Advertisement

Vision Paper: Towards Model-Based Energy Testing

  • Claas Wilke
  • Sebastian Götz
  • Jan Reimann
  • Uwe Aßmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6981)

Abstract

Today, energy consumption is one of the major challenges for optimisation of future software applications and ICT infrastructures. To develop software w.r.t. its energy consumption, testing is an essential activity, since testing allows quality assurance and thus, energy consumption reduction during the software’s development. Although first approaches measuring and predicting software’s energy consumption for its execution on a specific hardware platform exist, no model-based testing approach has been developed, yet. In this paper we present our vision of a model-based energy testing approach that uses a combination of abstract interpretation and run-time profiling to predict the energy consumption of software applications and to derive energy consumption test cases.

Keywords

Energy consumption testing abstract interpretation profiling unit testing model-based testing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Gartner, Inc.: Gartner Estimates ICT Industry Accounts for 2 Percent of Global CO2 Emissions. Gartner Press Release (April 2007)Google Scholar
  2. 2.
    The Climate Group: SMART 2020: Enabling the low carbon economy in the information age. Report on behalf of the Global eSustainability Initiative (GeSI) (2008)Google Scholar
  3. 3.
    Intel Corporation, Microsoft Corporation: Advanced Power Management (APM) BIOS Interface Specification. Revision 1.2 (February 1996)Google Scholar
  4. 4.
    Hewlett-Packard, Intel, Microsoft, Phoenix Technologies, Toshiba: Advanced Configuration and Power Interface Specification, Revision 4.0a (2010)Google Scholar
  5. 5.
    Lachenmann, A., Marrón, P., Minder, D., Rothermel, K.: Meeting lifetime goals with energy levels. In: Proceedings of the 5th International Conference on Embedded Networked Sensor Systems, pp. 131–144. ACM, New York (2007)CrossRefGoogle Scholar
  6. 6.
    Chan, W.K., Chen, T.Y., Cheung, S.C., Tse, T.H., Zhang, Z.: Towards the Testing of Power-Aware Software Applications for Wireless Sensor Networks. In: Abdennahder, N., Kordon, F. (eds.) Ada-Europe 2007. LNCS, vol. 4498, pp. 84–99. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
    Woehrle, M., Beutel, J., Lim, R., Yuecel, M., Thiele, L.: Power monitoring and testing in wireless sensor network development. In: Workshop on Energy in Wireless Sensor Networks (WEWSN), Citeseer (2008)Google Scholar
  8. 8.
    Lafond, S., Lilius, J.: An Energy Consumption Model for an Embedded Java Virtual Machine. In: Grass, W., Sick, B., Waldschmidt, K. (eds.) ARCS 2006. LNCS, vol. 3894, pp. 311–325. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Seo, C., Malek, S., Medvidovic, N.: An Energy Consumption Framework for Distributed Java-Based Systems. In: Proceedings of the 22nd IEEE/ACM Intl. Conference on Automated Software Engineering, Atlanta, Georgia, USA. ACM, New York (2007)Google Scholar
  10. 10.
    Seo, C., Edwards, G., Malek, S., Medvidovic, N.: A Framework for Estimating the Impact of a Distributed Software System’s Architectural Style on its Energy Consumption. In: WICSA 2008: Proceedings of the Seventh Working IEEE/IFIP Conference on Software Architecture, pp. 277–280. IEEE Computer Society, Los Alamitos (2008)Google Scholar
  11. 11.
    Navas, J., Méndez-Lojo, M., Hermenegildo, M.: Safe Upper-bounds Inference of Energy Consumption for Java Bytecode Applications. In: Proceedings of The Sixth NASA Langley Formal Methods Workshop, pp. 29–32 (2008)Google Scholar
  12. 12.
    Utting, M., Pretschner, A., Legeard, B.: A Taxonomy of Model-Based Testing. Technical Report 04/2006, University of Waikato, Department of Computer Science, Hamilton, NZ (April 2006)Google Scholar
  13. 13.
    Roßner, T., Brandes, C., Götz, H., Winter, M.: Basiswissen Modellbasierter Test. dpunkt Verlag, Heidelberg (2010)Google Scholar
  14. 14.
    Süttner, P.: Abstract Behavior Description of CCM Software Components (Abstrakte Verhaltensbeschreibung von CCM Softwarekomponenten). Diploma Thesis, Technische Universität Dresden (March 2011)Google Scholar
  15. 15.
    Cousot, P., Cousot, R.: Abstract interpretation: a unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages, pp. 238–252. ACM, New York (1977)Google Scholar
  16. 16.
    Martin, F.: Generating Program Analyzers. PhD thesis, Universität des Saarlandes (1999)Google Scholar
  17. 17.
    Götz, S., Wilke, C., Schmidt, M., Cech, S., Aßmann, U.: Towards Energy Auto Tuning. In: Proceedings of First Annual International Conference on Green Information Technology, GREEN IT (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Claas Wilke
    • 1
  • Sebastian Götz
    • 1
  • Jan Reimann
    • 1
  • Uwe Aßmann
    • 1
  1. 1.Institut für Software- und MultimediatechnikTechnische Universität DresdenDresdenGermany

Personalised recommendations