編譯器構造

出版時間:2010-6  出版社:清華大學出版社  作者:(美)費希爾,塞特朗,勒布蘭 著  頁數(shù):683  
Tag標簽:無  

前言

  Much has changed since Crafting a Compiler, by Fischer and LeBlanc, waspublished in 1988. While instructors may remember the 5~-inch floppy disk ofsoftware that accompanied that text, most students today have neither seen norheld such a disk. Many changes have occurred in the programming languagesthat students experience in class and in the marketplace. In 1991 the bookwas available in two forms, with algorithms presented in either C or Ada.While C remains a popular language, Ada has become relatively obscure anddid not achieve its predicted popularity. The C++ language evolved fromC with the addition of object-oriented features. JavaTM was developed as asimpler object-oriented language, gaining popularity because of its securityand ability to be run within a Web browser. The College Board AdvancedPlacement curriculum moved from Pascal to C++ to Java.

內容概要

本書是一本面向計算機系本科生的編譯器教材。作者在三所美國大學擁有長達25年的編譯器教學經(jīng)驗,在本書中對編譯器構造的基本知識與關鍵技術進行了全新的講解。本書的主要內容包括:編譯器歷史和概述、詞法分析(掃描)、語法分析(包括自頂向下和自底向上的分析)、語法制導翻譯、符號表和聲明處理、語義分析、中間表示形式、虛擬機上的代碼生成、運行時支持、目標代碼生成和程序優(yōu)化等?! ”緯峁┝嗽敱M清晰的算法,主推在實踐中學習編譯器構造的相關技術,同時提供了配合教材使用的教學網(wǎng)站、參考資料以及源碼下載。不僅可以作為計算機專業(yè)本科生或研究生的參考教材,同時也適合相關領域的軟件工程師、系統(tǒng)分析師等作為參考資料。

