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Multimedia Tools and Applications

, Volume 74, Issue 20, pp 8745–8759 | Cite as

Towards virtualized and automated software performance test architecture

  • Gwang-Hun Kim
  • Yeon-Gyun Kim
  • Kyung-Yong ChungEmail author
Article

Abstract

In this paper, we propose the towards virtualized and automated software performance test architecture. In general, test engineers use the public performance testwares such as Load Runner, Silk Performer to validate the performance efficiency of their own systems. In case that they do not allowed to use the performance testwares due to the technical limitations in the testwares, most testers should perform the testing in manually. According to the waste of computer and human resources resulted from the situation, we need to propose the test automation scheme by using the virtualization technology to prevent the dissipation in the test environment which has limited resources. The system architecture considered efficient usage of computer resources and test automation to reduce human acts are addressed mainly in this paper. we describe our proposed method which deals with the system architecture and test automation procedures. In our system architecture, we will show how to use the virtual machines and the types of the virtual machines for performance measurement. In addition, the six steps of the test automation are introduced for the automated testing procedures. Finally, a number of experiments show that the proposed schemes allow offering the possibility for automated software performance testing by using the virtualization.

Keywords

Software testing Software performance engineering Performance testing Test automation Virtualization 

Notes

Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (No. 2012-0004478).

References

  1. 1.
    Balsamo S, Di Marco A, Inverardi P, Simeoni M (2004) Model-based performance prediction in software development: a survey. IEEE Trans Softw Eng 30(5):295–310CrossRefGoogle Scholar
  2. 2.
    Banga G, Druschel P (1999) Measuring the capacity of a Web server under realistic loads. World Wide Web 2(1):69–83CrossRefGoogle Scholar
  3. 3.
    Barber S (2004) User community modeling language (UCML 1.1™) for performance test workloads. Rational Developer NetworkGoogle Scholar
  4. 4.
    Barford P, Crovella M (1998, June) Generating representative web workloads for network and server performance evaluation. In: ACM SIGMETRICS performance evaluation review (vol. 26, no. 1, pp. 151–160). ACMGoogle Scholar
  5. 5.
    Chung KY (2013) Effect of facial makeup style recommendation on visual sensibility. Multimed Tools Appl. doi: 10.1007/s11042-013-1355-6 Google Scholar
  6. 6.
    Chung L, do Prado Leite J (2009) On non-functional requirements in software engineering. Concept Model Found Appl 363–379Google Scholar
  7. 7.
    Compuware, “applied performance management survey”, Oct, 2006Google Scholar
  8. 8.
  9. 9.
  10. 10.
  11. 11.
  12. 12.
  13. 13.
  14. 14.
  15. 15.
  16. 16.
  17. 17.
  18. 18.
  19. 19.
    Jung YG, Han MS, Chung KY, Lee SJ (2011) A study of a valid frequency range using correlation analysis of throat signal. Inf Int Interdisc J 14(11):3791–3799Google Scholar
  20. 20.
    Kim SH, Chung KY (2013) 3D simulator for stability analysis of finite slope causing plane activity. Multimed Tools Appl. doi: 10.1007/s11042-013-1356-5 Google Scholar
  21. 21.
    Kim JH, Chung KY (2013) Ontology-based healthcare context information model to implement ubiquitous environment. Multimed Tools Appl. doi: 10.1007/s11042-011-0919-6 Google Scholar
  22. 22.
    Kim GH, Kim YG, Shin SK (2012) Software performance test automation by using the virtualization, Proc. of the 2th International Conference IT Convergence and Security 2012, LNEE 215, pp. 35–42, SpringerGoogle Scholar
  23. 23.
    Kim JH, Lee D, Chung KY (2013) Item recommendation based on context-aware model for personalized u-healthcare service. Multimed Tools Appl. doi: 10.1007/s11042-011-0920-0 Google Scholar
  24. 24.
    Lee H (2008) Server virtualization overview and related solution areas. Commun Korean Inst Inf Sci Eng 26(10):5–13Google Scholar
  25. 25.
    Lee KD, Nam MY, Chung KY, Lee YH, Kang UG (2013) Context and profile based cascade classifier for efficient people detection and safety care system. Multimed Tools Appl 63(1):27–44CrossRefGoogle Scholar
  26. 26.
    Li P (2010) Selecting and using virtualization solutions: our experiences with VMware and VirtualBox. J Comput Sci Coll 25(3):11–17zbMATHGoogle Scholar
  27. 27.
    Mosberger D, Jin T (1998) httperf—a tool for measuring web server performance. ACM SIGMETRICS Perform Eval Rev 26(3):31–37CrossRefGoogle Scholar
  28. 28.
    Song CW, Chung KY, Jung JJ, Rim KW, Lee JH (2011) Localized approximation method using inertial compensation in WSNs. Inf Int Interdisc J 14(11):3591–3600Google Scholar
  29. 29.
    Song CW, Lee D, Chung KY, Rim KW, Lee JH (2013) Interactive middleware architecture for lifelog based context awareness. Multimed Tools Appl. doi: 10.1007/s11042-013-1362-7 Google Scholar
  30. 30.
    Turban E, King D, Lee J, Viehland D (2008) Chapter 19: building E-commerce applications and infrastructure. Electronic Commerce A Managerial Perspective (5th ed.). Prentice-Hall, 27Google Scholar
  31. 31.
    Woodside M, Franks G, Petriu DC (2007, May) The future of software performance engineering. In: Future of software engineering, 2007. FOSE’07 (pp. 171-187). IEEEGoogle Scholar
  32. 32.
    Younge AJ, Henschel R, Brown JT, von Laszewski G, Qiu J, Fox GC (2011, July) Analysis of virtualization technologies for high performance computing environments. In: Cloud computing (CLOUD), 2011 IEEE International Conference on (pp. 9–16). IEEEGoogle Scholar
  33. 33.
    Zheng G, Wilmarth T, Jagadishprasad P, Kalé LV (2005) Simulation-based performance prediction for large parallel machines. Int J Parallel Prog 33(2):183–207CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Gwang-Hun Kim
    • 1
  • Yeon-Gyun Kim
    • 2
  • Kyung-Yong Chung
    • 3
    Email author
  1. 1.Software Testing & Certification Laboratory, Telecommunications Technology Association (TTA)Seongnam-siKorea
  2. 2.Defense Avionics Technology Center, Agency for Defense Development (ADD)Daejeon-siKorea
  3. 3.School of Computer Information EngineeringSangji University, Usan-dongWonju-siKorea

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