Evolutionary Computing to solve product inconsistencies in Software Product Lines

Abstract

• Inconsistencies prevent and delay the configuration of an SPL product. • Evolutionary computation is proposed to resolve inconsistencies in SPL products. • ga-SPLIS (genetic algorithm-Software Product LIne Solution) is developed. • Results show the applicability of GA to resolve the SPL product inconsistencies. In Software Product Lines (SPLs), multiple design teams work collectively to configure products. Often, having multiple sub-designs leads to inconsistencies which prevent and delay the configuration of the final product at the end. Solutions are available to identify and resolve these inconsistencies for limited scale SPLs. For large scale and industrial SPLs, resolution of inconsistencies is still a potential research topic. In this paper, we propose, implement and validate an application of evolutionary computation, particularly genetic algorithms, to resolve inconsistencies in large scale SPL products. We label our approach ga -SPLIS (genetic algorithm-Software Product LIne Solution). Using a concrete experimental methodology with different feature set sizes and multiple standard performance metrics, we generate results which validate the applicability of ga -SPLIS for the SPL community.