decl– decl.preEnv={}– declList.env=decl.env–  IntuiPon:ForthefirstelementinourdeclaraPonlist,wecanstartwithanemptyenvironment,becausewewon’thaveseenanydeclaraPonsyet.(Truehere,butprobablynotinareallanguage.)

ExampleDeclaraPonList

int a; int b; int c;

•  declList::=decl•  decl.preEnv={}•  declList.env=decl.env

•  declList1::=declList2decl•  decl.preEnv=declList2.env•  declList1.env=decl.env

•  decl::=intid;•  decl.env=decl.preEnvU{(id,int)}Spring2017

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•  decl::=intid;•  decl.env=decl.preEnvU{(id,int)}

declList

Spring2017

declList

pre:{}

Spring2017

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declList

pre:{},env:{a,int}

env:{a,int}

Spring2017

declList

pre:{},env:{a,int}

env:{a,int} pre:{a,int}

Spring2017

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declList

pre:{},env:{a,int}

env:{a,int} pre:{a,int},env:{(a,int)(b,int)}

Spring2017

declList

pre:{},env:{a,int}

env:{a,int} pre:{a,int},env:{(a,int)(b,int)}

env:{(a,int)(b,int)} pre:{(a,int)(b,int)},env:{(a,int)(b,int)(c,int)}

env:{(a,int)(b,int)(c,int)}

Spring2017

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AyributesforProgram

•  program::=declListstmt–  stmt.env=declList.env–  IntuiPon:WewanttotypecheckourstatementgiventhetypeenvironmentsynthesizedbyourdeclaraPonlist.

•  Example:Ifprogramwas

int a; int b; b = a + 1;

Wewouldtypechecktheassignmentstatementwiththeenvironment{(a,int),(b,int)}

AyributesforConstants

•  exp::=INTEGER_LITERAL– exp.kind=val– exp.type=int– exp.value=INTEGER_LITERAL–  IntuiPon:Anintegerconstant(literal)clearlyhastypeint,andexplicitvalue.Youcan’tassigntoit(5=xisnotlegal),soitisavalue(val)notavariable(var).

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AyributesforIdenPfierExpressions

•  exp::=id–  id.type=exp.env.lookup(id)

•  Ifthislookupfails,issueanundeclaredvariableerror.–  exp.type=id.type–  exp.kind=var–  exp.value=UNK–  IntuiPon:WelookuptheidenPfier’stypeintheenvironment,andusethatastheexpression’stype.Ifitdoesn’texistintheenvironment,itmustnothavebeendeclared,soit’sanerror.Sinceitisavariable,itisassignableandhasunknownvalue.

–  Example:Typecheckingawithenvironment{(a,int)}givestypeint.Typecheckingbwiththesameenvironmentgivesanerror.

AyributesforAddiPon

•  exp::=exp1+exp2–  exp1.env=exp2.env=exp.env–  errorifexp1.type!=exp2.type(orifnotcompaPbleifusingmore

complexrules)

–  exp.type=exp1.type(orconvertedtypeifmorecomplexrules)

–  exp.kind=val–  exp.value=(exp1.value==UNK||exp2.value==UNK)?

UNK:exp1.value+exp2.value–  IntuiPon:TypecheckoperandswithsameenvironmentasoperaPon.VerifythattypesarecompaPble,andsetresulttypeappropriately.Notassignable,sosetkindtoval.Computevalueifbothoperandshaveconstantvalue.

Spring2017 UWCSEP590(PMPProgrammingSystems):

Ringenburg 57

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AyributeRulesforAssignment

•  stmt::=exp1=exp2;– exp1.env=stmt.env– exp2.env=stmt.env– Errorifexp2.typeisnotassignmentcompaPblewithexp1.type

– Errorifexp1.kindisnotvar(can’tbeval)–  IntuiPon:Verifythatle]handsideisassignable,andthattypesofle]andrighthandsidesarecompaPble.

Exampleintx;inty;intz;x=y+(1+2);

program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  program::=declListstmt•  stmt.env=declList.env

•  exp::=INTEGER_LITERAL•  exp.kind=val•  exp.type=int•  exp.value=INTEGER_LITERAL

•  exp::=id•  type=exp.env.lookup(id)

•  (erroriffails)•  exp.type=id.type•  exp.kind=var•  exp.value=UNKSpring2017

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program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  (erroriffails)•  exp.type=id.type•  exp.kind=var•  exp.value=UNK

TypecheckywithdeclListenvKind:var,Value:UNK

Spring2017

program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  (erroriffails)•  exp.type=id.type•  exp.kind=var•  exp.value=UNK

Type:int,Value:1,Kind:val

Spring2017

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program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  exp::=exp1+exp2•  exp1.env=exp2.env=exp.env

