A measurement methodology based on the core precepts of Software Engineering Describes lessons learned during on-site research and application of software quality measurement Discusses how to reach the desirable end result, while most other models and assessment procedures for software quality tend only to concentrate on the end result An holistic approach to software quality measurement Goes beyond the all-encompassing answers to the "why" and "what" questions Offers specific, viable suggestions to help you deal with difficult problems.

Describes a process supporting software quality assessment and prediction and how to get there.

Autorentext
Research motivated by problems arising in large, complex software systems is what stimulates Richard Nance. His collaboration with the U.S. Navy on major software-intensive programs spans over 30 years. James Arthur is an Associate Professor of Computer Science at Virginia Tech.

Inhalt

1. Motivating Software Quality Meaurement.- 1.1 Software Measurement: Why, What, How and When.- 1.2 Frequent and Hidden Pitfalls.- 1.3 The Rationale of an Holistic Approach.- 1.4 Background Efforts Contributing to the Book Content.- 1.5 Purpose and Scope of the Book.- 2. Foundations for a Comprehensive Approach to Software Quality Assessment.- 2.1 Establishing a Quality Focus.- 2.2 The Objectives/Principles/Attributes (OPA) Framework.- 2.3 Software Quality Indicators.- 2.4 Influences of the Process Model.- 2.5 Establishing Measurement Goals: Assessment or Prediction.- 3. An OPA Measurement Program.- 3.1 Accommodating the Organizational Process Model.- 3.2 Measurement Program Responsibilities.- 3.3 Derivation of Software Quality Indicators.- 3.4 Interpretation of SQI Results.- 3.5 Decisions and Actions.- 4. Process Measurement.- 4.1 The Inherent Difficulty of Process Measurement.- 4.2 Indicator Derivation and Distinctions.- 4.3 Interpretation, Decisions and Actions.- 5. Product Measurement: Documentation.- 5.1 Motivation and Distinctions.- 5.2 The Characteristics of High Quality in Documentation.- 5.3 Measurement Approaches.- 5.4 Interpretation, Decisions and Actions.- 6. Product Measurement: Code.- 6.1 Indicator Distinction and Derivation.- 6.2 Attributes of Code Quality.- 6.3 Automated Collection of Code Indicators.- 6.4 Interpretation, Decisions and Actions.- 7. An Examination of Indicator Values and Their Aggregation.- 7.1 Using and Interpreting Indicator Values.- 7.2 Integrating Code, Documentation and Process Quality Indicators in a Software Quality Measurement Program.- 8. Prediction and Assessment: Differences in Goals.- 8.1 Effects of Process Models.- 8.2 Software Reuse.- 8.3 Sustaining Responsibilities and Quality Measurement.- 8.4 The Quality Database and Validity of Indicators.- 9. Software Quality: Views and Purviews.- 9.1 Software Quality: Holy Grail or Eternal Enigma?.- 9.2 What is Quality?.- 9.3 What about Software?.- 9.4 The Evolving Views of Software Quality.- 9.5 Software Quality: A Standard View.- References.