Capturing variability in space and time with hyper feature models

  • Authors:
  • Christoph Seidl;Ina Schaefer;Uwe Aßmann

  • Affiliations:
  • Technische Universität Dresden, Dresden, Germany;Technische Universität Braunschweig, Braunschweig, Germany;Technische Universität Dresden, Dresden, Germany

  • Venue:
  • Proceedings of the Eighth International Workshop on Variability Modelling of Software-Intensive Systems
  • Year:
  • 2014

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Abstract

Software product lines (SPLs) and software ecosystems (SECOs) are approaches to capturing families of closely related software systems in terms of common and variable functionality. SPLs and especially SECOs are subject to evolution to adapt to new or changed requirements resulting in different versions of the software family and its variable assets. These versions may have to be maintained and used for products even after they were superseded by newer versions. Variability models describing valid combinations of variable assets, such as feature models, capture variability in space (configuration), but not variability in time (evolution) making it impossible to respect versions of variable assets in product definitions on a conceptual level. In this paper, we propose Hyper Feature Models (HFMs) explicitly providing feature versions as configurable units for product definition. Furthermore, we provide a version-aware constraint language to specify dependencies between features and ranges of feature versions as well as a procedure to automatically select valid combinations of versions for a pre-configuration of features. We demonstrate our approach in a case study.