Software Engineering A Practitioners Approach Roger S Pressman 2001

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Software Engineering

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Senior Consulting Editor C. L. Liu, National Tsing Hua

University

Consulting Editor Allen B. Tucker, Bowdoin

College

Fundamentals of Computing and Programming

Computer Organization and Architecture

Systems and Languages Theoretical Foundations Software Engineering and

Databases Artificial Intelligence

Networks, Parallel and Distributed Computing Graphics and Visualization The MIT Electrical and

Computer Science Series

Software Engineering and Databases

Atzeni, Ceri, Paraborschi, and Torlone,

Database Systems, 1/e Mitchell, Machine

Learning, 1/e Musa, Iannino,

and Okumoto,

Software Reliability, 1/e

Pressman, Software Engineering: A Beginner’s Guide, 1/e

Pressman, Software

Engineering: A Practioner’s Guide, 5/e

Ramakrishnan/Gehrke, Database Management Systems, 2/e

Schach, Classical and Object-Oriented Software

Engineering with UML and C++, 4/e

Schach, Classical and Object-Oriented Software

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Software Engineering

A P R A C T I T I O N E R ’ S A P P R O A C H

FIFTH EDITION

Roger S. Pressman, Ph.D.

Boston Burr Ridge, IL Dubuque, IA Madison, WI

New York San Francisco St. Louis

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SOFTWARE ENGINEERING

Published by McGraw-Hill, an imprint of The McGraw-Hill Companies, Inc. 1221 Avenue of the Americas, New York, NY, 10020. Copyright/2001, 1997, 1992, 1987, 1982, by The McGraw-Hill Com-panies, Inc. All rights reserved. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of The McGraw-Hill Companies, Inc., including, but not limited to, in any network or other electronic storage or transmission, or broadcast for distance learning.

This book is printed on acid-free paper.

1 2 3 4 5 6 7 8 9 0 DOC/DOC 0 9 8 7 6 5 4 3 2 1 0 ISBN 0073655783

Publisher: Thomas Casson Executive editor: Betsy Jones Developmental editor: Emily Gray Marketing manager: John Wannemacher Project manager: Karen J. Nelson

Production supervisor: Heather Burbridge Coordinator freelance design: Keith McPherson Supplement coordinator: Rose Range

New media: Christopher Styles Cover design: Rhiannon Erwin Cover illustrator: Joseph Gilians

Compositor: Carlisle Communications, Ltd. Typeface: 8.5/13.5 Leawood

Printer: R. R. Donnelley & Sons Company

Library of Congress Cataloging-in-Publication Data Pressman, Roger S.

Software engineering: a practitioner’s approach / Roger S. Pressman.—5th ed. p. cm.— (McGraw-Hill series in computer science)

Includes index. ISBN 0-07-365578-3

1. Software engineering. I. Title. II. Series. QA76.758.P75 2001

005.1—dc21

00-036133 http://www.mhhe.com

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vi

R

oger S. Pressman is an internationally recognized authority in software process improvement and software engineering technologies. For over three decades, he has worked as a software engineer, a manager, a professor, an author, and a consultant, focus-ing on software engineerfocus-ing issues.

As an industry practitioner and manager, Dr. Pressman worked on the development of CAD/CAM systems for advanced engineering and manufacturing applications. He has also held positions with responsibility for scientific and systems programming.

After receiving a Ph.D. in engineering from the University of Connecticut, Dr. Pressman moved to academia where he became Bullard Associate Professor of Computer Engineering at the University of Bridgeport and director of the university's Computer-Aided Design and Manufacturing Center.

Dr. Pressman is currently president of R.S. Pressman & Associates, Inc., a consulting firm specializing in software engineering methods and training. He serves as principle con-sultant, helping companies establish effective software engineering practices. He also designed and developed the company’s software engineering training and process improve-ment products—Essential Software Engineering,a complete video curriculum that is among the industry's most comprehensive treatments of the subject, and Process Advisor,a self-directed system for software engineering process improvement. Both products are used by hundreds of companies worldwide.

Dr. Pressman has written many technical papers, is a regular contributor to industry periodicals, and is author of six books. In addition to Software Engineering: A Practitioner's Approach, he has written A Manager's Guide to Software Engineering(McGraw-Hill), an award-winning book that uses a unique Q&A format to present management guidelines for instituting and understanding software engineering technology; Making Software Engi-neering Happen(Prentice-Hall), the first book to address the critical management problems associated with software process improvement; and Software Shock(Dorset House), a treat-ment that focuses on software and its impact on business and society. Dr. Pressman is on the Editorial Boards of IEEE Software and the Cutter IT Journal,and for many years, was editor of the “Manager” column in IEEE Software.

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vii Preface xxv

PA R T O N E

The Product and the Process

1

C H A P T E R 1 _{The Product} ₃ C H A P T E R 2 _{The Process} ₁₉

PA R T T W O

Managing Software Projects

53

C H A P T E R 3 _{Project Management Concepts} ₅₅ C H A P T E R 4 _{Software Process and Project Metrics} ₇₉ C H A P T E R 5 _{Software Project Planning} ₁₁₃ C H A P T E R 6 _{Risk Analysis and Management} ₁₄₅ C H A P T E R 7 _{Project Scheduling and Tracking} ₁₆₅ C H A P T E R 8 _{Software Quality Assurance} ₁₉₃ C H A P T E R 9 _{Software Configuration Management} ₂₂₅

PA R T T H R E E

Conventional Methods for Software Engineering

243

C H A P T E R 1 0 _{System Engineering} ₂₄₅

C H A P T E R 1 1 _{Analysis Concepts and Principles} ₂₇₁ C H A P T E R 1 2 _{Analysis Modeling} ₂₉₉

C H A P T E R 1 3 _{Design Concepts and Principles} ₃₃₅ C H A P T E R 1 4 _{Architectural Design} ₃₆₅

C H A P T E R 1 5 _{User Interface Design} ₄₀₁ C H A P T E R 1 6 _{Component-Level Design} ₄₂₃ C H A P T E R 1 7 _{Software Testing Techniques} ₄₃₇ C H A P T E R 1 8 _{Software Testing Strategies} ₄₇₇ C H A P T E R 1 9 _{Technical Metrics for Software} ₅₀₇

PA R T F O U R

Object-Oriented Software Engineering

539

C H A P T E R 2 0 _{Object-Oriented Concepts and Principles} ₅₄₁ C H A P T E R 2 1 _{Object-Oriented Analysis} ₅₇₁

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C H A P T E R 2 3 _{Object-Oriented Testing} ₆₃₁

C H A P T E R 2 4 _{Technical Metrics for Object-Oriented Systems} ₆₅₃

PA R T F I V E

Advanced Topics in Software Engineering

671

C H A P T E R 2 5 _{Formal Methods} ₆₇₃

C H A P T E R 2 6 _{Cleanroom Software Engineering} ₆₉₉ C H A P T E R 2 7 _{Component-Based Software Engineering} ₇₂₁ C H A P T E R 2 8 _{Client/Server Software Engineering} ₇₄₇ C H A P T E R 2 9 _{Web Engineering} ₇₆₉

C H A P T E R 3 0 _{Reengineering} ₇₉₉

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ix PA R T O N E — T H E P R O D U C T A N D T H E P R O C E S S 1

C H A P T E R 1 T H E P R O D U C T 3

1.1 The Evolving Role of Software 4 1.2 Software 6

1.2.1 Software Characteristics 6 1.2.2 Software Applications 9 1.3 Software: A Crisis on the Horizon? 11 1.4 Software Myths 12

1.5 Summary 15

REFERENCES 15

PROBLEMS AND POINTS TO PONDER 16

FURTHER READINGS AND INFORMATION SOURCES 17

C H A P T E R 2 T H E P R O C E S S 1 9

2.1 Software Engineering: A Layered Technology 20 2.1.1 Process, Methods, and Tools 20

2.1.2 A Generic View of Software Engineering 21 2.2 The Software Process 23

2.3 Software Process Models 26 2.4 The Linear Sequential Model 28 2.5 The Prototyping Model 30 2.6 The RAD Model 32

2.7 Evolutionary Software Process Models 34 2.7.1 The Incremental Model 35 2.7.2 The Spiral Model 36

2.7.3 The WINWIN Spiral Model 38 2.7.4 The Concurrent Development Model 40 2.8 Component-Based Development 42

2.9 The Formal Methods Model 43 2.10 Fourth Generation Techniques 44 2.11 Process Technology 46 2.12 Product and Process 46 2.13 Summary 47

