Tailor-made data management for embedded systems: A case study on Berkeley DB

  • Authors:
  • Marko Rosenmüller;Sven Apel;Thomas Leich;Gunter Saake

  • Affiliations:
  • School of Computer Science, University of Magdeburg, Germany;Department of Informatics and Mathematics, University of Passau, Germany;Metop Research Institute, Magdeburg, Germany;School of Computer Science, University of Magdeburg, Germany

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2009

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Abstract

Applications in the domain of embedded systems are diverse and store an increasing amount of data. In order to satisfy the varying requirements of these applications, data management functionality is needed that can be tailored to the applications' needs. Furthermore, the resource restrictions of embedded systems imply a need for data management that is customized to the hardware platform. In this paper, we present an approach for decomposing data management software for embedded systems using feature-oriented programming. The result of such a decomposition is a software product line that allows us to generate tailor-made data management systems. While existing approaches for tailoring software have significant drawbacks regarding customizability and performance, a feature-oriented approach overcomes these limitations, as we will demonstrate. In a non-trivial case study on Berkeley DB, we evaluate our approach and compare it to other approaches for tailoring DBMS.