 | 书 名: 软件质量工程的度量与模型 第2版（影印版）
作 者: Stephen H,Kan
出 版 社: 清华大学出版社
ISBN : 730208839
原 价: ￥49
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Foreword to the Second Edition xiii
Foreword to the First Edition xv
Preface xvii
Chapter 1: What Is Software Quality?
1.I Quality: Popular Views 1
1.2 Quality: Professional Views 2
1.2.1 The Role of the Customer
1.3 Software Quality 4
1.4 Total Quality Management 7
1.5 Summary 1
References 11
Chapter 2: Software Development Process Models 13
2.1 The Waterfall Development Model 14
2.2 The Prototyping Approach 19
2.3 The Spiral Model 21
2.4 The Iterative Development Process Model 24
2.5 The Object-Oriented Development Process 27
2.6 The Cleanroom Methodology 32
2.7 The Defect Prevention Process 35
2.8 Process Maturity Framework and Quality Standards 39
2.8.1 The SEI Process Capability Maturity Model 39
2.8.2 The SPRAssessment 44
2.8.3 The Malcolm Baldrige Assessment 45
2.8.4 ISO9 47
2.9 Summary 51
References 52
Chapter 3: Fundamentals of Measurement Theory 55
3.1 Definition, Operational Definition, and Measurement 55
3.2 Level of Measurement 59
3.3 Some Basic Measures 62
3.4 Reliability and Validity 7
3.5 Measurement Errors 73
3.5.1 Assessing Reliability 75
3.5.2 Correction for Attenuation 76
3.6 Be Careful with Correlation 77
3.7 Criteria for Causality 8
3.8 Summary 82
References 83
Chapter 4: Software Quality Metrics Overview 85
4.1 Product Quality Metrics 86
4.1.1 The Defect Density Metric 87
4.1.2 Customer Problems Metric 96
4.1.3 Customer Satisfaction Metrics 98
4.2 In-Process Quality Metrics 1
4.2.1 Defect Density During Machine Testing 1
4.2.2 Defect Arrival Pattern During Machine Testing 11
4.2.3 Phase-Based Defect Removal Pattern 13
4.2.4 Defect Removal Effectiveness 13
4.3 Metrics for Software Maintenance 15
4.3.1 Fix Backlog and Backlog Management Index 16
4.3.2 Fix Response Time and Fix Responsiveness 17
4.3.3 Percent Delinquent Fixes 18
4.3.4 Fix Quality 19
4.4 Examples of Metrics Programs 11
4.4.1 Motorola 11
4.4.2 Hewlett-Packard 115
4.4.3 IBM Rochester 116
4.5 Collecting Software Engineering Data 117
4.6 Summary 123
References 125
Chapter 5: Applying the Seven Basic Quality Tools
in Software Development 127
5.1 Ishikawas Seven Basic Tools 128
5.2 Checklist 13
5.3 Pareto Diagram 133
5.4 Histogram 136
5.5 Run Charts 138
5.6 Scatter Diagram 14
5.7 Control Chart 143
5.8 Cause-and-Effect Diagram 152
5.9 Relations Diagram 154
5.1 Summary 156
References 158
Chapter 6: Defect Removal Effectiveness 159
6.1 Literature Review 16
6.2 A Closer Look at Defect Removal Effectiveness 164
6.3 Defect Removal Effectiveness and Quality Planning 172
6.3.1 Phase-Based Defect Removal Model 172
6.3.2 Some Characteristics of a Special Case Two-Phase Model 174
6.4 Cost Effectiveness of Phase Defect Removal 177
6.5 Defect Removal Effectiveness and Process Maturity Level 181
6.6 Summary 183
References 184
Chapter 7: The Rayleigh Model 187
7.1 Reliability Models 187
7.2 The Rayleigh Model 189
7.3 Basic Assumptions 192
7.4 Implementation 195
7.5 Reliability and Predictive Validity 23
7.6 Summary 25
References 26
Chapter 8: Exponential Distribution and Reliability Growth Models 27
8.1 The Exponential Model 28
