Abstract (English). Modern business applications are getting increasingly distributed as multi-tenant software as a service (SaaS). This leads to new challenges in terms of quality assurance, because all customers are directly affected by software changes. The resulting problem is to proactively determinate evolutionary effects.
Because SaaS applications are often realized in the sense of a software product line, this thesis examines ways of using feature models to face the mentioned problem. For this purpose, two approaches are analyzed: extended feature models with quality attributes annotated per feature and the analysis of structural aspects of feature models and corresponding concrete configurations.
The presented attributed feature model approach measures the quality of concrete configurations to make configurations comparable according to specific quality goals. Criteria are elicited for when configurations can be compared to draw helpful conclusions. The structural approach focuses economic questions that are quality assurance related, such as identifying features that none of the tenants selected in their application configurations. Furthermore, three algorithms are presented that demonstrate the structural analysis approach to gather information relevant to quality assurance.
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