Defining categorical reasoning of numerical feature models with feature-wise and variant-wise quality attributes

Abstract

Automatic analysis of variability is an important stage of Software Product Line (SPL) engineering. Incorporating quality information into this stage poses a significant challenge. However, quality-aware automated analysis tools are rare, mainly because in existing solutions variability and quality information are not unified under the same model. In this paper, we make use of the Quality Variability Model (QVM), based on Category Theory (CT), to redefine reasoning operations. We start defining and composing the six most common operations in SPL, but now as quality-based queries, which tend to be unavailable in other approaches. Consequently, QVM supports interactions between variant-wise and feature-wise quality attributes. As a proof of concept, we present, implement and execute the operations as lambda reasoning for CQL IDE - the state-of-the-art CT tool.