REFERENCES 47

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PA R T T W O — M A N A G I N G S O F T WA R E P R O J E C T S 5 3

C H A P T E R 3 P R O J E C T M A N A G E M E N T C O N C E P T S 5 5 3.1 The Management Spectrum 56

3.1.1 The People 56 3.1.2 The Product 57 3.1.2 The Process 57 3.1.3 The Project 57

3.2 People 58

3.2.1 The Players 58 3.2.2 Team Leaders 59 3.2.3 The Software Team 60

3.2.4 Coordination and Communication Issues 65 3.3 The Product 67

3.3.1 Software Scope 67 3.3.2 Problem Decomposition 67 3.4 The Process 68

3.4.1 Melding the Product and the Process 69 3.4.2 Process Decomposition 70

3.5 The Project 71 3.6 The W5_{HH Principle} ₇₃ 3.7 Critical Practices 74

3.8 Summary 74

REFERENCES 75

C H A P T E R 4 S O F T WA R E P R O C E S S A N D P R O J E C T M E T R I C S 7 9 4.1 Measures, Metrics, and Indicators 80

4.2 Metrics in the Process and Project Domains 81

4.2.1 Process Metrics and Software Process Improvement 82 4.2.2 Project Metrics 86

4.3 Software Measurement 87

4.3.1 Size-Oriented Metrics 88 4.3.2 Function-Oriented Metrics 89 4.3.3 Extended Function Point Metrics 91 4.4 Reconciling Different Metrics Approaches 94 4.5 Metrics for Software Quality 95

4.5.1 An Overview of Factors That Affect Quality 95 4.5.2 Measuring Quality 96

4.5.3 Defect Removal Efficiency 98

4.6 Integrating Metrics Within the Software Engineering Process 98 4.6.1 Arguments for Software Metrics 99

4.6.2 Establishing a Baseline 100

4.6.3 Metrics Collection, Computation, and Evaluation 100 4.7 Managing Variation: Statistical Quality Control 100

4.8 Metrics for Small Organizations 104 4.9 Establishing a Software Metrics Program 105 4.10 Summary 107

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PROBLEMS AND POINTS TO PONDER 109

C H A P T E R 5 S O F T WA R E P R O J E C T P L A N N I N G 1 1 3 5.1 Observations on Estimating 114 5.2 Project Planning Objectives 115 5.3 Software Scope 115

5.3.1 Obtaining Information Necessary for Scope 116 5.3.2 Feasibility 117

5.3.3 A Scoping Example 118 5.4 Resources 120

5.4.1 Human Resources 121

5.4.2 Reusable Software Resources 121 5.4.3 Environmental Resources 122 5.5 Software Project Estimation 123 5.6 Decomposition Techniques 124

5.6.1 Software Sizing 124 5.6.2 Problem-Based Estimation 126

5.6.3 An Example of LOC-Based Estimation 128 5.6.4 An Example of FP-Based Estimation 129 5.6.4 Process-Based Estimation 130

5.6.5 An Example of Process-Based Estimation 131 5.7 Empirical Estimation Models 132

5.7.1 The Structure of Estimation Models 132

5.7.2 The COCOMO Model 133

5.7.3 The Software Equation 135 5.8 The Make/Buy Decision 136

5.8.1 Creating a Decision Tree 137 5.8.2 Outsourcing 138

5.9 Automated Estimation Tools 139 5.10 Summary 140

REFERENCES 140

C H A P T E R 6 R I S K A N A LY S I S A N D M A N A G E M E N T 1 4 5 6.1 Reactive versus Proactive Risk Strategies 146 6.2 Software Risks 146

6.3 Risk Identification 148

6.3.1 Assessing Overall Project Risk 149 6.3.2 Risk Components and Drivers 149 6.4 Risk Projection 151

6.4.1 Developing a Risk Table 151 6.4.2 Assessing Risk Impact 153 6.4.3 Risk Assessment 154 6.5 Risk Refinement 156

6.6 Risk Mitigation, Monitoring, and Management 156 6.7 Safety Risks and Hazards 158

6.8 The RMMM Plan 159

6.9 Summary 159

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PROBLEMS AND POINTS TO PONDER 161

C H A P T E R 7 P R O J E C T S C H E D U L I N G A N D T R A C K I N G 1 6 5 7.1 Basic Concepts 166

7.1.1 Comments on “Lateness” 167 7.2.1 Basic Principles 168

7.2 The Relationship Between People and Effort 170 7.2.1 An Example 170

7.2.2 An Empirical Relationship 171 7.2.3 Effort Distribution 172

7.3 Defining a Task Set for the Software Project 172 7.3.1 Degree of Rigor 173

7.3.2 Defining Adaptation Criteria 174 7.3.3 Computing a Task Set Selector Value 175

7.3.4 Interpreting the TSS Value and Selecting the Task Set 176 7.4 Selecting Software Engineering Tasks 177

7.5 Refinement of Major Tasks 178 7.6 Defining a Task Network 180 7.7 Scheduling 181

7.7.1 Timeline Charts 182 7.7.2 Tracking the Schedule 185 7.8 Earned Value Analysis 186

7.9 Error Tracking 187 7.10 The Project Plan 189 7.11 Summary 189 REFERENCES 189

PROBLEMS AND POINTS TO PONDER 190

C H A P T E R 8 S O F T WA R E Q U A L I T Y A S S U R A N C E 1 9 3 8.1 Quality Concepts 194

8.1.1 Quality 195 8.1.2 Quality Control 196 8.1.3 Quality Assurance 196 8.1.4 Cost of Quality 196 8.2 The Quality Movement 198 8.3 Software Quality Assurance 199

8.3.1 Background Issues 200 8.3.2 SQA Activities 201 8.4 Software Reviews 202

8.4.1 Cost Impact of Software Defects 203 8.4.2 Defect Amplification and Removal 204 8.5 Formal Technical Reviews 205

8.5.1 The Review Meeting 206

8.5.2 Review Reporting and Record Keeping 207 8.5.3 Review Guidelines 207

8.6 Formal Approaches to SQA 209 8.7 Statistical Software Quality Assurance 209 8.8 Software Reliability 212

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8.9 Mistake-Proofing for Software 214 8.10 The ISO 9000 Quality Standards 216

8.10.1 The ISO Approach to Quality Assurance Systems 217 8.10.2 The ISO 9001 Standard 217

8.11 The SQA Plan 218

8.12 Summary 219

REFERENCES 220

C H A P T E R 9 S O F T WA R E C O N F I G U R AT I O N M A N A G E M E N T 2 2 5 9.1 Software Configuration Management 226

9.1.1 Baselines 227

9.1.2 Software Configuration Items 228 9.2 The SCM Process 230

9.3 Identification of Objects in the Software Configuration 230 9.4 Version Control 232

9.5 Change Control 234 9.6 Configuration Audit 237 9.7 Status Reporting 237 9.8 SCM Standards 238

9.9 Summary 238

REFERENCES 239

PA R T T H R E E — C O N V E N T I O N A L M E T H O D S F O R S O F T WA R E E N G I N E E R I N G 2 4 3

C H A P T E R 1 0 S Y S T E M E N G I N E E R I N G 2 4 5

10.1 Computer-Based Systems 246 10.2 The System Engineering Hierarchy 248

10.2.1 System Modeling 249 10.2.2 System Simulation 251

10.3 Business Process Engineering: An Overview 251 10.4 Product Engineering: An Overview 254 10.5 Requirements Engineering 256

