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E-raamat: Data Flow Analysis: Theory and Practice

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(IIT Bombay, Mumbai, India), (IIT Bombay, Mumbai, India), (IIT Bombay, Mumbai, India)
  • Formaat: 395 pages
  • Ilmumisaeg: 19-Dec-2017
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9781351838238
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Data Flow Analysis: Theory and PracticeSuurem pilt
  • Formaat: 395 pages
  • Ilmumisaeg: 19-Dec-2017
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9781351838238
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Data flow analysis is used to discover information for a wide variety of useful applications, ranging from compiler optimizations to software engineering and verification. Modern compilers apply it to produce performance-maximizing code, and software engineers use it to re-engineer or reverse engineer programs and verify the integrity of their programs.

Supplementary Online Materials to Strengthen Understanding

Unlike most comparable books, many of which are limited to bit vector frameworks and classical constant propagation, Data Flow Analysis: Theory and Practice offers comprehensive coverage of both classical and contemporary data flow analysis. It prepares foundations useful for both researchers and students in the field by standardizing and unifying various existing research, concepts, and notations. It also presents mathematical foundations of data flow analysis and includes study of data flow analysis implantation through use of the GNU Compiler Collection (GCC). Divided into three parts, this unique text combines discussions of inter- and intraprocedural analysis and then describes implementation of a generic data flow analyzer (gdfa) for bit vector frameworks in GCC.

Through the inclusion of case studies and examples to reinforce material, this text equips readers with a combination of mutually supportive theory and practice, and they will be able to access the authors accompanying Web page. Here they can experiment with the analyses described in the book, and can make use of updated features, including:











Slides used in the authors courses The source of the generic data flow analyzer (gdfa) An errata that features errors as they are discovered Additional updated relevant material discovered in the course of research

Arvustused

provides a very decent and quite balanced coverage of the topic from a formal perspective. It is well written and nicely organized, containing many examples which definitely help to clarify the rather technical content. All the chapters end with a summary and concluding remarks, as well as bibliographic notes, pointing to further readings. This book also comes with a live web pagethat contains slides with some additional material, [ an updated] Errata section and the analyzer software. This book includes an introduction to GCC, a rich list of references, and an index.

