Metrics and Models in Software Quality Engineering

Abstract

Chapter 1, What Is Software Quality?, discusses the definition of quality and software quality. The customers role in the definition is highlighted. Quality attributes and their interrelationships are discussed. In the second part of the chapter covers the definition and framework of TQM and the customers view of quality, a key focus in this book. Chapter 2, Software Development Process Model, reviews various development process models that are used in the software industry. It briefly describes two methods of software process maturity assessmentthe Carnegie Mellon Universitys Software Engineering Institutes (SEI) process Capability Maturity Model (CMM) and the Software Productivity Research (SPR) assessment method. It summarizes two bodies of quality management standardsthe Malcolm Baldrige National Quality Award assessment discipline and ISO 9000. Chapter 3, Fundamentals in Measurement Theory, examines measurement theory fundamentals, which are very important for the practice of software measurement. The concept of operational definition and its importance in measurement are illustrated with an example. The level of measurement, some basic measures, and the concept of six sigma are discussed. The two key criteria of measurement quality, reliability and validity, and the related issue of measurement errors are examined and their importance is articulated. This chapter also provides a discussion on correlation and addresses the criteria needed to establish causality based on observational data. Chapter 4, Software Quality Metrics Overview, presents examples of quality metrics for the three categories of metrics associated with the software life-cycle: end-product, in-process, and maintenance. It describes the metrics programs of several large software companies and discusses software engineering data collection. Chapter 5, Applying the Seven Basic Quality Tools in Software Development, describes the application of the basic statistical tools for quality control, known as Ishikawas seven basic tools, in software development. The potentials and challenges of applying the control chart in software environments are discussed. In addition, a qualitative tool for brainstorming and for displaying complex cause-and-effect relationshipsthe relations diagramis discussed. Chapter 6, Defect Removal Effectiveness, is the first of five chapters about the models and metrics that describe the quality dynamics of software development. Through two types of models, quality management models and software reliability and projection models, the quality of software development can be planned, engineered, managed, and projected. This chapter examines the central concept of defect-removal effectiveness, its measurements, and its role in quality planning. Chapter 7, The Rayleigh Model, describes the model and its implementation as a reliability and projection model. The Rayleigh Models use as a quality management model is discussed in Chapter 9. Chapter 8, Exponential Distribution and Reliability Growth Models, discusses the exponential distribution and the major software reliability growth models. These models, like the Rayleigh Model, are used for quality projection before the software is shipped to customers, just before development is complete. The models are also used to model the failure pattern or the defect arrival patterns in the field, for maintenance planning. Chapter 9, Quality Management Models, describes several quality management models that cover the entire development cycle. In-process metrics and reports that support the models are shown and discussed. A framework for interpreting in-process metrics and assessing in-process quality statusthe Effort/Outcome model, is presented. Chapter 10, In-Process Metrics for Software Testing, is a continuation of Chapter 9; it focuses on the metrics for software testing. The Effort/Outcome model, as it applies to metrics during the testing phase, is elaborated. Candidate metrics for acceptance testing to evaluate vendor-developed software, and the central question of how do you know your product is good enough to ship, are also discussed. Chapter 11, Complexity Metrics and Models, discusses the third type of metrics and models in software engineering. While quality management models and reliability and projection models are for project management and quality management, the objective of the complexity metrics and models is for software engineers to be able to improve their design and implementation of software development. Chapter 12, Metrics and Lessons Learned for Object-Oriented Projects, covers design and complexity metrics, productivity metrics, quality and quality management metrics for object-oriented development, and lessons learned from the deployment and implementation of OO projects. The first section can be viewed as a continuation of the discussion on complexity metrics and models, while the other sections fall within the framework of quality and project management. Chapter 13, Availability Metrics, discusses system availability and outage metrics, and explores the relationships among availability, reliability, and the traditional defect-rate measurement. Availability metrics and customer satisfaction measurements are the fourth type of metrics and modelscustomer-oriented metrics. Chapter 14, Measuring and Analyzing Customer Satisfaction, discusses customer satisfaction data collection and measurements, and techniques and models for the analysis of customer satisfaction data. From Chapter 3 to this chapter, the entire spectrum of metrics and models is covered. Chapter 15, Conducting In-Process Quality Assessments, describes in-process quality assessments as an integrated element of good project quality management. Quality assessments are based on both quantitative indicators, such as those discussed in previous chapters, and qualitative information. Chapter 16, Conducting Software Project Assessments, takes the level of discussion yet another level higher; this chapter proposes a software project assessment method. The focus is at the project level and the discussion is from a practitioners perspective. Chapter 17, Dos and Donts of Software Process Improvement by Patrick OToole, offers practical advice for software process improvement professionals. It provides a link to the process maturity discussions in Chapter 2. Chapter 18, Measuring Software Process Improvement by Capers Jones, discusses the six stages of software process improvement. Based on a large body of empirical data, it examines the costs and effects of process improvement. It shows the results of quantitative analyses with regard to costs, time, schedule, productivity, and quality. It provides a link to the process maturity discussions in Chapter 2. Chapter 19, Concluding Remarks, provides several observations with regard to software measurement in general and software quality metrics and models in particular, and it offers a perspective on the future of software engineering measurement.