8.2 Reliability Growth Models 211
8.2.1 Jelinski-MorandaModel 212
8.2.2 LittlewoodModels 213
8.2.3 Goel-Okumoto Imperfect Debugging Model 213
8.2.4 Goel-Okumoto Nonhomogeneous Poisson Process Model 213
8.2.5 Musa-Okumoto Logarithmic Poisson Execution Time Model 215
8.2.6 The Delayed S and Inflection S Models 215
8.3 Model Assumptions 216
8.4 Criteria for Model Evaluation 218
8.5 Modeling Process 22
8.6 Test Compression Factor 224
8.7 Estimating the Distribution of Total Defects over Time 226
8.8 Summary 229
References 231
Chapter 9: Quality Management Models 235
9.1 The Rayleigh Model Framework 236
9.2 The Code Integration Pattern 242
9.3 The PTR Submodel 245
9.4 The PTR Arrival/Backlog Projection Model 249
9.5 Reliability Growth Models 254
9.6 Criteria for Model Evaluation 257
9.7 In-Process Metrics and Reports 258
9.8 Orthogonal Defect Classification 266
9.9 Summary 27
References 27
Chapter 1: In.Process Metrics for Software Testing 271
1.1 In-Process Metrics for Software Testing 272
1.1.1 Test Progress S Curve 272
1.1.2 Testing Defect Arrivals over Time 279
1.1.3 Testing Defect Backlog over Time 283
1.1.4 Product Size over Time 285
1.1.5 CPU Utilization during Test 286
1.1.6 System Crashes and Hangs 289
1.1.7 Mean Time to Unplanned IPL 291
1.1.8 Critical Problems: Show Stoppers 293
1.2 In-Process Metrics and Quality Management 294
1.2.1 Effort/Outcome Model 298
1.3 Possible Metrics for Acceptance Testing to Evaluate
Vendor-Developed Software 32
1.4 How DoYou Know Your Product is Good Enough to Ship? 34
1.5 Summary 38
References 39
Chapter 11: Complexity Metrics and Models 311
11.1 Lines of Code 312
11.2 Halsteads Software Science 314
11.3 Cyclomatic Complexity 315
11.4 Syntactic Constructs 318
11.5 Structure Metrics 319
11.6 An Example of Module Design Metrics in Practice 322
11.7 Summary 328
References 329
Chapter 12: Metrics and Lessons Learned for Object-Oriented Projects 331
12.1 Object-Oriented Concepts and Constructs 331
12.2 Design and Complexity Metrics 334
12.2.1 Lorenz Metrics and Rules of Thumb 334
12.2.2 Some Metrics Examples 336
12.2.3 The CK OO Metrics Suite 337
12.2.4 Validation Studies and Further Examples 339
12.3 Productivity Metrics 343
12.4 Quality and Quality Management Metrics 347
12.5 Lessons Learned for OO Projects 351
12.6 Summary 356
References 357
Chapter 13: Availability Metrics 359
13.1 Definition and Measurements of System Availability 36
13.2 Reliability, Availability, and Defect Rate 362
13.3 Collecting Customer Outage Data for Quality Improvement 366
13.4 In-Process Metrics for Outage and Availability 372
13.5 Summary 394
References 394
Chapter 14: Measuring and Analyzing Customer Satisfaction 375
14.1 Customer Satisfaction Surveys 376
14.1.1 Methods of Survey Data Collection 376
14.1.2 Sampling Methods 377
14.1.3 Sample Size 379
14.2 Analyzing SatisfactionData 381
14.2.1 Specific Attributes and Overall Satisfaction 382
14.3 Satisfaction with Company 388
14.4 How Good Is Good Enough? 39
15.5 Summary 41
References 411
Chapter 16: Conducting Software Project Assessments 413
16.1 Audit and Assessment 414
16.2 Software Process Maturity Assessment and Software Project Assessment 415
