Compilers: Principles, Techniques, and Tools, 2nd edition

Alfred V. Aho Columbia University
Jeffrey D. Ullman Stanford University
Ravi Sethi Avaya Labs
Monica S. Lam Stanford University

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Compilers: Principles, Techniques and Tools (known to professors, students and developers worldwide as the "Dragon Book") is available in a 2nd Edition. Every chapter has been completely revised to reflect developments in software engineering, programming languages, and computer architecture that have occurred since 1986, when the previous edition published. The authors, recognizing that few readers will ever go on to construct a compiler, retain their focus on the broader set of problems faced in software design and software development.

New chapters include Instruction-Level Parallelism (Ch. 10), Optimizing for Parallelism and Locality (Ch. 11), and Interprocedural Analysis (Ch. 12).

Hallmark features of this title

Introduces the theory and practice of compiler design.
Covers topics like context-free grammars, fine state machines, and syntax-directed translation.

New and updated features of this title

All new chapter on Interprocedural analysis, written by world-renowned computer scientist, Monica S.Lam.
Presents the Five Methods for Translation to explain syntax-directed translation.
Illustrates new techniques for data-flow analysis that emphasize the unity of code optimization and other program analysis software.
Uses code optimization to work with parallel machines.
Explains just-in-time compiling with programming languages such as Java.
Discusses garbage collection.
Brings all new material together through new case studies.

1. Introduction

1.1 Language Processors
1.2 The Structure of a Compiler
1.3 The Evolution of Programming Languages
1.4 The Science of Building a Compiler
1.6 Programming Language Basics
1.7 Summary of Chapter 1
1.8 References for Chapter 1

2. A Simple Syntax-Directed Translator

2.1 Introduction
2.2 Syntax Definition
2.3 Syntax-Directed Translation
2.4 Parsing
2.5 A Translator for Simple Expressions
2.6 Lexical Analysis
2.7 Symbol Tables
2.8 Intermediate Code Generation
2.9 Summary of Chapter 2

3. Lexical Analysis

3.1 The Role of the Lexical Analyzer
3.2 Input Buffering
3.3 Specification of Tokens
3.4 Recognition of Tokens
3.5 The Lexical-Analyzer Generator Lex
3.6 Finite Automata
3.7 From Regular Expressions to Automata
3.8 Design of a Lexical-Analyzer Generator
3.9 Optimization of DFA-Based Pattern Matchers
3.10 Summary of Chapter 3
3.11 References for Chapter 3

4. Syntax Analysis

4.1 Introduction
4.2 Context-Free Grammars
4.3 Writing a Grammar
4.4 Top-Down Parsing
4.5 Bottom-Up Parsing
4.6 Introduction to LR Parsing: Simple LR
4.7 More Powerful LR Parsers
4.8 Using Ambiguous Grammars
4.9 Parser Generators
4.10 Summary of Chapter 4
4.11 References for Chapter 4

5. Syntax-Directed Translation

5.1 Syntax-Directed Definitions
5.2 Evaluation Orders for SDD's
5.3 Applications of Syntax-Directed Translation
5.4 Syntax-Directed Translation Schemes
5.5 Implementing L-Attributed SDD's
5.6 Summary of Chapter 5
5.7 References for Chapter 5

6. Intermediate-Code Generation

6.1 Variants of Syntax Trees
6.2 Three-Address Code
6.3 Types and Declarations
6.4 Translation of Expressions
6.5 Type Checking
6.6 Control Flow
6.7 Backpatching
6.8 Switch-Statements
6.9 Intermediate Code for Procedures
6.10 Summary of Chapter 6
6.11 References for Chapter 6

7. Run-Time Environments

7.1 Storage Organization
7.2 Stack Allocation of Space
7.3 Access to Nonlocal Data on the Stack
7.4 Heap Management
7.5 Introduction to Garbage Collection
7.6 Introduction to Trace-Based Collection
7.7 Short-Pause Garbage Collection
7.8 Advanced Topics in Garbage Collection
7.9 Summary of Chapter 7
7.10 References for Chapter 7

