Skip to main content

Feature-Based Adaptation of Database Schemas

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7706))

Abstract

A recognized quality of a modern software system is its ability to adapt to changing user needs, user tasks, user skills and context of operation. While recent research results have been achieved in the domain of architectures, requirements and user interfaces, very little attention has been devoted to the adaptation of the data manipulation aspects of the system. However, mobile and pervasive applications impose constraints over the amount of data that can be supported, thus making necessary to adapt the schema to the current context in order to provide only relevant data to the system user.

This paper presents a feature-based approach to adapt database schemas according to the changing context conditions. The method allows the derivation of a consistent and sufficient sub-schema starting from the current context. We define and formalize a generic framework, considering two levels of abstraction for database schema specification, and we propose two schema derivation algorithms.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bolchini, C., Curino, C., Orsi, G., Quintarelli, E., Rossato, R., Schreiber, F.A., Tanca, L.: And what can context do for data? ACM 52(11), 136–140 (2009)

    Article  Google Scholar 

  2. Bolchini, C., Quintarelli, E., Rossato, R.: Relational data tailoring through view composition. In: Parent, C., Schewe, K.-D., Storey, V.C., Thalheim, B. (eds.) ER 2007. LNCS, vol. 4801, pp. 149–164. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  3. Bolchini, C., Schreiber, F.A., Tanca, L.: A methodology for a very small data base design. Inf. Syst. 32(1), 61–82 (2007)

    Article  Google Scholar 

  4. Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.): Software Engineering for Self-Adaptive Systems. LNCS, vol. 5525. Springer, Heidelberg (2009)

    Google Scholar 

  5. Ciaccia, P., Torlone, R.: Modeling the propagation of user preferences. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 304–317. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  6. Classen, A., Heymans, P., Schobbens, P.-Y.: What’s in a feature: A requirements engineering perspective. In: Fiadeiro, J.L., Inverardi, P. (eds.) FASE 2008. LNCS, vol. 4961, pp. 16–30. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  7. Cleve, A., Brogneaux, A.-F., Hainaut, J.-L.: A conceptual approach to database applications evolution. In: Parsons, J., Saeki, M., Shoval, P., Woo, C., Wand, Y. (eds.) ER 2010. LNCS, vol. 6412, pp. 132–145. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Czarnecki, K., Antkiewicz, M.: Mapping features to models: A template approach based on superimposed variants. In: Glück, R., Lowry, M. (eds.) GPCE 2005. LNCS, vol. 3676, pp. 422–437. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  9. Czarnecki, K., Eisenecker, U.W.: Generative programming: Methods, Tools and Applications. Addison-Wesley (2000)

    Google Scholar 

  10. Glinz, M.: On non-functional requirements. In: RE, pp. 21–26 (2007)

    Google Scholar 

  11. Inverardi, P., Mori, M.: Model checking requirements at run-time in adaptive systems. In: ASAS 2011, pp. 5–9 (2011)

    Google Scholar 

  12. Inverardi, P., Mori, M.: A software lifecycle process to support consistent evolutions. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds.) Self-Adaptive Systems. LNCS, vol. 7475, pp. 239–264. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  13. Keck, D.O., Kühn, P.J.: The feature and service interaction problem in telecommunications systems. a survey. IEEE TSE 24(10), 779–796 (1998)

    Google Scholar 

  14. Marriott, K., Stuckey, P.: Programming with Constraints: An introduction. MIT Press (1998)

    Google Scholar 

  15. Mori, M., Li, F., Dorn, C., Inverardi, P., Dustdar, S.: Leveraging state-based user preferences in context-aware reconfigurations for self-adaptive systems. In: Barthe, G., Pardo, A., Schneider, G. (eds.) SEFM 2011. LNCS, vol. 7041, pp. 286–301. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  16. Parra, C., Cleve, A., Blanc, X., Duchien, L.: Feature-based composition of software architectures. In: Babar, M.A., Gorton, I. (eds.) ECSA 2010. LNCS, vol. 6285, pp. 230–245. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  17. Parra, C., Romero, D., Mosser, S., Rouvoy, R., Duchien, L., Seinturier, L.: Using constraint-based optimization and variability to support continuous self-adaptation. In: SAC, pp. 486–491 (2012)

    Google Scholar 

  18. Quintarelli, E., Rabosio, E., Tanca, L.: Context schema evolution in context-aware data management. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 290–303. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  19. Salehie, M., Tahvildari, L.: Self-adaptive software: Landscape and research challenges. TAAS 4(2) (2009)

    Google Scholar 

  20. Saval, G., Puissant, J.P., Heymans, P., Mens, T.: Some challenges of feature-based merging of class diagrams. In: VaMoS, pp. 127–136 (2009)

    Google Scholar 

  21. Schobbens, P.-Y., Heymans, P., Trigaux, J.-C., Bontemps, Y.: Generic semantics of feature diagrams. Computer Networks 51(2), 456–479 (2007)

    Article  MATH  Google Scholar 

  22. Siegmund, N., Kästner, C., Rosenmüller, M., Heidenreich, F., Apel, S., Saake, G.: Bridging the gap between variability in client application and database schema. In: BTW, pp. 297–306 (2009)

    Google Scholar 

  23. Villegas, A., Olivé, A.: A method for filtering large conceptual schemas. In: Parsons, J., Saeki, M., Shoval, P., Woo, C., Wand, Y. (eds.) ER 2010. LNCS, vol. 6412, pp. 247–260. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mori, M., Cleve, A. (2013). Feature-Based Adaptation of Database Schemas. In: Machado, R.J., Maciel, R.S.P., Rubin, J., Botterweck, G. (eds) Model-Based Methodologies for Pervasive and Embedded Software. MOMPES 2012. Lecture Notes in Computer Science, vol 7706. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38209-3_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38209-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38208-6

  • Online ISBN: 978-3-642-38209-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics