An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning

Abstract

During a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.