Management challenges and techniques on a large Ada project
TRI-Ada '91 Proceedings of the conference on TRI-Ada '91: today's accomplishments; tomorrow's expectations
Software first: applying Ada megaprogramming technology to target platform selection trades
TRI-Ada '93 Proceedings of the conference on TRI-Ada '93
COCOMO-Based Effort Estimation for Iterative and Incremental Software Development
Software Quality Control
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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. Software rework experience with over 1500 software change orders on the Command Center Processing and Display System - Replacement (CCPDS-R) project was used both to formulate the metrics definitions and to demonstrate their usefulness. These metrics can be applied uniformly from multiple perspectives (project, subsystem, build, CSCI) to achieve objective comparability. They are automated, consistent, and easy to use. Along with subjective interpretation to account for the lifecycle context, objective insight into product quality can be achieved early where correction or improvement can be instigated more efficiently.