10.5.1 Requirements Elicitation 256

10.5.2 Requirements Analysis and Negotiation 258 10.5.3 Requirements Specification 259

10.5.4 System Modeling 259 10.5.5 Requirements Validation 260 10.5.6 Requirements Management 261 10.6 System Modeling 262

10.7 Summary 265

REFERENCES 267

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C H A P T E R 1 1 A N A LY S I S C O N C E P T S A N D P R I N C I P L E S 2 7 1 11.1 Requirements Analysis 272

11.2 Requirements Elicitation for Software 274 11.2.1 Initiating the Process 274

11.2.2 Facilitated Application Specification Techniques 275 11.2.3 Quality Function Deployment 279

11.2.4 Use-Cases 280 11.3 Analysis Principles 282

11.3.1 The Information Domain 283 11.3.2 Modeling 285

11.3.3 Partitioning 286

11.3.4 Essential and Implementation Views 288 11.4 Software Prototyping 289

11.4.1 Selecting the Prototyping Approach 289 11.4.2 Prototyping Methods and Tools 290 11.5 Specification 291

11.5.1 Specification Principles 291 11.5.2 Representation 292

11.5.3 The Software Requirements Specification 293 11.6 Specification Review 294

11.7 Summary 294 REFERENCES 295

PROBLEMS AND POINTS TO PONDER 296

C H A P T E R 1 2 A N A LY S I S M O D E L I N G 2 9 9

12.1 A Brief History 300

12.2 The Elements of the Analysis Model 301 12.3 Data Modeling 302

12.3.1 Data Objects, Attributes, and Relationships 302 12.3.2 Cardinality and Modality 305

12.3.3 Entity/Relationship Diagrams 307 12.4 Functional Modeling and Information Flow 309

12.4.1 Data Flow Diagrams 311

12.4.2 Extensions for Real-Time Systems 312 12.4.3 Ward and Mellor Extensions 312 12.4.4 Hatley and Pirbhai Extensions 315 12.5 Behavioral Modeling 317

12.6 The Mechanics of Structured Analysis 319

12.6.1 Creating an Entity/Relationship Diagram 319 12.6.2 Creating a Data Flow Model 321

12.6.3 Creating a Control Flow Model 324 12.6.4 The Control Specification 325 12.6.5 The Process Specification 327 12.7 The Data Dictionary 328

12.8 Other Classical Analysis Methods 330 12.9 Summary 331

REFERENCES 331

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C H A P T E R 1 3 D E S I G N C O N C E P T S A N D P R I N C I P L E S 3 3 5 13.1 Software Design and Software Engineering 336 13.2 The Design Process 338

13.2.1 Design and Software Quality 338 13.2.2 The Evolution of Software Design 339 13.3 Design Principles 340

13.4 Design Concepts 341 13.4.1 Abstraction 342 13.4.2 Refinement 343 13.4.3 Modularity 343

13.4.4 Software Architecture 346 13.4.5 Control Hierarchy 347 13.4.6 Structural Partitioning 348 13.4.7 Data Structure 349 13.4.8 Software Procedure 351 13.4.9 Information Hiding 351 13.5 Effective Modular Design 352

13.5.1 Functional Independence 352 13.5.2 Cohesion 353

13.5.3 Coupling 354

13.6 Design Heuristics for Effective Modularity 355 13.7 The Design Model 357

13.8 Design Documentation 358

13.9 Summary 359

REFERENCES 359

C H A P T E R 1 4 A R C H I T E C T U R A L D E S I G N 3 6 5 14.1 Software Architecture 366

14.1.1 What Is Architecture? 366 14.1.2 Why Is Architecture Important? 367 14.2 Data Design 368

14.2.1 Data Modeling, Data Structures, Databases, and the Data Warehouse 368

14.2.2 Data Design at the Component Level 369

14.3 Architectural Styles 371

14.3.1 A Brief Taxonomy of Styles and Patterns 371 14.3.2 Organization and Refinement 374 14.4 Analyzing Alternative Architectural Designs 375

14.4.1 An Architecture Trade-off Analysis Method 375 14.4.2 Quantitative Guidance for Architectural Design 376 14.4.3 Architectural Complexity 378

14.5 Mapping Requirements into a Software Architecture 378 14.5.1 Transform Flow 379

14.5.2 Transaction Flow 380 14.6 Transform Mapping 380

14.6.1 An Example 380 14.6.2 Design Steps 381 14.7 Transaction Mapping 389

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14.8 Refining the Architectural Design 394 14.9 Summary 395

REFERENCES 396

C H A P T E R 1 5 U S E R I N T E R FA C E D E S I G N 4 0 1 15.1 The Golden Rules 402

15.1.1 Place the User in Control 402 15.1.2 Reduce the User’s Memory Load 404 15.1.3 Make the Interface Consistent 404 15.2 User Interface Design 405

15.2.1 Interface Design Models 405 15.2.2 The User Interface Design Process 407 15.3 Task Analysis and Modeling 408

15.4 Interface Design Activities 410

15.4.1 Defining Interface Objects and Actions 410 15.4.2 Design Issues 413

15.5 Implementation Tools 415 15.6 Design Evaluation 416 15.7 Summary 418 REFERENCES 418

PROBLEMS AND POINTS TO PONDER 419

C H A P T E R 1 6 C O M P O N E N T - L E V E L D E S I G N 4 2 3 16.1 Structured Programming 424

16.1.1 Graphical Design Notation 425 16.1.2 Tabular Design Notation 427 16.1.3 Program Design Language 429 16.1.4 A PDL Example 430

16.2 Comparison of Design Notation 432 16.3 Summary 433

REFERENCES 433

C H A P T E R 1 7 S O F T WA R E T E S T I N G T E C H N I Q U E S 4 3 7 17.1 Software Testing Fundamentals 438

17.1.1 Testing Objectives 439 17.1.2 Testing Principles 439 17.1.3 Testability 440 17.2 Test Case Design 443 17.3 White-Box Testing 444 17.4 Basis Path Testing 445

17.4.1 Flow Graph Notation 445 17.4.2 Cyclomatic Complexity 446 17.4.3 Deriving Test Cases 449 17.4.4 Graph Matrices 452 17.5 Control Structure Testing 454

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17.5.2 Data Flow Testing 456 17.5.3 Loop Testing 458 17.6 Black-Box Testing 459

17.6.1 Graph-Based Testing Methods 460 17.6.2 Equivalence Partitioning 463 17.6.3 Boundary Value Analysis 465 17.6.4 Comparison Testing 465 17.6.5 Orthogonal Array Testing 466

17.7 Testing for Specialized Environments, Architectures, and Applications 468 17.7.1 Testing GUIs 469

17.7.2 Testing of Client/Server Architectures 469 17.7.3 Testing Documentation and Help Facilities 469 17.7.4 Testing for Real-Time Systems 470

17.8 Summary 472

REFERENCES 473

C H A P T E R 1 8 S O F T WA R E T E S T I N G S T R AT E G I E S 4 7 7 18.1 A Strategic Approach to Software Testing 478

18.1.1 Verification and Validation 479 18.1.2 Organizing for Software Testing 479 18.1.3 A Software Testing Strategy 480 18.1.4 Criteria for Completion of Testing 482 18.2 Strategic Issues 484

18.3 Unit Testing 485

18.3.1 Unit Test Considerations 485 18.3.2 Unit Test Procedures 487 18.4 Integration Testing 488

18.4.1 Top-down Integration 488 18.4.2 Bottom-up Integration 490 18.4.3 Regression Testing 491 18.4.4 Smoke Testing 492

18.4.5 Comments on Integration Testing 493 18.4.6 Integration Test Documentation 494 18.5 Validation Testing 495

18.5.1 Validation Test Criteria 495 18.5.2 Configuration Review 496 18.5.3 Alpha and Beta Testing 496 18.6 System Testing 496

18.6.1 Recovery Testing 497 18.6.2 Security Testing 497 18.6.3 Stress Testing 498 18.6.4 Performance Testing 498 18.7 The Art of Debugging 499

