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A cloud-based dynamic random software testing strategy

  • Beihang University
  • City University of Hong Kong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cloud testing has emerged as a new technology in corporate world and organization, which generates virtual machines for application demands, and employs resource allocation strategies to dispatch the test tasks. Traditional resource allocation strategies usually concern on static assignment, which lacks dynamic adjustment functions. Dynamic Random Testing (DRT) strategy employs feedback mechanism to guide the selection of test cases, which is shown to be effective and has great potential in theoretical as well as practical terms. Therefore, planting the idea of DRT into cloud testing can allocate the test tasks in a dynamic way. In this paper, a cloud-based dynamic random testing strategy is proposed to enhance the testing process and promote the testing efficiency, in which the virtual resource allocation is in accordance with the testing results. A framework of cloud-based DRT strategy is constructed and contrast experiments are conducted on the Cloudsim platform. The experimental results show that the proposed cloud-based DRT strategy has better performance than the traditional testing strategies.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
PublisherIEEE Computer Society
Pages509-513
Number of pages5
ISBN (Electronic)9781538609484
DOIs
StatePublished - 2 Jul 2017
Event2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 - Singapore, Singapore
Duration: 10 Dec 201713 Dec 2017

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2017-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
Country/TerritorySingapore
CitySingapore
Period10/12/1713/12/17

Keywords

  • Cloud testing
  • Dynamic Random Testing
  • cloud computing
  • resource allocation

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