Software Quality measurement with Metamorphic Testing

Authors

  • M. SatishKumar  Assoc. Professor Department of computer Applications, SVCET, Chittoor, Andhra Pradesh, India
  • S. Surekha  PG scholar Department of computer Applications, SVCET, Chittoor, Andhra Pradesh, India
  • M. Keerthi  PG scholar Department of computer Applications, SVCET, Chittoor, Andhra Pradesh, India

Keywords:

Metamorphic testing, Google, Bing, Chinese Bing.

Abstract

Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries. Metamorphic testing may be a testing technique which will be used to verify the useful correctness of software system within the absence of an ideal oracle. This paper extends metamorphic testing into a user-oriented approach to software system verification, validation, and quality assessment, and conducts large scale empirical studies with four major net search engines: Google, Bing, Chinese Bing, and Baidu. These search engines are very tough to check and assess using conventional approaches owing to the lack of an objective and generally recognized oracle. The results are useful for each search engine developers and users, and demonstrate that our approach will effectively alleviate the oracle drawback and challenges close a lack of specifications when verifying, validating, and evaluating giant and complex software systems.

References

  1. G. Agha. Actors: a model of concurrent computation in distributed systems. MIT Press, 1986.
  2. J. Aldrich, C. Chambers, and D. Notkin. Archjava: connecting software architecture to implementation. In Proceedings of the 24th international conference on Software engineering, pages 187-197. ACM Press, 2002.
  3. J. Aldrich, V. Sazawal, C. Chambers, and D. Notkin. Language support for connector abstractions. In ECOOP 2003 - Object-Oriented Programming: 17th European Conference, volume 2743 of Lecture Notes in Computer Science, pages 74-102. Springer-Verlag, July 2003.
  4. G. Arango, L. Bruneau, J. F. Cloarec, and A. Feroldi. A tool shell for tracking design decisions. IEEE Software, 8(2):75-83, March 1991.
  5. The Archium website, http://www.archium.net.
  6. M. Babar, I. Gorton, and B. Kitchenham. A framework for supporting architecture knowledge and rationale management. In A. H. Dutoit, R. McCall, I. Mistrik, and B. Paech, editors, Rationale Management in Software Engineering, chapter 11, pages 237-254. Springer-Verlag, March 2006.
  7. M. A. Babar, R. C. de Boer, T. Dingsøyr, and R. Farenhorstir. Architectural knowledge management strategies: approaches in research and industry. In Proceedings of the 2nd Workshop on SHAring and Reusing architectural Knowledge - Architecture, rationale, and Design Intent (SHARK/ADI 2007), May 2007.
  8. M. Bachler, S. Buckingham Shum, D. D. Roure, D. Michaelides, and K. Page. Ontological mediation of meeting structure: Argumentation, annotation, and navigation. In 1st International Workshop on Hypermedia and the Semantic Web, 2003.
  9. E. L. A. Baniassad, G. C. Murphy, and C. Schwanninger. Design pattern rationale graphs: Linking design to source. In Proceedings of the 25th ICSE, pages 352-362, May 2003.
  10. L. Bass, P. Clements, and R. Kazman. Software architecture in practice. Addison Wesley, 1998.
  11. L. Bass, P. Clements, and R. Kazman. Software architecture in practice 2nd ed. Addison Wesley, 2003.
  12. L. Bass, P. Clements, R. L. Nord, and J. Stafford. Capturing and using rationale for software architecture. In A. H. Dutoit, R. McCall, I. Mistrik, and B. Paech, editors, Rationale Management in Software Engineering, chapter 12, pages 255-272. Springer-Verlag, March 2006.
  13. D. Batory, J. Liu, and J. N. Sarvela. Refinements and multi-dimensional separation of concerns. In Proceedings of the 9th European software engineering conference, pages 48-57. ACM Press, 2003.
  14. K. H. Bennett and V. T. Rajlich. Software maintenance and evolution: a roadmap. In Proceedings of the conference on the future of Software engineering, pages 73-87. ACM Press, 2000.
  15. B. W. Boehm, E. Horowitz, R. Madachy, D. Reifer, B. K. Clark, B. Steece, A. W. Brown, S. Chulani, and C. Abts. Software Cost Estimation with Cocomo II. Prentice Hall, January 2000.
  16. C. Boekhoudt. The big bang theory of ides. Queue, 1(7):74-82, 2003.
  17. G. Booch, J. RumBaugh, and I. Jacobson. The unified modeling language user guide. Addison Wesley, 1998.
  18. J. Bosch. Superimposition: A component adaptation technique. Information and Software Technology, 41(5):257-273, 25 March 1999.
  19. J. Bosch. Design & Use of Software Architectures, Adopting and evolving a product line approach. ACM Press/Addison Wesley, 2000.
  20. J. Bosch. Maturity and evolution in software product lines: approaches, artefacts and organization. In Proceedings of the 2nd Software Product Line Conference (SPLC 2002), August 2002.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 4, March-April-2018

Section

Research Articles

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Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. SatishKumar, S. Surekha, M. Keerthi, " Software Quality measurement with Metamorphic Testing, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.511-516, March-April-2018.