18.7.1 The Debugging Process 499 18.7.2 Psychological Considerations 500 18.7.3 Debugging Approaches 501

18.8 Summary 502

REFERENCES 503

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C H A P T E R 1 9 T E C H N I C A L M E T R I C S F O R S O F T WA R E 5 0 7 19.1 Software Quality 508

19.1.1 McCall’s Quality Factors 509

19.1.2 FURPS 511

19.1.3 ISO 9126 Quality Factors 513

19.1.4 The Transition to a Quantitative View 513 19.2 A Framework for Technical Software Metrics 514

19.2.1 The Challenge of Technical Metrics 514 19.2.2 Measurement Principles 515

19.2.3 The Attributes of Effective Software Metrics 516 19.3 Metrics for the Analysis Model 517

19.3.1 Function-Based Metrics 518 19.3.2 The Bang Metric 520

19.3.3 Metrics for Specification Quality 522 19.4 Metrics for the Design Model 523

19.4.1 Architectural Design Metrics 523 19.4.2 Component-Level Design Metrics 526 19.4.3 Interface Design Metrics 530 19.5 Metrics for Source Code 531

19.6 Metrics for Testing 532 19.7 Metrics for Maintenance 533 19.8 Summary 534

REFERENCES 534

FURTHER READING AND OTHER INFORMATION SOURCES 537

PA R T F O U R — O B J E C T - O R I E N T E D S O F T WA R E E N G I N E E R I N G 5 3 9

C H A P T E R 2 0 O B J E C T - O R I E N T E D C O N C E P T S A N D P R I N C I P L E S 5 4 1 20.1 The Object-Oriented Paradigm 542

20.2 Object-Oriented Concepts 544 20.2.1 Classes and Objects 546 20.2.2 Attributes 547

20.2.3 Operations, Methods, and Services 548 20.2.4 Messages 548

20.2.5 Encapsulation, Inheritance, and Polymorphism 550 20.3 Identifying the Elements of an Object Model 553

20.3.1 Identifying Classes and Objects 553 20.3.2 Specifying Attributes 557

20.3.3 Defining Operations 558

20.3.4 Finalizing the Object Definition 559 20.4 Management of Object-Oriented Software Projects 560

20.4.1 The Common Process Framework for OO 560 20.4.2 OO Project Metrics and Estimation 562

20.4.3 An OO Estimating and Scheduling Approach 564 20.4.4 Tracking Progress for an OO Project 565 20.5 Summary 566

REFERENCES 566

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C H A P T E R 2 1 O B J E C T - O R I E N T E D A N A LY S I S 5 7 1 21.1 Object-Oriented Analysis 572

21.1.1 Conventional vs. OO Approaches 572 21.1.2 The OOA Landscape 573

21.1.3 A Unified Approach to OOA 575 21.2 Domain Analysis 576

21.2.1 Reuse and Domain Analysis 577 21.2.2 The Domain Analysis Process 577 21.3 Generic Components of the OO Analysis Model 579 21.4 The OOA Process 581

21.4.1 Use-Cases 581

21.4.2 Class-Responsibility-Collaborator Modeling 582 21.4.3 Defining Structures and Hierarchies 588 21.4.4 Defining Subjects and Subsystems 590 21.5 The Object-Relationship Model 591

21.6 The Object-Behavior Model 594

21.6.1 Event Identification with Use-Cases 594 21.6.2 State Representations 595

21.7 Summary 598

REFERENCES 599

C H A P T E R 2 2 O B J E C T - O R I E N T E D D E S I G N 6 0 3 22.1 Design for Object-Oriented Systems 604

22.1.1 Conventional vs. OO Approaches 605 22.1.2 Design Issues 607

22.1.3 The OOD Landscape 608 22.1.4 A Unified Approach to OOD 610 22.2 The System Design Process 611

22.2.1 Partitioning the Analysis Model 612 22.2.2 Concurrency and Subsystem Allocation 613 22.2.3 The Task Management Component 614 22.2.4 The User Interface Component 615 22.2.5 The Data Management Component 615 22.2.6 The Resource Management Component 616 22.2.7 Intersubsystem Communication 616 22.3 The Object Design Process 618

22.3.1 Object Descriptions 618

22.3.2 Designing Algorithms and Data Structures 619 22.3.3 Program Components and Interfaces 621 22.4 Design Patterns 624

22.4.1 Describing a Design Pattern 624 22.4.2 Using Patterns in Design 625 22.5 Object-Oriented Programming 625

22.6 Summary 626

REFERENCES 627

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C H A P T E R 2 3 O B J E C T - O R I E N T E D T E S T I N G 6 3 1 23.1 Broadening the View of Testing 632 23.2 Testing OOA and OOD Models 633

23.2.1 Correctness of OOA and OOD Models 633 23.2.2 Consistency of OOA and OOD Models 634 23.3 Object-Oriented Testing Strategies 636

23.3.1 Unit Testing in the OO Context 636 23.3.2 Integration Testing in the OO Context 637 23.3.3 Validation Testing in an OO Context 637 23.4 Test Case Design for OO Software 637

23.4.1 The Test Case Design Implications of OO Concepts 638 23.4.2 Applicability of Conventional Test Case Design

Methods 638 23.4.3 Fault-Based Testing 639

23.4.4 The Impact of OO Programming on Testing 640 23.4.5 Test Cases and the Class Hierarchy 641 23.4.6 Scenario-Based Test Design 641

23.4.7 Testing Surface Structure and Deep Structure 643 23.5 Testing Methods Applicable at the Class Level 644

23.5.1 Random Testing for OO Classes 644 23.5.2 Partition Testing at the Class Level 644 23.6 Interclass Test Case Design 645

23.6.1 Multiple Class Testing 645

23.6.2 Tests Derived from Behavior Models 647 23.7 Summary 648

REFERENCES 649

C H A P T E R 2 4 T E C H N I C A L M E T R I C S F O R O B J E C T - O R I E N T E D S Y S T E M S 6 5 3

24.1 The Intent of Object-Oriented Metrics 654

24.2 The Distinguishing Characteristics of Object-Oriented Metrics 654 24.2.1 Localization 655

24.2.2 Encapsulation 655 24.2.3 Information Hiding 655 24.2.4 Inheritance 656 24.2.5 Abstraction 656

24.3 Metrics for the OO Design Model 656 24.4 Class-Oriented Metrics 658

24.4.1 The CK Metrics Suite 658

24.4.2 Metrics Proposed by Lorenz and Kidd 661 24.4.3 The MOOD Metrics Suite 662

24.5 Operation-Oriented Metrics 664 24.6 Metrics for Object-Oriented Testing 664 24.7 Metrics for Object-Oriented Projects 665 24.8 Summary 666

REFERENCES 667

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PA R T F I V E — A D VA N C E D T O P I C S I N S O F T WA R E E N G I N E E R I N G 6 7 1

C H A P T E R 2 5 F O R M A L M E T H O D S 6 7 3 25.1 Basic Concepts 674

25.1.1 Deficiencies of Less Formal Approaches 675 25.1.2 Mathematics in Software Development 676 25.1.3 Formal Methods Concepts 677

25.2 Mathematical Preliminaries 682

25.2.1 Sets and Constructive Specification 683 25.2.2 Set Operators 684

25.2.3 Logic Operators 686 25.2.4 Sequences 686

25.3 Applying Mathematical Notation for Formal Specification 687 25.4 Formal Specification Languages 689

25.5 Using Z to Represent an Example Software Component 690 25.6 The Ten Commandments of Formal Methods 693

25.7 Formal Methods—The Road Ahead 694

25.8 Summary 695

REFERENCES 695

C H A P T E R 2 6 C L E A N R O O M S O F T WA R E E N G I N E E R I N G 6 9 9 26.1 The Cleanroom Approach 700

26.1.1 The Cleanroom Strategy 701

26.1.2 What Makes Cleanroom Different? 703 26.2 Functional Specification 703

26.2.1 Black-Box Specification 705 26.2.2 State-Box Specification 705 26.2.3 Clear-Box Specification 706 26.3 Cleanroom Design 706

