Pragmatic Quality Metrics for Evolutionary Software Development Models

Abstract

Due to the large number of product, project and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1991
Accession Number
ADA243022

Entities

People

  • Walker Royce

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Business Administration
  • Computer Programming
  • Computer Programs
  • Computers
  • Configuration Management
  • Control Systems Engineering
  • Databases
  • Engineering
  • Language
  • Life Cycles
  • Quality Control
  • Software Development
  • Software Metrics
  • Standards
  • Statistics
  • Systems Engineering

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Modeling and Simulation
  • Organizational Process Management (OPM).
  • Theoretical Analysis.