An extensible, hierarchical architecture for analysis of software quality assurance

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Montana State University - Bozeman, College of Engineering


As software becomes integrated into most aspects of life, a need to assess and guarantee the quality of a software product is paramount. Poor software quality can lead to traffic accidents, failure of life-saving devices, government destabilization, and economic ruin. To assess software quality, quality researchers design quality models. A common quality model will decompose quality concepts such as 'total quality', 'maintainability', and 'confidentiality' into a hierarchy that can eventually be linked to specific lines of code in a software system. However, a problem persists in the domain of quality modeling: quality assessment through use of quality models is not finding acceptance by industry practitioners. This thesis reviews the weaknesses of modern modeling attempts and aims to improve the processes surrounding quality assessment from the perspective of both researchers and academic practitioners. The analysis uses the Goal/Question/Metric paradigm. Two closely related goals are presented that aim to analyze a process of generating, validating, and operationalizing quality models for the purpose of improvement with respect to cost, experimentative capability, collaborative opportunity, and acceptability. A system is designed, PIQUE, that provides functionality to generate experimental quality models. Test cases and exercises are run on the models generated by PIQUE to supply metric data used to answer the questions and goals. The results show that-in the context of a PIQUE-generated quality model compared to a similar non-PIQUE quality model-improvement can be achieved with respect to development cost and experimentative capability. Clear improvement was not found in the context of model operationalization difficulty and output acceptability. Ultimately, partial achievement of both goals is realized. The work concludes that the current problems in the domain of quality modeling can be improved upon, and systems like PIQUE are a valuable approach toward that goal.




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