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X-Machine Based Testing for Cloud Services

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Advances in Service-Oriented and Cloud Computing (ESOCC 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 508))

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Abstract

In this article we present a tool designed for cloud service testing, able to generate test cases from a formal specification of the service, in form of a deterministic stream X-machine (DSXM) model. The paper summarizes the theoretical foundations of X-machine based testing and illustrates the usage of the developed tool on some examples. It shows in detail how the specification should be written, which are the design for test conditions it should satisfy, in order to assure the generation of high quality test suites for the cloud service.

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Notes

  1. 1.

    http://staffwww.dcs.shef.ac.uk/people/A.Simons/broker/.

  2. 2.

    http://staffwww.dcs.shef.ac.uk/people/A.Simons/broker/specify.html.

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Acknowledgements

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 328392, the Broker@Cloud project (www.broker-cloud.eu).

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Authors and Affiliations

  1. Department of Computer Science, The University of Sheffield, Regent Court, Portobello Street, Sheffield, S1 4DP, UK

    Raluca Lefticaru & Anthony J. H. Simons

  2. Department of Computer Science, University of Bucharest, Str. Academiei Nr. 14, 010014, Bucharest, Romania

    Raluca Lefticaru

Authors
  1. Raluca Lefticaru
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  2. Anthony J. H. Simons
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Corresponding author

Correspondence to Raluca Lefticaru .

Editor information

Editors and Affiliations

  1. University of Cádiz, Puerto Real, Spain

    Guadalupe Ortiz

  2. The University of Manchester, Manchester, United Kingdom

    Cuong Tran

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Lefticaru, R., Simons, A.J.H. (2015). X-Machine Based Testing for Cloud Services. In: Ortiz, G., Tran, C. (eds) Advances in Service-Oriented and Cloud Computing. ESOCC 2014. Communications in Computer and Information Science, vol 508. Springer, Cham. https://doi.org/10.1007/978-3-319-14886-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-14886-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14885-4

  • Online ISBN: 978-3-319-14886-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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