26.3.1 Design Refinement and Verification 707 26.3.2 Advantages of Design Verification 710 26.4 Cleanroom Testing 712

26.4.1 Statistical Use Testing 712 26.4.2 Certification 714

26.5 Summary 714

REFERENCES 715

C H A P T E R 2 7 C O M P O N E N T - B A S E D S O F T WA R E E N G I N E E R I N G 7 2 1 27.1 Engineering of Component-Based Systems 722

27.2 The CBSE Process 724 27.3 Domain Engineering 725

27.3.1 The Domain Analysis Process 726 27.3.2 Characterization Functions 727

27.3.3 Structural Modeling and Structure Points 728 27.4 Component-Based Development 730

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27.4 2 Component Engineering 734 27.4.3 Analysis and Design for Reuse 734 27.5 Classifying and Retrieving Components 735

27.5.1 Describing Reusable Components 736 27.5.2 The Reuse Environment 738

27.6 Economics of CBSE 739

27.6.1 Impact on Quality, Productivity, and Cost 739 27.6.2 Cost Analysis Using Structure Points 741 27.6.3 Reuse Metrics 741

27.7 Summary 742 REFERENCES 743

PROBLEMS AND POINTS TO PONDER 744

C H A P T E R 2 8 C L I E N T / S E R V E R S O F T WA R E E N G I N E E R I N G 7 4 7 28.1 The Structure of Client/Server Systems 748

28.1.1 Software Components for c/s Systems 750 28.1.2 The Distribution of Software Components 750 28.1.3 Guidelines for Distributing Application Subsystems 752 28.1.4 Linking c/s Software Subsystems 753

28.1.5 Middleware and Object Request Broker Architectures 753 28.2 Software Engineering for c/s Systems 755

28.3 Analysis Modeling Issues 755 28.4 Design for c/s Systems 755

28.4.1 Architectural Design for Client/Server Systems 756 28.4.2 Conventional Design Approaches for Application

Software 757 28.4.3 Database Design 758

28.4.4 An Overview of a Design Approach 759 28.4.5 Process Design Iteration 761

28.5 Testing Issues 761

28.5.1 Overall c/s Testing Strategy 762 28.5.2 c/s Testing Tactics 763 28.6 Summary 764

REFERENCES 764

C H A P T E R 2 9 W E B E N G I N E E R I N G 7 6 9

29.1 The Attributes of Web-Based Applications 771 29.1.1 Quality Attributes 773

29.1.2 The Technologies 773 29.2 The WebE Process 774

29.3 A Framework for WebE 775

29.4 Formulating/Analyzing Web-Based Systems 776 29.4.1 Formulation 776

29.4.2 Analysis 778

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29.6 Testing Web-Based Applications 786 29.7 Management Issues 787

29.7.1 The WebE Team 788 29.7.2 Project Management 789 29.7.3 SCM Issues for WebE 792

29.8 Summary 794

REFERENCES 795

C H A P T E R 3 0 R E E N G I N E E R I N G 7 9 9

30.1 Business Process Reengineering 800 30.1.1 Business Processes 800

30.1.2 Principles of Business Process Reengineering 801 30.1.3 A BPR Model 802

30.1.4 Words of Warning 804 30.2 Software Reengineering 804

30.2.1 Software Maintenance 804

30.2.2 A Software Reengineering Process Model 805 30.3 Reverse Engineering 809

30.3.1 Reverse Engineering to Understand Processing 810 30.3.2 Reverse Engineering to Understand Data 811 30.3.3 Reverse Engineering User Interfaces 812 30.4 Restructuring 813

30.4.1 Code Restructuring 814 30.4.2 Data Restructuring 814 30.5 Forward Engineering 814

30.5.1 Forward Engineering for Client/Server Architectures 816 30.5.2 Forward Engineering for Object-Oriented Architectures 817 30.5.3 Forward Engineering User Interfaces 818

30.6 The Economics of Reengineering 819

30.7 Summary 820

REFERENCES 820

C H A P T E R 3 1 C O M P U T E R - A I D E D S O F T WA R E E N G I N E E R I N G 8 2 5 31.1 What is CASE? 826

31.2 Building Blocks for CASE 826 31.3 A Taxonomy of CASE Tools 828 31.4 Integrated CASE Environments 833 31.5 The Integration Architecture 834 31.6 The CASE Repository 836

31.6.1 The Role of the Repository in I-CASE 836 31.6.2 Features and Content 837

31.7 Summary 841

REFERENCES 842

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C H A P T E R 3 2 T H E R O A D A H E A D 8 4 5

32.1 The Importance of Software—Revisited 846 32.2 The Scope of Change 847

32.3 People and the Way They Build Systems 847 32.4 The "New" Software Engineering Process 848 32.5 New Modes for Representing Information 849 32.6 Technology as a Driver 851

32.7 A Concluding Comment 852 REFERENCES 853

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xxv

W

hen a computer software succeeds—when it meets the needs of the people who use it, when it performs flawlessly over a long period of time, when it is easy to modify and even easier to use—it can and does change things for the better. But when software fails—when its users are dissatisfied, when it is error prone, when it is difficult to change and even harder to use—bad things can and do happen. We all want to build software that makes things better, avoiding the bad things that lurk in the shadow of failed efforts. To succeed, we need discipline when software is designed and built. We need an engineering approach.

In the 20 years since the first edition of this book was written, software engineer-ing has evolved from an obscure idea practiced by a relatively small number of zealots to a legitimate engineering discipline. Today, it is recognized as a subject worthy of serious research, conscientious study, and tumultuous debate. Throughout the indus-try, software engineerhas replaced programmeras the job title of preference. Software process models, software engineering methods, and software tools have been adopted successfully across a broad spectrum of industry applications.

Although managers and practitioners alike recognize the need for a more disci-plined approach to software, they continue to debate the manner in which discipline is to be applied. Many individuals and companies still develop software haphazardly, even as they build systems to service the most advanced technologies of the day. Many professionals and students are unaware of modern methods. And as a result, the quality of the software that we produce suffers and bad things happen. In addi-tion, debate and controversy about the true nature of the software engineering approach continue. The status of software engineering is a study in contrasts. Atti-tudes have changed, progress has been made, but much remains to be done before the discipline reaches full maturity.

The fifth edition of Software Engineering: A Practitioner's Approachis intended to serve as a guide to a maturing engineering discipline. The fifth edition, like the four editions that preceded it, is intended for both students and practitioners, retaining its appeal as a guide to the industry professional and a comprehensive introduction to the student at the upper level undergraduate or first year graduate level. The format and style of the fifth edition have undergone significant change, making the presen-tation more reader-friendly and the content more easily accessible.

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SepaWeb,can be found at http://www.mhhe.com/pressman.Designed to be used in conjunction with the fifth edition of Software Engineering: A Practitioner's Approach, SepaWeb provides a broad array of software engineering resources that will benefit instructors, students, and industry professionals.

Like all Web sites, SepaWeb will evolve over time, but the following major con-tent areas will always be present: (1) a broad array of instructor resourcesincluding a comprehensive on-line Instructor’s Guideand supplementary teaching materials (e.g., slide presentations to supplement lectures, video-based instructional aids); (2) a wide variety of student resourcesincluding an extensive on-line learning center (encompassing study guides, Web-based resources, and self-tests), an evolving col-lection of “tiny tools,” a case study, and additional supplementary content; and (3) a detailed collection of professional resourcesincluding outlines (and samples of) soft-ware engineering documents and other work products, a useful set of softsoft-ware engi-neering checklists, a catalog of software engiengi-neering (CASE) tools, a comprehensive collection of Web-based resources, and an “adaptable process model” that provides a detailed task breakdown of the software engineering process. In addition, Sepa-Web will contain other goodies that are currently in development.