•  errorifexp1.type!=exp2.type(orifnotcompaPble)

•  exp.type=exp1.type(orconvertedtype)

•  exp.kind=val•  exp.value=(exp1.value==

UNK||exp2.value==UNK)?UNK:exp1.value+exp2.value

Spring2017

program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  exp::=exp1+exp2•  exp1.env=exp2.env=exp.env

•  errorifexp1.type!=exp2.type(orifnotcompaPble)

•  exp.type=exp1.type(orconvertedtype)

•  exp.kind=val•  exp.value=(exp1.value==

UNK||exp2.value==UNK)?UNK:exp1.value+exp2.value

Type:int,Value:UNK,Kind:val

Spring2017

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program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  stmt::=exp1=exp2;•  exp1.env=stmt.env•  exp2.env=stmt.env•  Errorifexp2.typeisnot

assignmentcompaPblewithexp1.type

•  Errorifexp1.kindisnotvar(can’tbeval)

TypecheckxwithdeclListenvType:int,Kind:var

Spring2017

program

declList stmt(=)

exp exp

id(y)+

INT(1) INT(2)

•  stmt::=exp1=exp2;•  exp1.env=stmt.env•  exp2.env=stmt.env•  Errorifexp2.typeisnot

assignmentcompaPblewithexp1.type

•  Errorifexp1.kindisnotvar(can’tbeval)

TypecheckxwithdeclListenvType:int,Kind:var

Passesbothchecks!

Spring2017

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ObservaPons•  TheseareequaPonal(funcPonal)computaPons•  Thiscanbeautomated(ifequaPonsarenon-circular)•  ButimplementaPonproblems

–  Non-localcomputaPon:AyributeequaPonscanonlyrefertovaluesassociatedwithsymbolsthatappearinasingleproducPonrule.

•  Ifyouneednon-localvalues,youneedtoaddspecialrulestothegrammartocopythemaround.Canmakegrammarverylarge.

–  Can’taffordtoliterallypassaroundcopiesoflarge,aggregatestructureslikeenvironments.

–  UseofproducPonrulesbindsayributestotheparsetreeratherthanthe(typicallysmaller,andmoreuseful)AST.Canworkaroundthis(use“ASTgrammar”),butresultsinmorecomplexayributerules.

InPracPce

•  AyributegrammarsgiveusagoodwayofthinkingabouthowtostructuresemanPcchecks

•  SymboltableswillholdenvironmentinformaPon•  AddfieldstoASTnodestorefertoappropriateayributes(symboltableentriesforidenPfiers,typesforexpressions,etc.)–  PutinappropriateplacesinASTclassinheritancetree–moststatementsdon’tneedtypes,forexample

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SymbolTables•  MapidenPfiersto<type,kind,locaPon,otherproperPes>

•  OperaPons–  Lookup(id)=>informaPon–  Enter(id,informaPon)– Open/closescopes

•  Build&useduringsemanPcspass–  BuildfirstfromdeclaraPons–  ThenusetochecksemanPcrules

•  Use(andaddto)duringlaterphasesaswell

CodeGenera.on

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BasicCodeGeneraPonStrategy

•  WalktheASTorotherIR,outpu�ngcodeforeachconstructencountered

•  Handlingofnode’schildrenisdependentontypeofnode–  E.g.,forbinaryoperaPonlike+:

•  Generatecodetocomputeoperand1(andstoreresult)•  Generatecodetocomputeoperand2(andstoreresult)•  Generatecodetoloadoperandresultsandaddthemtogether

•  Todayisjustasamplingofbasicconstructs,togivebasicidea

ConvenPonsforExamples

•  Thefollowingslideswillwalkthroughhowthisisdoneformanycommonlanguageconstructs

•  ExamplesshowcodesnippetsinisolaPon•  Registereaxusedbelowasagenericexample

–  RenameasneededformorecomplexcodeusingmulPpleregisters

•  Afewpeepholeop7miza7onsincludedbelowforaflavorofwhat’spossible–  LocalizedopPmizaPonsperformedonsmallASMinstrucPonsequences.