--Zhjzhang Shen, Plymouth State University

Preface v
An Introduction to Data Flow Analysis
1(20)
A Motivating Example
1(11)
Optimizing for Heap Memory
1(3)
Computing Liveness
4(5)
Computing Aliases
9(1)
Performing Optimization
10(1)
General Observations
10(2)
Program Analysis: The Larger Perspective
12(4)
Characteristics of Data Flow Analysis
16(2)
Summary and Concluding Remarks
18(1)
Bibliographic Notes
19(2)
I Intraprocedural Data Flow Analysis
21(210)
Classical Bit Vector Data Flow Analysis
23(36)
Basic Concepts and Notations
23(1)
Discovering Local Data Flow Information
24(2)
Discovering Global Properties of Variables
26(7)
Live Variables Analysis
26(3)
Dead Variables Analysis
29(1)
Reaching Definitions Analysis
29(3)
Reaching Definitions for Copy Propagation
32(1)
Discovering Global Properties of Expressions
33(20)
Available Expressions Analysis
33(3)
Partially Available Expressions Analysis
36(1)
Anticipable Expressions Analysis
37(2)
Classical Partial Redundancy Elimination
39(10)
Lazy Code Motion
49(4)
Combined May-Must Analyses
53(3)
Summary and Concluding Remarks
56(1)
Bibliographic Notes
57(2)
Theoretical Abstractions in Data Flow Analysis
59(42)
Graph Properties Relevant to Data Flow Analysis
59(4)
Data Flow Framework
63(11)
Modeling Data Flow Values Using Lattices
64(7)
Modeling Flow Functions
71(1)
Data Flow Frameworks
72(2)
Data Flow Assignments
74(5)
Meet Over Paths Assignment
75(1)
Fixed Point Assignment
76(1)
Existence of Fixed Point Assignment
77(2)
Computing Data Flow Assignments
79(6)
Computing MFP Assignment
79(2)
Comparing MFP and MOP Assignments
81(2)
Undecidability of MOP Assignment Computation
83(2)
Complexity of Data Flow Analysis for Rapid Frameworks
85(14)
Properties of Data Flow Frameworks
86(4)
Complexity for General CFGs
90(7)
Complexity in Special Cases
97(2)
Summary and Concluding Remarks
99(1)
Bibliographic Notes
100(1)
General Data Flow Frameworks
101(58)
Non-Separable Flow Functions
101(2)
Discovering Properties of Variables
103(16)
Faint Variables Analysis
103(3)
Possibly Uninitialized Variables Analysis
106(2)
Constant Propagation
108(7)
Variants of Constant Propagation
115(4)
Discovering Properties of Pointers
119(16)
Points-To Analysis of Stack and Static Data
119(10)
Alias Analysis of Stack and Static Data
129(3)
Formulating Data Flow Equations for Alias Analysis
132(3)
Liveness Analysis of Heap Data
135(17)
Access Expressions and Access Paths
137(1)
Liveness of Access Paths
138(3)
Representing Sets of Access Paths by Access Graphs
141(5)
Data Flow Analysis for Explicit Liveness
146(5)
The Motivating Example Revisited
151(1)
Modeling Entity Dependence
152(4)
Primitive Entity Functions
153(2)
Composite Entity Functions
155(1)
Summary and Concluding Remarks
156(1)
Bibliographic Notes
156(3)
Complexity of Iterative Data Flow Analysis
159(26)
Generic Flow Functions and Data Flow Equations
159(3)
Generic Round-Robin Iterative Algorithm
162(2)
Complexity of Round-Robin Iterative Algorithm
164(20)
Identifying the Core Work Using Work List
165(6)
Information Flow Paths in Bit Vector Frameworks
171(2)
Defining Complexity Using Information Flow Paths
173(2)
Information Flow Paths in Fast Frameworks
175(4)
Information Flow Paths in Non-separable Frameworks
179(5)
Summary and Concluding Remarks
184(1)
Bibliographic Notes
184(1)
Single Static Assignment Form as Intermediate Representation
185(46)
Introduction
185(4)
An Overview of SSA
186(2)
Benefits of SSA Representation
188(1)
Construction of SSA Form Programs
189(18)
Dominance Frontier
191(3)
Placement of ø-instructions
194(2)
Renaming of Variables
196(2)
Correctness of the Algorithm
198(9)
Destruction of SSA
207(20)
An Algorithm for SSA Destruction
209(7)
SSA Destruction and Register Allocation
216(11)
Summary and Concluding Remarks
227(1)
Bibliographic Notes
228(3)
II Interprocedural Data Flow Analysis
231(100)
Introduction to Interprocedural Data Flow Analysis
233(26)
A Motivating Example
233(1)
Program Representations for Interprocedural Analysis
234(2)
Modeling Interprocedural Data Flow Analysis
236(3)
Summary Flow Functions
236(1)
Inherited and Synthesized Data Flow Information
237(1)
Approaches to Interprocedural Data Flow Analysis
238(1)
Compromising Precision for Scalability
239(5)
Flow and Context Insensitivity
240(4)
Side Effects Analysis
244(1)
Language Features Influencing Interprocedural Analysis
244(2)
Common Variants of Interprocedural Data Flow Analysis
246(8)
Intraprocedural Analysis with Conservative Interprocedural Approximation
246(2)
Intraprocedural Analysis with Side Effects Computation
248(5)
Whole Program Analysis
253(1)
An Aside on Interprocedural Optimizations
254(2)
Summary and Concluding Remarks
256(1)
Bibliographic Notes
256(3)
Functional Approach to Interprocedural Data Flow Analysis
259(34)
Side Effects Analysis of Procedure Calls
259(7)
Computing Flow Sensitive Side Effects
261(2)
Computing Flow Insensitive Side Effects
263(3)
Handling the Effects of Parameters
266(8)
Defining Aliasing of Parameters
267(1)
Formulating Alias Analysis of Parameters
268(3)
Augmenting Data Flow Analyses Using Parameter Aliases
271(2)
Efficient Parameter Alias Analysis
273(1)
Whole Program Analysis
274(16)
Lattice of Flow Functions
274(1)
Reducing Function Compositions and Confluences
275(3)
Constructing Summary Flow Functions
278(4)
Computing Data Flow Information
282(3)
Enumerating Summary Flow Functions
285(5)
Summary and Concluding Remarks
290(1)
Bibliographic Notes
291(2)
Value-Based Approach to Interprocedural Data Flow Analysis
293(38)
Program Model for Value-Based Approaches to Interprocedural Data Flow Analysis
293(3)
Interprocedural Analysis Using Restricted Contexts
296(5)
Interprocedural Analysis Using Unrestricted Contexts
301(10)
Using Call Strings to Represent Unrestricted Contexts
302(3)
Issues in Termination of Call String Construction
305(6)
Bounding Unrestricted Contexts Using Data Flow Values
311(13)
Call String Invariants
311(6)
Value-Based Termination of Call String Construction
317(7)
The Motivating Example Revisited
324(2)
Summary and Concluding Remarks
326(2)
Bibliographic Notes
328(3)
III Implementing Data Flow Analysis
331(40)
Implementing Data Flow Analysis in GCC
333(38)
Specifying a Data Flow Analysis
333(7)
Registering a Pass With the Pass Manager in GCC
334(2)
Specifying Available Expressions Analysis
336(2)
Specifying Other Bit Vector Data Flow Analyses
338(2)
An Example of Data Row Analysis
340(12)
Executing the Data Flow Analyzer
341(1)
Examining the Gimple Version of CFG
342(4)
Examining the Result of Data Flow Analysis
346(6)
Implementing the Generic Data Flow Analyzer gdfa
352(11)
Specification Primitives
352(2)
Interface with GCC
354(4)
The Preparatory Pass
358(1)
Local Data Flow Analysis
358(2)
Global Data Flow Analysis
360(3)
Extending the Generic Data Flow Analyzer gdfa
363(2)
An Introduction to GCC
365(6)
About GCC
365(1)
Building GCC
366(2)
Further Readings in GCC
368(3)
References 371(7)
Index 378
Uday Khedker, Amitabha Sanyal, Bageshri Sathe
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