Author

# Alfred V. Aho

Other affiliations: Bell Labs, Alcatel-Lucent, George Mason University

Bio: Alfred V. Aho is an academic researcher from Columbia University. The author has contributed to research in topics: Code generation & Compiler. The author has an hindex of 54, co-authored 137 publications receiving 37917 citations. Previous affiliations of Alfred V. Aho include Bell Labs & Alcatel-Lucent.

##### Papers published on a yearly basis

##### Papers

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01 Jan 1974

TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.

Abstract: From the Publisher:
With this text, you gain an understanding of the fundamental concepts of algorithms, the very heart of computer science. It introduces the basic data structures and programming techniques often used in efficient algorithms. Covers use of lists, push-down stacks, queues, trees, and graphs. Later chapters go into sorting, searching and graphing algorithms, the string-matching algorithms, and the Schonhage-Strassen integer-multiplication algorithm. Provides numerous graded exercises at the end of each chapter.
0201000296B04062001

9,262 citations

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01 Jan 1986

TL;DR: This book discusses the design of a Code Generator, the role of the Lexical Analyzer, and other topics related to code generation and optimization.

Abstract: 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 1.5 Applications of Compiler Technology 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

8,437 citations

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Bell Labs

^{1}TL;DR: A simple, efficient algorithm to locate all occurrences of any of a finite number of keywords in a string of text that has been used to improve the speed of a library bibliographic search program by a factor of 5 to 10.

Abstract: This paper describes a simple, efficient algorithm to locate all occurrences of any of a finite number of keywords in a string of text. The algorithm consists of constructing a finite state pattern matching machine from the keywords and then using the pattern matching machine to process the text string in a single pass. Construction of the pattern matching machine takes time proportional to the sum of the lengths of the keywords. The number of state transitions made by the pattern matching machine in processing the text string is independent of the number of keywords. The algorithm has been used to improve the speed of a library bibliographic search program by a factor of 5 to 10.

3,270 citations

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01 Jan 1983TL;DR: The basis of this book is the material contained in the first six chapters of the earlier work, The Design and Analysis of Computer Algorithms, and has added material on algorithms for external storage and memory management.

Abstract: From the Publisher:
This book presents the data structures and algorithms that underpin much of today's computer programming. The basis of this book is the material contained in the first six chapters of our earlier work, The Design and Analysis of Computer Algorithms. We have expanded that coverage and have added material on algorithms for external storage and memory management. As a consequence, this book should be suitable as a text for a first course on data structures and algorithms. The only prerequisite we assume is familiarity with some high-level programming language such as Pascal.

2,690 citations

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01 Jan 1972

TL;DR: It is the hope that the algorithms and concepts presented in this book will survive the next generation of computers and programming languages, and that at least some of them will be applicable to fields other than compiler writing.

Abstract: From volume 1 Preface (See Front Matter for full Preface)
This book is intended for a one or two semester course in compiling theory at the senior or graduate level. It is a theoretically oriented treatment of a practical subject. Our motivation for making it so is threefold.
(1) In an area as rapidly changing as Computer Science, sound pedagogy demands that courses emphasize ideas, rather than implementation details. It is our hope that the algorithms and concepts presented in this book will survive the next generation of computers and programming languages, and that at least some of them will be applicable to fields other than compiler writing.
(2) Compiler writing has progressed to the point where many portions of a compiler can be isolated and subjected to design optimization. It is important that appropriate mathematical tools be available to the person attempting this optimization.
(3) Some of the most useful and most efficient compiler algorithms, e.g. LR(k) parsing, require a good deal of mathematical background for full understanding. We expect, therefore, that a good theoretical background will become essential for the compiler designer.
While we have not omitted difficult theorems that are relevant to compiling, we have tried to make the book as readable as possible. Numerous examples are given, each based on a small grammar, rather than on the large grammars encountered in practice. It is hoped that these examples are sufficient to illustrate the basic ideas, even in cases where the theoretical developments are difficult to follow in isolation.
From volume 2 Preface (See Front Matter for full Preface)
Compiler design is one of the first major areas of systems programming for which a strong theoretical foundation is becoming available. Volume I of The Theory of Parsing, Translation, and Compiling developed the relevant parts of mathematics and language theory for this foundation and developed the principal methods of fast syntactic analysis. Volume II is a continuation of Volume I, but except for Chapters 7 and 8 it is oriented towards the nonsyntactic aspects of compiler design.
The treatment of the material in Volume II is much the same as in Volume I, although proofs have become a little more sketchy. We have tried to make the discussion as readable as possible by providing numerous examples, each illustrating one or two concepts.
Since the text emphasizes concepts rather than language or machine details, a programming laboratory should accompany a course based on this book, so that a student can develop some facility in applying the concepts discussed to practical problems. The programming exercises appearing at the ends of sections can be used as recommended projects in such a laboratory. Part of the laboratory course should discuss the code to be generated for such programming language constructs as recursion, parameter passing, subroutine linkages, array references, loops, and so forth.

1,727 citations

##### Cited by

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TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.

Abstract: There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and provides an unfamiliar perspective on traditional optimization problems and methods.

41,772 citations

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TL;DR: This paper suggests ways to solve currently open problems in cryptography, and discusses how the theories of communication and computation are beginning to provide the tools to solve cryptographic problems of long standing.

Abstract: Two kinds of contemporary developments in cryptography are examined. Widening applications of teleprocessing have given rise to a need for new types of cryptographic systems, which minimize the need for secure key distribution channels and supply the equivalent of a written signature. This paper suggests ways to solve these currently open problems. It also discusses how the theories of communication and computation are beginning to provide the tools to solve cryptographic problems of long standing.

14,980 citations

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TL;DR: This technique enables the construction of robust key management schemes for cryptographic systems that can function securely and reliably even when misfortunes destroy half the pieces and security breaches expose all but one of the remaining pieces.

Abstract: In this paper we show how to divide data D into n pieces in such a way that D is easily reconstructable from any k pieces, but even complete knowledge of k - 1 pieces reveals absolutely no information about D. This technique enables the construction of robust key management schemes for cryptographic systems that can function securely and reliably even when misfortunes destroy half the pieces and security breaches expose all but one of the remaining pieces.

14,340 citations

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TL;DR: Much of what constitutes the core of scientific knowledge may be regarded as a reservoir of concepts and techniques which can be drawn upon to construct mathematical models of various types of systems and thereby yield quantitative information concerning their behavior.

12,530 citations

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01 Jan 1974

TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.

Abstract: From the Publisher:
With this text, you gain an understanding of the fundamental concepts of algorithms, the very heart of computer science. It introduces the basic data structures and programming techniques often used in efficient algorithms. Covers use of lists, push-down stacks, queues, trees, and graphs. Later chapters go into sorting, searching and graphing algorithms, the string-matching algorithms, and the Schonhage-Strassen integer-multiplication algorithm. Provides numerous graded exercises at the end of each chapter.
0201000296B04062001

9,262 citations