8. Code Generation

8.1 Issues in the Design of a Code Generator
8.2 The Target Language
8.3 Addresses in the Target Code
8.4 Basic Blocks and Flow Graphs
8.5 Optimization of Basic Blocks
8.6 A Simple Code Generator
8.7 Peephole Optimization
8.8 Register Allocation and Assignment
8.9 Instruction Selection by Tree Rewriting
8.10 Optimal Code Generation for Expressions
8.11 Dynamic Programming Code-Generation
8.12 Summary of Chapter 8
8.13 References for Chapter 8

9. Machine-Independent Optimizations

9.1 The Principal Sources of Optimization
9.2 Introduction to Data-Flow Analysis
9.3 Foundations of Data-Flow Analysis
9.4 Constant Propagation
9.5 Partial-Redundancy Elimination
9.6 Loops in Flow Graphs
9.7 Region-Based Analysis
9.8 Symbolic Analysis
9.9 Summary of Chapter 9
9.10 References for Chapter 9

10. Instruction-Level Parallelism

10.1 Processor Architectures
10.2 Code-Scheduling Constraints
10.3 Basic-Block Scheduling
10.4 Global Code Scheduling
10.5 Software Pipelining
10.6 Summary of Chapter 10
10.7 References for Chapter 10

11. Optimizing for Parallelism and Locality

11.1 Basic Concepts
11.2 Matrix Multiply: An In-Depth Example
11.3 Iteration Spaces
11.4 Affine Array Indexes
11.5 Data Reuse
11.6 Array Data-Dependence Analysis
11.7 Finding Synchronization-Free Parallelism
11.8 Synchronization Between Parallel Loops
11.9 Pipelining
11.10 Locality Optimizations
11.11 Other Uses of Affine Transforms
11.12 Summary of Chapter 11
11.13 References for Chapter 11

12. Interprocedural Analysis

12.1 Basic Concepts
12.2 Why Interprocedural Analysis?
12.3 A Logical Representation of Data Flow
12.4 A Simple Pointer-Analysis Algorithm
12.5 Context-Insensitive Interprocedural Analysis
12.6 Context-Sensitive Pointer Analysis
12.7 Datalog Implementation by BDD's
12.8 Summary of Chapter 12
12.9 References for Chapter 12

A. A Complete Front End

A.1 The Source Language
A.2 Main
A.3 Lexical Analyzer
A.4 Symbol Tables and Types
A.5 Intermediate Code for Expressions
A.6 Jumping Code for Boolean Expressions
A.7 Intermediate Code for Statements
A.8 Parser
A.9 Creating the Front End

B. Finding Linearly Independent Solutions

Index

Alfred V. Aho is Lawrence Gussman Professor of Computer Science at Columbia University. Professor Aho has won several awards including the Great Teacher Award for 2003 from the Society of Columbia Graduates and the IEEE John von Neumann Medal. He is a member of the National Academy of Engineering and a fellow of the ACM and IEEE.

Monica S. Lam is a Professor of Computer Science at Stanford University, was the Chief Scientist at Tensilica and the founding CEO of moka5. She led the SUIF project which produced one of the most popular research compilers, and pioneered numerous compiler techniques used in industry.

Ravi Sethi launched the research organization in Avaya and is president of Avaya Labs. Previously, he was a senior vice president at Bell Labs in Murray Hill and chief technical officer for communications software at Lucent Technologies. He has held teaching positions at the Pennsylvania State University and the University of Arizona, and has taught at Princeton University and Rutgers. He is a fellow of the ACM.

Jeffrey Ullman is CEO of Gradiance and a Stanford W. Ascherman Professor of Computer Science at Stanford University. His research interests include database theory, database integration, data mining, and education using the information infrastructure. He is a member of the National Academy of Engineering, a fellow of the ACM, and winner of the Karlstrom Award and Knuth Prize.

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