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Full Description
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.
Contents
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 Data The Evaluation Phase. Quantitative Data Qualitative Data Evaluation Criteria The Summarization Phase. Summarization Strategy. The Overall Assessment Recommendations 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.