The 32 chapters of the fifth edition have been organized into five parts. This has been done to compartmentalize topics and assist instructors who may not have the time to complete the entire book in one term. Part One, The Product and the Process, presents an introduction to the software engineering milieu. It is intended to intro-duce the subject matter, and more important, to present concepts that will be nec-essary for later chapters. Part Two, Managing Software Projects, presents topics that are relevant to those who plan, manage, and control a software development proj-ect. Part Three, Conventional Methods for Software Engineering, presents the clas-sical analysis, design, and testing methods that some view as the “conventional” school of software engineering. Part Four, Object-Oriented Software Engineering, presents object-oriented methods across the entire software engineering process, including analysis, design, and testing. Part Five, Advanced Software Engineering Topics, presents dedicated chapters that address formal methods, cleanroom soft-ware engineering, component-based softsoft-ware engineering, client/server softsoft-ware engineering, Web engineering, reengineering, and CASE.

The five-part organization of the fifth edition enables an instructor to "cluster" top-ics based on available time and student need. An entire one-term course can be built around one or more of the five parts. For example, a "design course" might empha-size only Part Three or Part Four; a "methods course" might present selected chap-ters in Parts Three, Four, and Five. A "management course" would stress Parts One and Two. By organizing the fifth edition in this way, I attempted to provide an instruc-tor with a number of teaching options. SepaWeb can and should be used to supple-ment the content that is chosen from the book.

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var-ious types of software engineering courses, recommendations for a variety of soft-ware projects to be conducted in conjunction with a course, solutions to selected problems, and a number of teaching aids.

A comprehensive video curriculum, Essential Software Engineering,is available to complement this book. The video curriculum has been designed for industry train-ing and has been modularized to enable individual software engineertrain-ing topics to be presented on an as-needed, when-needed basis. Further information on the video can be obtained by mailing the request card at the back of this book.1

My work on the five editions of Software Engineering: A Practitioner’s Approach has been the longest continuing technical project of my life. Even when the writing stops, information extracted from the technical literature continues to be assimilated and organized. For this reason, my thanks to the many authors of books, papers, and arti-cles as well as a new generation of contributors to electronic media (newsgroups, e-newsletters, and the World Wide Web) who have provided me with additional insight, ideas, and commentary over the past 20 years. Many have been referenced within the pages of each chapter. All deserve credit for their contribution to this rapidly evolv-ing field. I also wish to thank the reviewers of the fifth edition: Donald H. Kraft, Louisiana State University; Panos E. Livadas, University of Florida; Joseph Lambert, Pennsylvania State University; Kenneth L. Modesitt, University of Michigan—Dear-born; and, James Purtilo, University of Maryland. Their comments and criticism have been invaluable. Special thanks and acknowledgement also go to Bruce Maxim of the University of Michigan—Dearborn, who assisted me in developing the Web site that accompanies this book. Bruce is responsible for much of its design and peda-gogical content.

The content of the fifth edition of Software Engineering: A Practitioner's Approach has been shaped by industry professionals, university professors, and students who have used earlier editions of the book and have taken the time to communicate their suggestions, criticisms, and ideas. My thanks to each of you. In addition, my personal thanks go to our many industry clients worldwide, who certainly teach me as much or more than I can teach them.

As the editions of this book have evolved, my sons, Mathew and Michael, have grown from boys to men. Their maturity, character, and success in the real world have been an inspiration to me. Nothing has filled me with more pride. And finally, to Barbara, my love and thanks for encouraging still another edition of "the book."

Roger S. Pressman

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xxviii

T

he fifth edition of Software Engineering: A Practitioner’s Approach(SEPA) has been redesigned to enhance your reading experience and to provide integrated links to the SEPA Web site, http://www.mhhe.com/pressman/. SepaWeb contains a wealth of useful supplementary information for readers of the book and a broad array of resources (e.g., an Instructor’s Guide,classroom slides, and video supplements) for instructors who have adopted SEPA for classroom use.

A comprehensive video curriculum, Essential Software Engineering,is available to com-plement this book. The video curriculum has been designed for industry training and has been modularized to enable individual software engineering topics to be presented on an as-needed, when-needed basis. Further information on the video can be obtained by mail-ing the request card at the back of this book.1

Throughout the book, you will encounter marginal icons that should be interpreted in the following manner:

Used to emphasize an important point in the body of the text.

Practical advice from the real world of software engineering.

Where can I find the answer?

?

XRef Provides an important cross reference within the book.

The keypointicon will help you to find important points quickly.

The adviceicon provides prag-matic guidance that can help you make the right decision or avoid common problems while building software.

The question markicon asks common questions that are answered in the body of the text.

The xreficon will point you to another part of the book where information relevant to the cur-rent discussion can be found.

The quoteicon presents inter-esting quotes that have rele-vance to the topic at hand.

The WebReficon provides direct pointers to important software engineering related Web sites.

The SepaWebpointer indicates that further information about the noted topic is available at the SEPA Web site.

The SepaWeb.checklists icon points you to detailed checklists that will help you to assess the software engineering work you’re doing and the work products you produce.

The SepaWeb.documents icon points you to detailed doc-ument outlines, descriptions and examples contained within the SEPA Web site.

“Important words”

WebRef

For pointers that will take you directly to Web resources

A selected topic

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1

I

n this part of Software Engineering: A Practitioner’s Approach, you’ll

learn about the product that is to be engineered and the process

that provides a framework for the engineering technology. The

following questions are addressed in the chapters that follow:

• What is computer software . . . really?

• Why do we struggle to build high-quality computer-based

systems?

• How can we categorize application domains for computer

software?

• What myths about software still exist?

• What is a “software process”?

• Is there a generic way to assess the quality of a process?

• What process models can be applied to software

develop-ment?

• How do linear and iterative process models differ?

• What are their strengths and weaknesses?

• What advanced process models have been proposed for

soft-ware engineering work?

Once these questions are answered, you’ll be better prepared to

understand the management and technical aspects of the

engi-neering discipline to which the remainder of this book is dedicated.

THE PRODUCT AND

THE PROCESS

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3 K E Y

C O N C E P T S

application categories. . . 9

component-based assembly. . . 8

failure curves. . . 8

history. . . 5

myths. . . 12

reuse. . . 9

software

characteristics. . . . 6

software

engineering . . . 4

wear. . . 7

T

he warnings began more than a decade before the event, but no one paid much attention. With less than two years to the deadline, the media picked up the story. Then government officials voiced their concern, busi-ness and industry leaders committed vast sums of money, and finally, dire warn-ings of pending catastrophe penetrated the public’s consciousness. Software, in the guise of the now-infamous Y2K bug, would fail and, as a result, stop the world as we then knew it.

As we watched and wondered during the waning months of 1999, I couldn’t help thinking of an unintentionally prophetic paragraph contained on the first page of the fourth edition of this book. It stated:

Computer software has become a driving force. It is the engine that drives business decision making. It serves as the basis for modern scientific investigation and engi-neering problem solving. It is a key factor that differentiates modern products and services. It is embedded in systems of all kinds: transportation, medical, telecom-munications, military, industrial processes, entertainment, office products, . . . the list is almost endless. Software is virtually inescapable in a modern world. And as we move into the twenty-first century, it will become the driver for new advances in everything from elementary education to genetic engineering.

1

THE PRODUCT

What is it? Computer software is

the product that software

engi-neers design and build. It

encom-passes programs that execute within a computer

of any size and architecture, documents that encompass hard-copy and virtual forms, and

data that combine numbers and text but also

includes representations of pictorial, video, and

audio information.

Who does it? Software engineers build it, and

virtu-ally everyone in the industrialized world uses it

either directly or indirectly.

Why is it important? Because it affects nearly every

aspect of our lives and has become pervasive in

our commerce, our culture, and our everyday

activities.

What are the steps? You build computer software

like you build any successful product, by

apply-ing a process that leads to a high-quality result

that meets the needs of the people who will use

the product. You apply a software engineering approach.

What is the work product? From the point of view of

a software engineer, the work product is the

pro-grams, documents, and data that are computer software. But from the user’s viewpoint, the work

product is the resultant information that somehow

makes the user’s world better.

How do I ensure that I’ve done it right? Read the remainder of this book, select those ideas

appli-cable to the software that you build, and apply

them to your work.

