Ecology

Biology

Identification (biology)

Set (abstract data type)

Data mining

Computer science

Botany

Decomposition

Software

Mathematics

Domain (mathematical analysis)

Mathematical analysis

Data science

Artificial intelligence

Goal modeling

Programming language

Requirements engineering

Human–computer interaction

Machine learning

We introduce a variability-intensive approach to goal decomposition that is tailored to support requirements identification for highly customizable software. The approach is based on the semantic characterization of OR-decompositions 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, contextual 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 contextual factors are used to test whether it addresses all realistic background circumstances. We apply our approach in a study from the geriatric health care domain

On Goal-based Variability Acquisition and Analysis