Foreword to the Second Edition.
Foreword to the First Edition
Preface.
1. What Is Software Quality?
Quality: Popular Views.Quality: Professional Views.The Role of the
Customer.Software Quality.Total Quality Management.
2. Software Development Process Models.
The Waterfall Development Model.The Prototyping Approach.The Spiral
Model.The Iterative Development Process Model.The Object-Oriented
Development Process.The Cleanroom Methodology.The Defect Prevention
Process.Process Maturity Framework and Quality Standards.The SEI
Process Capability Maturity Model.The SPR Assessment.The Malcolm
Baldrige Assessment.ISO 9000.
3. Fundamentals in Measurement Theory.
Definition, Operational Definition, and Measurement.Level of
Measurement.Some Basic Measures.Reliability and
Validity.Measurement Errors.Assessing Reliability.Correction for
Attenuation.Be Careful with Correlation.Criteria for Causality.
4. Software Quality Metrics Overview.
Product Quality Metrics.The Defect Density Metric.Customer Problems
Metric.Customer Satisfaction Metrics.In-Process Quality
Metrics.Defect Density During Machine Testing.Defect Arrival
Pattern During Machine Testing.Phase-Based Defect Removal
Pattern.Defect Removal Effectiveness.Metrics for Software
Maintenance.Fix Backlog and Backlog Management Index.Fix Response
Time and Fix Responsiveness.Percent Delinquent Fixes.Fix
Quality.Examples of Metrics Programs.Motorola.Hewlett-Packard.IBM
Rochester.Collecting Software Engineering Data.
5. Applying the Seven Basic Quality Tools in Software
Development.
Ishikawa's Seven Basic Tools.Checklist.Pareto Diagram.Histogram.Run
Charts.Scatter Diagram.Control Chart.Cause-and-Effect
Diagram.Relations Diagram.
6. Defect Removal Effectiveness.
Literature Review.A Closer Look at Defect Removal
Effectiveness.Defect Removal Effectiveness and Quality
Planning.Phase-Based Defect Removal Model.Some Characteristics of a
Special Case Two-Phase Model.Cost Effectiveness of Phase Defect
Removal.Defect Removal Effectiveness and Process Maturity
Level.
7. The Rayleigh Model.
Reliability Models.The Rayleigh Model.Basic
Assumptions.Implementation.Reliability and Predictive Validity.
8. Exponential Distribution and Reliability Growth
Models.
The Exponential Model.Reliability Growth Models.Jelinski-Moranda
Model.Littlewood Models.Goel-Okumoto Imperfect Debugging
Model.Goel-Okumoto Nonhomogeneous Poisson Process
Model.Musa-Okumoto Logarithmic Poisson Execution Time Model.The
Delayed S and Inflection S Models.Model Assumptions.Criteria for
Model Evaluation.Modeling Process.Test Compression
Factor.Estimating the Distribution of Total Defects Over Time.
9. Quality Management Models.
The Rayleigh Model Framework.The Code Integration Pattern.The PTR
Submodel.The PTR Arrival/Backlog Projection Model.Reliability
Growth Models.Criteria for Model Evaluation.In-Process Metrics and
Reports.Orthogonal Defect Classification.
10. In-Process Metrics for Software Testing.
In-Process Metrics for Software Testing.Test Progress S
Curve.Testing Defect Arrivals Over Time.Testing Defect Backlog Over
Time.Product Size Over Time.CPU Utilization During Test.System
Crashes and Hangs.Mean Time to Unplanned IPL.Critical Problems:
Show Stoppers.In-Process Metrics and Quality
Management.Effort/Outcome Model.Possible Metrics for Acceptance
Testing to Evaluate Vendor-Developed Software.How Do You Know Your
Product Is Good Enough to Ship.
11. Complexity Metrics and Models.
Lines of Code.Halstead's Software Science.Cyclomatic
Complexity.Syntactic Constructs.Structure Metrics.An Example of
Module Design Metrics in Practice.
12. Metrics and Lessons Learned for Object-Oriented
Projects.