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In the five years since the fourth edition of this book was written, the role of soft-ware as the “driving force” has become even more obvious. A softsoft-ware-driven Inter-net has spawned its own $500 billion economy. In the euphoria created by the promise of a new economic paradigm, Wall Street investors gave tiny “dot-com” companies billion dollar valuations before these start-ups produced a dollar in sales. New software-driven industries have arisen and old ones that have not adapted to the new driving force are now threatened with extinction. The United States government has litigated against the software’s industry’s largest company, just as it did in earlier eras when it moved to stop monopolistic practices in the oil and steel industries.

Software’s impact on our society and culture continues to be profound. As its importance grows, the software community continually attempts to develop tech-nologies that will make it easier, faster, and less expensive to build high-quality com-puter programs. Some of these technologies are targeted at a specific application domain (e.g., Web-site design and implementation); others focus on a technology domain (e.g., object-oriented systems); and still others are broad-based (e.g., oper-ating systems such as LINUX). However, we have yet to develop a software technol-ogy that does it all, and the likelihood of one arising in the future is small. And yet, people bet their jobs, their comfort, their safety, their entertainment, their decisions, and their very lives on computer software. It better be right.

This book presents a framework that can be used by those who build computer software—people who must get it right. The technology encompasses a process, a set of methods, and an array of tools that we call software engineering.

1 . 1

T H E E V O LV I N G R O L E O F S O F T WA R E

Today, software takes on a dual role. It is a product and, at the same time, the vehi-cle for delivering a product. As a product, it delivers the computing potential embod-ied by computer hardware or, more broadly, a network of computers that are accessible by local hardware. Whether it resides within a cellular phone or operates inside a mainframe computer, software is an information transformer—producing, manag-ing, acquirmanag-ing, modifymanag-ing, displaymanag-ing, or transmitting information that can be as sim-ple as a single bit or as comsim-plex as a multimedia presentation. As the vehicle used to deliver the product, software acts as the basis for the control of the computer (oper-ating systems), the communication of information (networks), and the creation and control of other programs (software tools and environments).

Software delivers the most important product of our time—information. Software transforms personal data (e.g., an individual’s financial transactions) so that the data can be more useful in a local context; it manages business information to enhance competitiveness; it provides a gateway to worldwide information networks (e.g., Inter-net) and provides the means for acquiring information in all of its forms.

The role of computer software has undergone significant change over a time span of little more than 50 years. Dramatic improvements in hardware performance, pro-“Ideas and

technological discoveries are the driving engines of economic growth.” The Wall Street Journal

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found changes in computing architectures, vast increases in memory and storage capacity, and a wide variety of exotic input and output options have all precipitated more sophisticated and complex computer-based systems. Sophistication and com-plexity can produce dazzling results when a system succeeds, but they can also pose huge problems for those who must build complex systems.

Popular books published during the 1970s and 1980s provide useful historical insight into the changing perception of computers and software and their impact on our culture. Osborne [OSB79] characterized a "new industrial revolution." Toffler [TOF80] called the advent of microelectronics part of "the third wave of change" in human history, and Naisbitt [NAI82] predicted a transformation from an industrial society to an "information society." Feigenbaum and McCorduck [FEI83] suggested that information and knowledge (controlled by computers) would be the focal point for power in the twenty-first century, and Stoll [STO89] argued that the "electronic community" created by networks and software was the key to knowledge interchange throughout the world.

As the 1990s began, Toffler [TOF90] described a "power shift" in which old power structures (governmental, educational, industrial, economic, and military) disinte-grate as computers and software lead to a "democratization of knowledge." Yourdon [YOU92] worried that U.S. companies might loose their competitive edge in software-related businesses and predicted “the decline and fall of the American programmer.” Hammer and Champy [HAM93] argued that information technologies were to play a pivotal role in the “reengineering of the corporation.” During the mid-1990s, the per-vasiveness of computers and software spawned a rash of books by “neo-Luddites” (e.g., Resisting the Virtual Life,edited by James Brook and Iain Boal and The Future

Does Not Computeby Stephen Talbot). These authors demonized the computer,

empha-sizing legitimate concerns but ignoring the profound benefits that have already been realized. [LEV95]

During the later 1990s, Yourdon [YOU96] re-evaluated the prospects for the software professional and suggested the “the rise and resurrection” of the Ameri-can programmer. As the Internet grew in importance, his change of heart proved to be correct. As the twentieth century closed, the focus shifted once more, this time to the impact of the Y2K “time bomb” (e.g., [YOU98b], [DEJ98], [KAR99]). Although the predictions of the Y2K doomsayers were incorrect, their popular writings drove home the pervasiveness of software in our lives. Today, “ubiquitous computing” [NOR98] has spawned a generation of information appliances that have broadband connectivity to the Web to provide “a blanket of connectedness over our homes, offices and motorways” [LEV99]. Software’s role continues to expand.

The lone programmer of an earlier era has been replaced by a team of software specialists, each focusing on one part of the technology required to deliver a com-plex application. And yet, the same questions asked of the lone programmer are being asked when modern computer-based systems are built:

“For I dipped into the future, far as the human eye could see, Saw the vision of the world, and all the wonder that would be.” Tennyson

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• Why does it take so long to get software finished?

• Why are development costs so high?

• Why can't we find all the errors before we give the software to customers?

• Why do we continue to have difficulty in measuring progress as software is being developed?

These, and many other questions,1_{are a manifestation of the concern about} soft-ware and the manner in which it is developed—a concern that has lead to the adop-tion of software engineering practice.

1 . 2

S O F T WA R E

In 1970, less than 1 percent of the public could have intelligently described what "computer software" meant. Today, most professionals and many members of the public at large feel that they understand software. But do they?

A textbook description of software might take the following form: Software is (1) instructions (computer programs) that when executed provide desired function and per-formance, (2) data structures that enable the programs to adequately manipulate infor-mation, and (3) documents that describe the operation and use of the programs. There is no question that other, more complete definitions could be offered. But we need more than a formal definition.

1.2.1

Software Characteristics

To gain an understanding of software (and ultimately an understanding of software engineering), it is important to examine the characteristics of software that make it different from other things that human beings build. When hardware is built, the human creative process (analysis, design, construction, testing) is ultimately trans-lated into a physical form. If we build a new computer, our initial sketches, formal design drawings, and breadboarded prototype evolve into a physical product (chips, circuit boards, power supplies, etc.).

Software is a logical rather than a physical system element. Therefore, software has characteristics that are considerably different than those of hardware:

1. Software is developed or engineered, it is not manufactured in the classical sense.

Although some similarities exist between software development and hardware man-ufacture, the two activities are fundamentally different. In both activities, high qual-How should

we define software?

?

1 In an excellent book of essays on the software business, Tom DeMarco [DEM95] argues the coun-terpoint. He states: “Instead of asking ‘why does software cost so much?’ we need to begin ask-ing ‘What have we done to make it possible for today’s software to cost so little?’ The answer to that question will help us continue the extraordinary level of achievement that has always distin-guished the software industry.”

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ity is achieved through good design, but the manufacturing phase for hardware can introduce quality problems that are nonexistent (or easily corrected) for software. Both activities are dependent on people, but the relationship between people applied and work accomplished is entirely different (see Chapter 7). Both activities require the construction of a "product" but the approaches are different.

Software costs are concentrated in engineering. This means that software proj-ects cannot be managed as if they were manufacturing projproj-ects.

2. Software doesn't "wear out."

Figure 1.1 depicts failure rate as a function of time for hardware. The relationship, often called the "bathtub curve," indicates that hardware exhibits relatively high fail-ure rates early in its life (these failfail-ures are often attributable to design or manufac-turing defects); defects are corrected and the failure rate drops to a steady-state level (ideally, quite low) for some period of time. As time passes, however, the failure rate rises again as hardware components suffer from the cumulative affects of dust, vibra-tion, abuse, temperature extremes, and many other environmental maladies. Stated simply, the hardware begins to wear out.