16.3 Software Process Assessment Cycle 417
16.4 A Proposed Software Project Assessment Method 42
16.4.1 Preparation Phase 421
16.4.2 Facts Gathering Phase 1 422
16.4.3 Questionnaire Customization and Finalization 423
16.4.4 Facts Gathering Phase 2 425
16.4.5 Possible Improvement Opportunities and Recommendations 426
16.4.6 Team Discussions of Assessment Results and Recommendations 428
16.4.7 Assessment Report 429
16.4.8 Summary 433
16.5 Summary 434
References 435
Chapter 17: Dos and Donts of Software Process Improvement 437
17.1 Measuring Process Maturity 438
17.2 Measuring Process Capability 44
17.3 Staged versus Continuous--Debating Religion 44
17.4 Measuring Levels Is Not Enough 441
17.5 Establishing the Alignment Principle 443
17.6 Take Time Getting Faster 444
17.7 Keep It Simple--or Face Decomplexification 446
17.8 Measuring the Value of Process Improvement 447
17.9 Measuring Process Adoption 448
17.1 Measuring Process Compliance 449
17.11 Celebrate The Journey, Not Just the Destination 45
17.12 Summary 451
References 452
Chapter 18: Using Function Point Metrics to Measure
Software Process Improvement 453
18.1 Software Process Improvement Sequences 455
18.1.1 Stage : Software Process Assessment and Baseline 455
18.1.2 Stage 1: Focus on Management Technologies 456
18.1.3 Stage 2: Focus on Software Processes and Methodologies 457
18.1.4 Stage 3: Focus on New Tools and Approaches 457
18.1.5 Stage 4: Focus on Infrastructure and Specialization 457
18.1.6 Stage 5: Focus on Reusability 458
18.1.7 Stage 6: Focus on Industry Leadership 458
18.2 Process Improvement Economies 459
18.3 Measuring Process Improvements at Activity Levels 462
18.4 Summary 466
References 467
Chapter 19: Concluding Remarks 469
19.1 Data Quality Control 47
19.2 Getting Started with a Software Metrics Program 472
19.3 Software Quality Engineering Modeling 475
19.4 Statistical Process Control in Software Development 481
19.5 Measurement and the Future 484
References 485
Appendix: A Project Assessment Questionnaire 487
Index 59
软件质量工程的度量与模型 第2版（影印版）-图书简介:
本书主要介绍了软件质量过程的度量与模型，内容包括质量规划、过程提高与质量控制、过程中(in-process)质量管理、产品工程(设计与代码复杂性)、可靠性评估与预测，以及用户满意度数据分析等。本书不仅阐述了有关软件质量的度量与技术知识，还给出了很多的实际案例分析，完全符合软件工程知识体(SWEBOK)，具有很好的指导性和实用性。
本书可作为软件工程相关专业高年级学生和研究生的教材，同时也是软件工程专业人员的重要参考书。
随着软件规模的日益增大，软件质量问题也日益突出。它不仅决定了软件交付后使用成本的增加和过早退役，而且也是软件开发延期交付、成本飙升，以至于开发失败的主要因素之一。事实上，软件科学和软件工程一直在寻求对软件本质更清晰的认识，试图以更加合理的方法组织和开发软件，在保证高质量的前提下，大量、快速开发软件。所以，各种软件书刊从分析、设计、构造、测试、维护，到管理、配置交付都涉及质量，而且各种构造方法、解决方案、实施规范层出不穷，吸引了从业者大量精力，而直观、系统地介绍软件质量最新研究成果和度量技术的书籍并不多见。本书正是这类较好的图书之一，作者是IBM公司资深研究员StephenH．Kan。
1995年第1版出版后即引起业界广泛关注，第2版在原有13章的基础上增加了当今成熟的软件度量和质量保证技术，如软件测试过程中的度量，面向对象开发中的度量，可用性度量，过程中(in-process)和项目的评估方法，软件过程改进及其功能度量方法，总共达19章。
本书有以下一些特点。
第一，面向工程实践、系统、完整。从软件质量的基本概念开始，介绍度量基本理论，软件开发过程中的各种度量，质量管理，七种基本的质量度量工具，直到上述最新度量方法成果。软件工程实践者可以从中得到直接的帮助。
第二，取材新颖，有一定的学术深度。传统的软件质量度量模型，因其过程编程背景压缩至相当小的篇幅，如McCabe、Halstead模型等，而引入了许多新颖的质量管理与度量模型，如可靠性增长模型，缺陷消除模型等。这些模型有较深厚的概率统计学理论基础，特别对面向对象软件，提供了一批新准则和经验公式，这对研究和开发当前基于构件、Web服务软件的质量度量方法和规范的从业者，无疑是个很好的参照。
第三，本书符合IEEE和ACM21年发布的软件工程知识体(SWEBOK)指南。软件质量一章界定的内容，是计算机专业课程体系制定者很好的参考资料。事实上，本书很适合计算机软件、软件工程学科本科生和研究生的教材。
麦中凡
北京航空航天大学软件学院教授
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