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Variables

•  Forourpurposes,assumealldatawillbeineither:– Astackframe(methodlocalvariables)– Anobject(instancevariables)

•  Localvariablesaccessedviaebp(stackbasepointer) moveax,[ebp-12]

•  Objectinstancevariablesaccessedviaanobjectaddressinaregister

CodeGeneraPonforConstants

•  Source17

•  x86moveax,17

–  Idea:realizeconstantvalueinaregister

•  OpPmizaPon:ifconstantis0 xoreax,eax

– Maybesmallerandfaster

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AssignmentStatement

•  Sourcevar=exp;

•  x86<codetoevaluateexpinto,say,eax>mov[ebp+offsetvar],eax

UnaryMinus

•  Source-exp

•  x86<codeevaluaPngexpintoeax>negeax

•  OpPmizaPon– Collapse-(-exp)toexp

•  Unaryplusisano-op

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Binary+

•  Sourceexp1+exp2

•  x86<codeevaluaPngexp1intoeax><codeevaluaPngexp2intoedx>addeax,edx

Binary+

•  OpPmizaPons–  Ifexp2isasimplevariableorconstant,don’tneedtoloaditintoanotherregisterfirst.Instead:

addeax,immConst;immisconstantaddeax,[ebp+offsetvar];offsetisvariable’sstackoffset

–  Changeexp1+(-exp2)intoexp1-exp2–  Ifexp2is1

inceax•  Somewhatsurprising:whetherthisisbeyerthanaddeax,1dependsonprocessorimplementaPonandhaschangedoverPme

Spring2017 UWCSEP590(PMPProgrammingSystems):

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ControlFlow

•  Basicidea:decomposehigherleveloperaPonintocondiPonalanduncondiPonalgotos

•  Inthefollowing,jfalseisusedtomeanjumpwhenacondiPonisfalse–  NosuchinstrucPononx86–  CanrealizewithappropriatesequenceofinstrucPonstosetcondiPoncodesfollowedbycondiPonaljumps

–  Normallydon’tactuallygeneratethevalue“true”or“false”inaregister

•  Sourcewhile(cond)stmt

•  X86test: <codeevaluaPngcond> jfalsedone <codeforstmt> jmptest

– Note:Ingeneratedasmcodewe’llneedtogenerateuniquelabelsforeachloop

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•  Sourceif(cond)stmt

•  x86 <codeevaluaPngcond> jfalseskip <codeforstmt>

BooleanExpressions

•  Whatdowedowiththis?x>y

•  Itisanexpressionthatevaluatestotrueorfalse– Couldgeneratethevalue(0/1orwhateverthelocalconvenPonis)

– Butnormallywedon’twant/needthevalue;we’reonlytryingtodecidewhethertojump

•  OneexcepPon:assignmentexpressions,e.g.,while(my_bool=(x<y)){…}

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Codeforexp1>exp2

•  Generatedcodedependsoncontext– Whatisthejumptarget?–  JumpifthecondiPonistrueoriffalse?

•  Example:evaluateexp1>exp2,jumponfalse,targetifjumptakenisL123

<evaluateexp1toeax><evaluateexp2toedx>cmpeax,edxjngL123 ;greater-thantest,jumponfalse,sojng ;(jumpnotgreater)

Op.miza.onOverview

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OpPmizaPons•  UseaddedpassestoidenPfyinefficienciesinintermediate

ortargetcode•  Replacewithequivalent(“hasthesameexternallyvisible

behavior”)butbeyersequences–  Beyercanmeanmanythings:faster,smaller,lessmemory,moreenergy-efficient,etc.

•  Target-independentopPmizaPonsbestdoneonIRcode–  RemovingredundantcomputaPons,deadcode,etc.

•  Target-dependentopPmizaPonsbestdoneontargetcode–  GeneraPngsequencethataremoreefficientonaparPcularmachine

•  “OpPmize”overlyopPmisPc:“usuallyimprove”isgenerallymoreaccurate–  And“clever”programmerscanoutwityou!

Anexamplex = a[i] + b[2]; c[i] = x - 5;

t1 = *(fp + ioffset); // i t2 = t1 * 4; t3 = fp + t2; t4 = *(t3 + aoffset); // a[i] t5 = 2; t6 = t5 * 4; t7 = fp + t6; t8 = *(t7 + boffset); // b[2] t9 = t4 + t8; *(fp + xoffset) = t9; // x = … t10 = *(fp + xoffset); // x t11 = 5; t12 = t10 - t11; t13 = *(fp + ioffset); // i t14 = t13 * 4; t15 = fp + t14; *(t15 + coffset) = t12; // c[i] := …

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Anexamplet1 = *(fp + ioffset); // i t2 = t1 << 2; t3 = fp + t2; t4 = *(t3 + aoffset); // a[i] t5 = 2; t6 = t5 << 2; t7 = fp + t6; t8 = *(t7 + boffset); // b[2] t9 = t4 + t8; *(fp + xoffset) = t9; // x = … t10 = *(fp + xoffset); // x t11 = 5; t12 = t10 - t11; t13 = *(fp + ioffset); // i t14 = t13 << 2; t15 = fp + t14; *(t15 + coffset) = t12; // c[i] := …

StrengthReducPon:shi]o]encheaperthanmulPply