Software is not susceptible to the environmental maladies that cause hardware to wear out. In theory, therefore, the failure rate curve for software should take the form of the “idealized curve” shown in Figure 1.2. Undiscovered defects will cause high failure rates early in the life of a program. However, these are corrected (ideally, without intro-ducing other errors) and the curve flattens as shown.The idealized curve is a gross over-simplification of actual failure models (see Chapter 8 for more information) for software. However, the implication is clear—software doesn't wear out. But it does deteriorate!

This seeming contradiction can best be explained by considering the “actual curve” shown in Figure 1.2. During its life, software will undergo change (maintenance). As

“Wear out” “Infant

mortality”

Time

Failure rate

F I G U R E 1.1 Failure curve for hardware

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changes are made, it is likely that some new defects will be introduced, causing the failure rate curve to spike as shown in Figure 1.2. Before the curve can return to the original steady-state failure rate, another change is requested, causing the curve to spike again. Slowly, the minimum failure rate level begins to rise—the software is deteriorating due to change.

Another aspect of wear illustrates the difference between hardware and software. When a hardware component wears out, it is replaced by a spare part. There are no software spare parts. Every software failure indicates an error in design or in the process through which design was translated into machine executable code. There-fore, software maintenance involves considerably more complexity than hardware maintenance.

3. Although the industry is moving toward component-based assembly, most software continues to be custom built.

Consider the manner in which the control hardware for a computer-based product is designed and built. The design engineer draws a simple schematic of the digital circuitry, does some fundamental analysis to assure that proper function will be achieved, and then goes to the shelf where catalogs of digital components exist. Each integrated circuit (called an ICor a chip) has a part number, a defined and validated function, a well-defined interface, and a standard set of integration guidelines. After each component is selected, it can be ordered off the shelf.

As an engineering discipline evolves, a collection of standard design components is created. Standard screws and off-the-shelf integrated circuits are only two of thou-sands of standard components that are used by mechanical and electrical engineers as they design new systems. The reusable components have been created so that the engineer can concentrate on the truly innovative elements of a design, that is, the F I G U R E 1.2

Idealized and actual failure curves for software

Increased failure rate due to side

effects

Time

Failure rate Change

Actual curve

Idealized curve

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parts of the design that represent something new. In the hardware world, component reuse is a natural part of the engineering process. In the software world, it is some-thing that has only begun to be achieved on a broad scale.

A software component should be designed and implemented so that it can be reused in many different programs. In the 1960s, we built scientific subroutine libraries that were reusable in a broad array of engineering and scientific applications. These subroutine libraries reused well-defined algorithms in an effective manner but had a limited domain of application. Today, we have extended our view of reuse to encom-pass not only algorithms but also data structure. Modern reusable components encap-sulate both data and the processing applied to the data, enabling the software engineer to create new applications from reusable parts. For example, today's graphical user interfaces are built using reusable components that enable the creation of graphics windows, pull-down menus, and a wide variety of interaction mechanisms. The data structure and processing detail required to build the interface are contained with a library of reusable components for interface construction.

1.2.2

Software Applications

Software may be applied in any situation for which a prespecified set of procedural steps (i.e., an algorithm) has been defined (notable exceptions to this rule are expert system software and neural network software). Information content and determinacy are important factors in determining the nature of a software application. Content refers to the meaning and form of incoming and outgoing information. For example, many business applications use highly structured input data (a database) and pro-duce formatted “reports.” Software that controls an automated machine (e.g., a numerical control) accepts discrete data items with limited structure and produces individual machine commands in rapid succession.

Information determinacy refers to the predictability of the order and timing of infor-mation. An engineering analysis program accepts data that have a predefined order, executes the analysis algorithm(s) without interruption, and produces resultant data in report or graphical format. Such applications are determinate. A multiuser oper-ating system, on the other hand, accepts inputs that have varied content and arbi-trary timing, executes algorithms that can be interrupted by external conditions, and produces output that varies as a function of environment and time. Applications with these characteristics are indeterminate.

It is somewhat difficult to develop meaningful generic categories for software appli-cations. As software complexity grows, neat compartmentalization disappears. The following software areas indicate the breadth of potential applications:

System software. System software is a collection of programs written to service

other programs. Some system software (e.g., compilers, editors, and file manage-ment utilities) process complex, but determinate, information structures. Other sys-tems applications (e.g., operating system components, drivers, telecommunications XRef

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processors) process largely indeterminate data. In either case, the system software area is characterized by heavy interaction with computer hardware; heavy usage by multiple users; concurrent operation that requires scheduling, resource sharing, and sophisticated process management; complex data structures; and multiple external interfaces.

Real-time software. Software that monitors/analyzes/controls real-world events

as they occur is called real time. Elements of real-time software include a data gath-ering component that collects and formats information from an external environ-ment, an analysis component that transforms information as required by the application, a control/output component that responds to the external environment, and a monitoring component that coordinates all other components so that real-time response (typically ranging from 1 millisecond to 1 second) can be maintained.

Business software. Business information processing is the largest single software

application area. Discrete "systems" (e.g., payroll, accounts receivable/payable, inven-tory) have evolved into management information system (MIS) software that accesses one or more large databases containing business information. Applications in this area restructure existing data in a way that facilitates business operations or man-agement decision making. In addition to conventional data processing application, business software applications also encompass interactive computing (e.g., point-of-sale transaction processing).

Engineering and scientific software. Engineering and scientific software have

been characterized by "number crunching" algorithms. Applications range from astron-omy to volcanology, from automotive stress analysis to space shuttle orbital dynam-ics, and from molecular biology to automated manufacturing. However, modern applications within the engineering/scientific area are moving away from conven-tional numerical algorithms. Computer-aided design, system simulation, and other interactive applications have begun to take on real-time and even system software characteristics.

Embedded software. Intelligent products have become commonplace in nearly

every consumer and industrial market. Embedded software resides in read-only mem-ory and is used to control products and systems for the consumer and industrial mar-kets. Embedded software can perform very limited and esoteric functions (e.g., keypad control for a microwave oven) or provide significant function and control capability (e.g., digital functions in an automobile such as fuel control, dashboard displays, and braking systems).

Personal computer software. The personal computer software market has

bur-geoned over the past two decades. Word processing, spreadsheets, computer graph-ics, multimedia, entertainment, database management, personal and business financial applications, external network, and database access are only a few of hundreds of applications.

Web-based software. The Web pages retrieved by a browser are software that

incorporates executable instructions (e.g., CGI, HTML, Perl, or Java), and data (e.g.,

One of the most comprehensive libraries of shareware/freeware can be found at

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hypertext and a variety of visual and audio formats). In essence, the network becomes a massive computer providing an almost unlimited software resource that can be accessed by anyone with a modem.

Artificial intelligence software. Artificial intelligence (AI) software makes use

of nonnumerical algorithms to solve complex problems that are not amenable to computation or straightforward analysis. Expert systems, also called knowledge-based systems, pattern recognition (image and voice), artificial neural networks, theorem proving, and game playing are representative of applications within this category.

1 . 3 S O F T WA R E : A C R I S I S O N T H E H O R I Z O N ?

Many industry observers (including this author) have characterized the problems associated with software development as a "crisis." More than a few books (e.g., [GLA97], [FLO97], [YOU98a]) have recounted the impact of some of the more spec-tacular software failures that have occurred over the past decade. Yet, the great suc-cesses achieved by the software industry have led many to question whether the term

software crisisis still appropriate. Robert Glass, the author of a number of books on

software failures, is representative of those who have had a change of heart. He states [GLA98]: “I look at my failure stories and see exception reporting, spectacular fail-ures in the midst of many successes, a cup that is [now] nearly full.”

It is true that software people succeed more often than they fail. It also true that the software crisis predicted 30 years ago never seemed to materialize. What we really have may be something rather different.

The word crisisis defined in Webster's Dictionaryas “a turning point in the course of anything; decisive or crucial time, stage or event.” Yet, in terms of overall software qual-ity and the speed with which computer-based systems and products are developed, there has been no "turning point," no "decisive time," only slow, evolutionary change, punctuated by explosive technological changes in disciplines associated with software.

The word crisishas another definition: "the turning point in the course of a disease, when it becomes clear whether the patient will live or die." This definitio