As long as software has been produced, there have been efforts to strive for quality in software products. In order to understand quality in software products, researchers have built models of software quality that rely on metrics in an attempt to provide a quantitative view of software quality. The aim of these models is to provide software producers with the capability to define and evaluate metrics related to quality and use these metrics to improve the quality of the software they produce over time. These models can be quite cumbersome to implement as they require effort and resources to define and evaluate metrics from software projects. This dissertation aims to build an understanding of quality in software engineering by investigating those concepts core to the field. The basic concepts of the field are described, including quality, metrics and software engineering processes. Three software quality models and four approaches to using metrics to gain insight into quality are discussed with an aim to understanding the apparent strengths and weaknesses of each. This dissertation proposes a new approach to using metrics to gain insight into software quality. An equation, called the Product Quality Indicator, is proposed and critically assessed, which uses a combination of metrics based on requirements, tests and defects, to provide some insight into quality. Furthermore, a software product, called Metaversion, which relies on the Subversion Software Configuration Management system is presented. This software, which is a reference implementation of the proposed approach, aims to allow for the automatic collection and evaluation of the Product Quality Indicator. A case study is discussed where the Metaversion system is used and the results of the evaluation of the Product Quality Indicator are compared with the quality of the software as perceived by the testers responsible for testing the software. / Dissertation (MSc)--University of Pretoria, 2013. / gm2014 / Computer Science / unrestricted