書籍目錄

1 Introduction 1  1.1 History of Compilation 2  1.2 What Compilers Do 4  1.2.1 Machine CodeGenerated byCompilers 4  1.2.2 TargetCode Formats 7  1.3 Interpreters 9  1.4 Syntax and Semantics 10  1.4.1 Static Semantics 11  1.4.2 Runtime Semantics 12  1.5 Organization of aCompiler 14  1.5.1 TheScanner 16  1.5.2 TheParser 16  1.5.3 TheTypeChecker(Semantic Analysis) 17  1.5.4 Translator(Program Synthesis) 17  1.5.5 Symbol Tables 18  1.5.6 TheOptimizer 18  1.5.7 TheCode Generator 19  1.5.8 Compiler Writing Tools 19  1.6 Programming Language and Compiler Design 20  1.7 Computer Architecture and Compiler Design 21  1.8 Compiler DesignConsiderations 22  1.8.1 Debugging(Development)Compilers 22  1.8.2 Optimizing Compilers 23  1.8.3 Retargetable Compilers 23  1.9 Integrated DevelopmentEnvironments 24  Exercises 26 2 A Simple Compiler 31  2.1 AnInformalDe.nition of the acLanguage 32  2.2 FormalDe.nition of ac 33  2.2.1 SyntaxSpeci.cation 33  2.2.2 TokenSpeci.cation 36  2.3 Phasesof aSimpleCompiler 37  2.4 Scanning 38  2.5 Parsing 39  2.5.1 Predicting aParsingProcedure 41  2.5.2 Implementing theProduction 43  2.6 AbstractSyntaxTrees 45  2.7 Semantic Analysis 46  2.7.1 Symbol Tables 47  2.7.2 TypeChecking 48  2.8 Code Generation 51  Exercises 54 3 Scanning—Theory and Practice 57  3.1 Overviewof aScanner 58  3.2 Regular Expressions 60  3.3 Examples 62  3.4 Finite Automata and Scanners 64  3.4.1 Deterministic Finite Automata 65  3.5 The LexScannerGenerator 69  3.5.1 De.ning Tokensin Lex 70  3.5.2 TheCharacterClass 71  3.5.3 UsingRegular Expressions to De.neTokens 73  3.5.4 CharacterProcessingUsingLex 76  3.6 OtherScannerGenerators 77  3.7 PracticalConsiderations ofBuildingScanners 79  3.7.1 ProcessingIdenti.ers andLiterals 79  3.7.2 UsingCompiler Directives and Listing SourceLines 83  3.7.3 Terminating theScanner 85  3.7.4 Multicharacter Lookahead 86  3.7.5 PerformanceConsiderations 87  3.7.6 LexicalErrorRecovery 89  3.8 Regular Expressions and Finite Automata 92  3.8.1 Transforming aRegularExpressioninto anNFA 93  3.8.2 Creating theDFA 94  3.8.3 Optimizing Finite Automata 97  3.8.4 Translating Finite Automata into Regular Expressions 100  3.9 Summary 103 Exercises 106 4 Grammars and Parsing 113  4.1 Context-FreeGrammars 114  4.1.1 Leftmost Derivations 116  4.1.2 Rightmost Derivations 116  4.1.3 ParseTrees 117  4.1.4 OtherTypes ofGrammars 118  4.2 Properties of CFGs 120  4.2.1 Reduced Grammars 120  4.2.2 Ambiguity 121  4.2.3 FaultyLanguage De.nition 122  4.3 TransformingExtended Grammars 122  4.4 Parsers and Recognizers 123  4.5 GrammarAnalysisAlgorithms 127  4.5.1 GrammarRepresentation 127  4.5.2 Deriving theEmpty String 128  4.5.3 FirstSets 130  4.5.4 FollowSets 134  Exercises 138 5 Top-Down Parsing 143  5.1 Overview 144  5.2 LL(k)Grammars 145  5.3 Recursive-DescentLL(1)Parsers 149  5.4 Table-Driven LL(1)Parsers 150  5.5 Obtaining LL(1)Grammars 154  5.5.1 Common Pre.xes 156  5.5.2 Left Recursion 157  5.6 A Non-LL(1)Language 159  5.7 Properties ofLL(1)Parsers 161  5.8 ParseTable Representation 163  5.8.1 Compaction 164  5.8.2 Compression 165  5.9 SyntacticErrorRecovery andRepair 168  5.9.1 ErrorRecovery 169  5.9.2 ErrorRepair 169  5.9.3 ErrorDetectionin LL(1)Parsers 171  5.9.4 ErrorRecoveryinLL(1)Parsers 171  Exercises 173 6 Bottom-Up Parsing 179  6.1 Overview 180  6.2 Shift-Reduce Parsers 181  6.2.1 LRParsers and RightmostDerivations 182  6.2.2 LRParsing asKnitting 182  6.2.3 LRParsing Engine 184  6.2.4 TheLRParseTable 185  6.2.5 LR(k)Parsing 187  6.3 LR(0)Table Construction 191  6.4 Con.ictDiagnosis 197  6.4.1 Ambiguous Grammars 199  6.4.2 Grammars that are not LR(k) 202  6.5 