Object-Oriented Concepts and Constructs.Design and Complexity
Metrics.Lorenz Metrics and Rules of Thumb.Some Metrics Examples.The
CK OO Metrics Suite.Validation Studies and Further
Examples.Productivity Metrics.Quality and Quality Management
Metrics.Lessons Learned for OO Projects.
13. Availability Metrics.
Definition and Measurements of System Availability.Reliability,
Availability, and Defect Rate.Collecting Customer Outage Data for
Quality Improvement.In-Process Metrics for Outage and
Availability.
14. Measuring and Analyzing Customer Satisfaction.
Customer Satisfaction Surveys.Methods of Survey Data
Collection.Sampling Methods.Sample Size.Analyzing Satisfaction
Data.Specific Attributes and Overall Satisfaction.Satisfaction with
Company.How Good Is Good Enough?
15. Conducting In-Process Quality Assessments.
The Preparation Phase.What Data Should I Look At?Don't Overlook
Qualitative DataThe Evaluation Phase.Quantitative DataQualitative
DataEvaluation CriteriaThe Summarization Phase.Summarization
Strategy.The Overall AssessmentRecommendations and Risk
Mitigation.
16. Conducting Software Project Assessments.
Audit and Assessment.Software Process Maturity Assessment and
Software Project Assessment.Software Process Assessment Cycle.A
Proposed Software Project Assessment Method.Preparation Phase.Facts
Gathering Phase 1.Questionnaire Customization and
Finalization.Facts Gathering Phase.Possible Improvement
Opportunities and Recommendations.Team Discussions of Assessment
Results and Recommendations.Assessment Report.Summary.
17. Dos and Don'ts of Software Process Improvement.
Measuring Process Maturity.Measuring Process Capability.Staged
versus Continuous--Debating Religion.Measuring Levels Is Not
Enough.Establishing the Alignment Principle.Take Time Getting
Faster.Keep It Simple—or Face Decomplexification.Measuring the
Value of Process Improvement.Measuring Process Adoption.Measuring
Process Compliance.Celebrate the Journey, Not Just the
Destination.
18. Using Function Point Metrics to Measure Software Process
Improvement.
Software Process Improvement Sequences.Stage 0: Software Process
Assessment and Baseline.Stage 1: Focus on Management
Technologies.Stage 2: Focus on Software Processes and
Methodologies.Stage 3: Focus on New Tools and Approaches.Stage 4:
Focus on Infrastructure and Specialization.Stage 5: Focus on
Reusability.Stage 6: Focus on Industry Leadership.Process
Improvement Economics.Measuring Process Improvements at Activity
Levels.
19. Concluding Remarks.
Data Quality Control.Getting Started with a Software Metrics
Program.Software Quality Engineering Modeling.Statistical Process
Control in Software Development.Measurement and the Future.
Appendix: A Project Assessment Questionnaire
Index. 0201729156T09052002.
Our society has become increasingly reliant on software in the past decade; businesses have learned that measuring the effectiveness of software projects can impact the bottom line; and quality is no longer an advantage in the software marketplace (it is a necessity). For these reasons, the demand for quality in software engineering has taken center stage in the twenty-first century. In this new edition, Stephen Kan presents a thoroughly updated overview and implementation guide for software engineers faced with the challenge of ensuring quality. The book balances theory, techniques, and real-life examples to provide practical guidelines in the practice of quality. Although there are equations and formulas presented, the book's focus remains on helping the reader understand and apply the metrics and models. With this book as a map, readers can navigate through the complex field of quality, and benefit their organization by improving their processes and products.
Stephen H. Kan is Senior Technical Staff Member (STSM) and a technical manager in programming for IBM in Rochester, Minnesota. As process manager of the quality management process in product development for IBM's eServer iSeries software development, his responsibilities include quality goal setting, supplier quality requirements, quality plans, in-process metrics, field quality status, and quality and project assessments. Dr. Kan has been a faculty member of the Master of Science in Software Engineering program at the University of Minnesota since 1998. He is certified by the American Society for Quality as a Quality Engineer, a Reliability Engineer, and a Quality Manager, and by the Project Management Institute as a Project Management Professional.
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