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Performance evaluation of test process based on stochastic models

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Published:11 April 2010Publication History

ABSTRACT

The demand for high quality software has motivated a definition of methods and techniques. As a result, the interest in software testing activities has been growing over the last few years. Software companies currently seek low cost testing procedures and at the same, with great capacity to handle mistakes. In this article, concepts related to testing processes are mapped in Stochastic Petri Nets(SPN) which provides a formal representation for measures used in performance analysis.

References

  1. OMG UML. 2.0 Superstructure Specification. http://www.uml.org/, 2005.Google ScholarGoogle Scholar
  2. A. Davison and D. Hinkley. Bootstrap methods and their application. Cambridge Univ Pr, 1997.Google ScholarGoogle ScholarCross RefCross Ref
  3. A. Desrochers and R. Al-Jaar. Applications of Petri Nets in Manufacturing Systems: Modeling, Control, and Performance Analysis. IEEE Press, 1995.Google ScholarGoogle Scholar
  4. R. German. Performance Analysis of Communication Systems with Non-Markovian Stochastic Petri Nets. John Wiley & Sons, Inc. New York, NY, USA, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. P. King and R. Pooley. Using UML to derive stochastic Petri net models. In Proceedings of the 15th UK Performance Engineering Workshop, pages 45--56. Citeseer.Google ScholarGoogle Scholar
  6. J. Merseguer and J. Campos. Software performance modeling using uml and petri nets. Lecture Notes in Computer Science, 2965:265--289, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  7. G. Myers. The art of software testing. Wiley, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. T. Pender. UML Bible. John Wiley & Sons, Inc. New York, NY, USA, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. R. Pressman and D. Ince. Software engineering: a practitioner's approach. McGraw-Hill New York, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. I. Sommerville. Software Engineering. Addison Wesley, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. J. Tian. Software Quality Engineering: Testing, Quality Assurance and Quantifiable Improvement. Wiley, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

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              SpringSim '10: Proceedings of the 2010 Spring Simulation Multiconference
              April 2010
              1726 pages
              ISBN:9781450300698

              Publisher

              Society for Computer Simulation International

              San Diego, CA, United States

              Publication History

              • Published: 11 April 2010

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