Con.ictResolution andTableConstruction 204  6.5.1 SLR(k)Table Construction 204  6.5.2 LALR(k)Table Construction 209  6.5.3 LALR Propagation Graph 211  6.5.4 LR(k)Table Construction 219 Exercises 224 7 Syntax-Directed Translation 235  7.1 Overview 235  7.1.1 SemanticActions andValues 236  7.1.2 Synthesized and Inherited Attributes 237  7.2 Bottom-Up Syntax-DirectedTranslation 239  7.2.1 Example 239  7.2.2 Rule Cloning 243  7.2.3 ForcingSemantic Actions 244  7.2.4 AggressiveGrammarRestructuring 246  7.3 Top-DownSyntax-DirectedTranslation 247  7.4 AbstractSyntaxTrees 250  7.4.1 Concrete and AbstractTrees 250  7.4.2 An Ef.cientAST DataStructure 251  7.4.3 InfrastructureforCreating ASTs 252  7.5 ASTDesign andConstruction 254  7.5.1 Design 256  7.5.2 Construction 258  7.6 ASTStructuresforLeft andRightValues 261  7.7 Design PatternsforASTs 264  7.7.1 Node ClassHierarchy 264  7.7.2 Visitor Pattern 265  7.7.3 Re.ectiveVisitorPattern 268 Exercises 272 8 Symbol Tables and Declaration Processing 279  8.1 Constructing aSymbolTable 280  8.1.1 Static Scoping 282  8.1.2 A Symbol Table Interface 282  8.2 Block-StructuredLanguages andScopes 284  8.2.1 Handling Scopes 284  8.2.2 OneSymbolTable orMany? 285  8.3 Basic Implementation Techniques 286  8.3.1 Entering andFindingNames 286  8.3.2 TheName Space 289  8.3.3 An Ef.cientSymbol Table Implementation 290  8.4 Advanced Features 293  8.4.1 Records and Typenames 294  8.4.2 Overloading andTypeHierarchies 294  8.4.3 Implicit Declarations 296  8.4.4 Export andImportDirectives 296  8.4.5 Altered SearchRules 297  8.5 Declaration ProcessingFundamentals 298  8.5.1 Attributes in the Symbol Table 298  8.5.2 TypeDescriptorStructures 299  8.5.3 TypeCheckingUsing anAbstractSyntaxTree 300  8.6 Variable andTypeDeclarations 303  8.6.1 Simple Variable Declarations 303  8.6.2 Handling TypeNames 304  8.6.3 TypeDeclarations 305  8.6.4 Variable DeclarationsRevisited 308  8.6.5 Static ArrayTypes 311  8.6.6 Struct and RecordTypes 312  8.6.7 Enumeration Types 313  8.7 Class and Method Declarations 316  8.7.1 ProcessingClassDeclarations 317  8.7.2 ProcessingMethod Declarations 321  8.8 An Introduction toTypeChecking 323  8.8.1 Simple Identi.ers and Literals 327  8.8.2 Assignment Statements 328  8.8.3 Checking Expressions 328  8.8.4 Checking ComplexNames 329  8.9 Summary 334 Exercises 336 9 Semantic Analysis 343  9.1 Semantic AnalysisforControl Structures 343  9.1.1 Reachability and Termination Analysis 345  9.1.2 IfStatements 348  9.1.3 While, Do, andRepeat Loops 350  9.1.4 ForLoops 353  9.1.5 Break,Continue, Return, andGoto Statements 356  9.1.6 Switch andCaseStatements 364  9.1.7 Exception Handling 369  9.2 Semantic Analysis ofCalls 376  9.3 Summary 384 Exercises 385 10 Intermediate Representations 391  10.1 Overview 392  10.1.1 Examples 393  10.1.2 TheMiddle-End 395  10.2 Java Virtual Machine 397  10.2.1 Introduction andDesignPrinciples 398  10.2.2 Contents of aClassFile 399  10.2.3 JVMInstructions 401  10.3 Static Single Assignment Form 410  10.3.1 Renaming and φ-functions 411  Exercises 414 11 Code Generation for a Virtual Machine 417  11.1 Visitors forCode Generation 418  11.2 Class and Method Declarations 420  11.2.1 ClassDeclarations 422  11.2.2 Method Declarations 424  11.3 The MethodBodyVisitor 425  11.3.1 Constants 425  11.3.2 References to LocalStorage 426  11.3.3 Static References 427  11.3.4 Expressions 427  11.3.5 Assignment 429  11.3.6 Method Calls 430  11.3.7 Field References 432  11.3.8 ArrayReferences 433  11.3.9 Conditional Execution 435 11.3.10Loops 436  11.4 The LHSVisitor 437  11.4.1 Local References 437  11.4.2 Static References 438  11.4.3 