Abstract

We introduce a variability-intensive approach to goal decomposition, which enables the identification of more complete requirements for customizable software. The approach is based on the semantic characterization of ORdecompositions of goals. We first show that each high-level goal can be associated with a set of concerns in response to which alternative refinements of the goal can be introduced. A text corpus relevant to the domain of discourse can be used to derive such variability concerns that are specific to the problem. In parallel, non-intentional background facts that can vary while a goal is being fulfilled are modeled. Then, a high-variability goal model is constructed aiming at responding to the predefined variability concerns completely, while non-intentional factors are used to test whether the result addresses all realistic background circumstances. We apply our approach in a study from the geriatric health care domain.

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