Automated analysis of two-layered feature models with feature attributes

Michael Lettner, Jorge Rodas, José A. Galindo, David Benavides

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


The proliferation of features and platforms in variability intensive systems, coupled with substantial technological progress, imposes several challenges for software developers and equipment manufacturers—in some cases referred as technical sustainability. For instance, in the mobile application domain, developers often need to know the requirements and limitations of their applications to be supported on a specific platform. Conversely, an equipment manufacturer is interested in knowing what additional features become accessible on the application layer when the or platform is being upgraded. To date, analyzing such interdependencies between specific feature and platform combinations is a tough problem, but important to solve. There are well-established approaches in the literature to analyze variability–intensive systems using feature models. However, there is a lack of approaches to analyze application and platform features in multiple layers. In this paper we present a framework towards the analysis of multi-layered feature models. First, modeling the two layers including their respective interdependencies. Second, a definition of operations that can be imposed on such models. We also provide a reference implementation for analysis of multiple layers. Finally, we present two empirical evaluations demonstrating the feasibility of the approach in practice.

Original languageEnglish
Pages (from-to)154-172
Number of pages19
JournalJournal of Computer Languages
Publication statusPublished - Apr 2019


  • Android
  • Feature models
  • Variability intensive systems


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