Analysis of variability models: a systematic literature review

Abstract

Dealing with variability, during Software Product Line Engineering (SPLE), means trying to allow software engineers to develop a set of similar applications based on a manageable range of variable functionalities according to expert users’ needs. Particularly, variability management (VM) is an activity that allows flexibility and a high level of reuse during software development. In the last years, we have witnessed a proliferation of methods, techniques and supporting tools for VM in general, and for its analysis in particular. More precisely, a specific field has emerged, named (automated) variability analysis, focusing on verifying variability models across the SPLE’s phases. In this paper, we introduce a systematic literature review of existing proposals (as primary studies) focused on analyzing variability models. We define a classification framework, which is composed of 20 sub-characteristics addressing general aspects, such as scope and validation, as well as model-specific aspects, such as variability primitives, reasoner type. The framework allows to look at the analysis of variability models during its whole life cycle—from design to derivation—according to the activities involved during an SPL development. Also, the framework helps us answer three research questions defined for showing the state of the art and drawing challenges for the near future. Among the more interesting challenges, we can highlight the needs of more applications in industry, the existence of more mature tools, and the needs of providing more semantics in the way of variability primitives for identifying inconsistencies in the models.