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The Quamoco product quality modelling and assessment approach

: Wagner, Stefan; Lochmann, Klaus; Heinemann, Lars; Kläs, Michael; Trendowicz, Adam; Plösch, Reinhold; Seidl, Andreas; Goeb, Andreas; Streit, Jonathan


Glinz, Martin (Ed.) ; IEEE Computer Society:
34th International Conference on Software Engineering, ICSE 2012. Proceedings : 2-9 June 2012, Zurich
New York, NY: IEEE, 2012
ISBN: 978-1-4673-1067-3
ISBN: 978-1-4673-1066-6 (Print)
ISBN: 978-1-4673-1065-9 (Online)
International Conference on Software Engineering (ICSE) <34, 2012, Zurich>
Conference Paper
Fraunhofer IESE ()
quality model; quality assessment; meta model; empirical validation

Published software quality models either provide abstract quality attributes or concrete quality assessments. There are no models that seamlessly integrate both aspects. In the project Quamoco, we built a comprehensive approach with the aim to close this gap. For this, we developed in several iterations a meta quality model specifying general concepts, a quality base model covering the most important quality factors and a quality assessment approach. The meta model introduces the new concept of a product factor, which bridges the gap between concrete measurements and abstract quality aspects. Product factors have measures and instruments to operationalise quality by measurements from manual inspection and tool analysis. The base model uses the ISO 25010 quality attributes, which we refine by 200 factors and 600 measures for Java and C#systems. We found in several empirical validations that the assessment results fit to the expectations of experts for the corresponding systems. The empirical analyses also showed that several of the correlations are statistically significant and that the maintainability part of the base model has the highest correlation, which fits to the fact that this part is the most comprehensive. Although we still see room for extending and improving the base model, it shows a high correspondence with expert opinions and hence is able to form the basis for repeatable and understandable quality assessments in practice.