Field References 439  11.4.4 ArrayReferences 439 Exercises 441 12 Runtime Support 445  12.1 Static Allocation 446  12.2 Stack Allocation 447  12.2.1 Field AccessinClasses andStructs 449  12.2.2 AccessingFrames at Runtime 450  12.2.3 Handling Classes and Objects 451  12.2.4 Handling Multiple Scopes 453  12.2.5 Block-LevelAllocation 455  12.2.6 MoreAbout Frames 457  12.3 Arrays 460  12.3.1 Static One-Dimensional Arrays 460  12.3.2 Multidimensional Arrays 465  12.4 Heap Management 468  12.4.1 Allocation Mechanisms 468  12.4.2 Deallocation Mechanisms 471  12.4.3 Automatic GarbageCollection 472  12.5 Region-Based MemoryManagement 479 Exercises 482 13 Target Code Generation 489  13.1 Translating Bytecodes 490  13.1.1 Allocating memory addresses 493  13.1.2 Allocating Arrays andObjects 493  13.1.3 Method Calls 496  13.1.4 Example ofBytecodeTranslation 498  13.2 Translating ExpressionTrees 501  13.3 Register Allocation 505  13.3.1 On-the-FlyRegister Allocation 506  13.3.2 RegisterAllocation Using GraphColoring 508  13.3.3 Priority-Based RegisterAllocation 516  13.3.4 Interprocedural RegisterAllocation 517  13.4 Code Scheduling 519  13.4.1 ImprovingCode Scheduling 523  13.4.2 Global andDynamicCodeScheduling 524  13.5 Automatic Instruction Selection 526  13.5.1 InstructionSelection UsingBURS 529  13.5.2 InstructionSelection UsingTwig 531  13.5.3 OtherApproaches 532  13.6 Peephole Optimization 532  13.6.1 Levels ofPeepholeOptimization 533  13.6.2 AutomaticGeneration ofPeepholeOptimizers 536  Exercises 538 14 Program Optimization 547  14.1 Overview 548  14.1.1 WhyOptimize? 549  14.2 Control FlowAnalysis 555  14.2.1 Control FlowGraphs 556  14.2.2 Program andControlFlowStructure 559  14.2.3 DirectProcedureCall Graphs 560  14.2.4 Depth-FirstSpanning Tree 560  14.2.5 Dominance 565  14.2.6 Simple Dominance Algorithm 567  14.2.7 FastDominanceAlgorithm 571  14.2.8 Dominance Frontiers 581  14.2.9 Intervals 585  14.3 Introduction to DataFlowAnalysis 598  14.3.1 Available Expressions 598  14.3.2 LiveVariables 601  14.4 Data FlowFrameworks 604  14.4.1 Data FlowEvaluation Graph 604  14.4.2 Meet Lattice 606  14.4.3 TransferFunctions 608  14.5 Evaluation 611  14.5.1 Iteration 611  14.5.2 Initialization 615  14.5.3 Termination andRapidFrameworks 616  14.5.4 Distributive Frameworks 620  14.6 Constant Propagation 623  14.7 SSA Form 627  14.7.1 Placing φ-Functions 629  14.7.2 Renaming 631 Exercises 636 Bibliography 651 Abbreviations 661 Pseudocode Guide 663 Index

章節(jié)摘錄

  An optimizing compiler is specially designed to produce efficient target codeat the cost of increased compiler complexity and possibly increased compila-tion times. In practice, all production-quality compilers (those whose outputwill be used in everyday work) make some effort to generate reasonable targetcode. For example, no add instruction would normally be generated for theexpression i+O.  The term optimizing compiler is actually a misnomer. This is because nocompiler of any sophistication can produce optimal code for all programs. Thereason for this is twofold. First, theoretical computer science has shown thateven so simple a question as whether two programs are equivalent is undecid-able: such questions cannot generally be answered by arty computer program.Thus finding the simplest (and most efficient) translation of a program cannotalways be done. Second, many program optimizations require time propor-tional to an exponential function of the size of the program being compiled.Thus, optimal code, even when theoretically possible, is often infeasible inpractice.

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