Advertisement

Automatic Testing of Real-Time Graphics Systems

  • Robert Nagy
  • Gerardo Schneider
  • Aram Timofeitchik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7795)

Abstract

In this paper we deal with the general topic of verification of real-time graphics systems. In particular we present the Runtime Graphics Verification Framework (RUGVEF), where we combine techniques from runtime verification and image analysis to automate testing of graphics systems. We provide a proof of concept in the form of a case study, where RUGVEF is evaluated in an industrial setting to verify an on-air graphics playout system used by the Swedish Broadcasting Corporation. We report on experimental results from the evaluation, in particular the discovery of five previously unknown defects.

Keywords

Mean Square Error Automatic Test Image Quality Assessment Graphical Output Reference Implementation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    Colombo, C., Pace, G.J., Schneider, G.: LARVA — safer monitoring of real-time java programs (tool paper). In: SEFM, pp. 33–37. IEEE Comp. Soc. (2009)Google Scholar
  3. 3.
    Cunha, M., Paiva, A.C.R., Ferreira, H.S., Abreu, R.: PETTool: A pattern-based GUI testing tool. In: ICSTE 2010, vol. 1, pp. 202–206 (2010)Google Scholar
  4. 4.
    Distler, T.: Image quality assessment (IQA) library (2011), http://tdistler.com/projects/iqa
  5. 5.
    Farnham, K.: Threading building blocks scheduling and task stealing: Introduction (August 2007), http://software.intel.com/en-us/blogs/2007/08/13/threading-building-blocks-scheduling-and-task-stealing-introduction/
  6. 6.
    Fell, D.: Testing graphical applications. Embedded Sys. Design 14(1), 86 (2001)Google Scholar
  7. 7.
    Li, X., Cui, Y., Xue, Y.: Towards an automatic parameter-tuning framework for cost optimization on video encoding cloud. Int. J. Digit. Multim. Broadc. (2012)Google Scholar
  8. 8.
    Microsoft. Streaming SIMD extensions, SSE (2012), http://msdn.microsoft.com/en-us/library/t467de55.aspx
  9. 9.
    Murching, A.M., Woods, J.W.: Adaptive subsampling of color images. In: ICIP 1994, vol. 3, pp. 963–966 (November 1994)Google Scholar
  10. 10.
    Myers, G.J., Sandler, C.: The Art of Software Testing, 2nd edn. John Wiley & Sons (2004)Google Scholar
  11. 11.
    Sharke, M.: Rage PC launch marred by graphics issues (October 2011), http://pc.gamespy.com/pc/id-tech-5-project/1198334p1.html
  12. 12.
    S.B.C. (SVT). National news: Aktuellt & Rapport, http://www.casparcg.com/case/national-news-aktuellt-rapport
  13. 13.
    S.B.C. (SVT). Swedish election 2006 (2006), http://www.casparcg.com/case/swedish-election-2006
  14. 14.
    Timofeitchik, A., Nagy, R.: Verification of real-time graphics systems. Master’s thesis, Chalmers University of Technology, Gothenburg, Sweden (May 2012)Google Scholar
  15. 15.
    Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Trans. on Image Proc. 13(4), 600–612 (2004)CrossRefGoogle Scholar
  16. 16.
    Yeh, T., Chang, T.-H., Miller, R.C.: Sikuli: using GUI screenshots for search and automation. In: UIST 2009, pp. 183–192. ACM (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robert Nagy
    • 1
  • Gerardo Schneider
    • 2
  • Aram Timofeitchik
    • 3
  1. 1.Dfind RedpatchSweden
  2. 2.Department of Computer Science and EngineeringChalmers | University of GothenburgSweden
  3. 3.DQ Consulting ABSweden

Personalised recommendations