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Test data generation algorithm of combinatorial testing based on differential evolution

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

Abstract

In this paper, we present a test data generation algorithm of combinatorial testing based on Differential Evolution, and introduce a selection and substitution based on the degree of unfinished interaction, in order to optimize the test case selected in further. An IPO-like strategy for generating the test suite is used to reduce the dimension for differential evolutionary computation in the optimization process and improve the efficiency of the algorithm. By preliminary experiments, the main parameters in DE algorithm are chosen. And in further experiments, we implement the algorithm in some typical instances to verify its effectiveness. Compare to other well-known algorithms, the final empirical results show the competitiveness of our algorithm in test suite size and running time.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2013
PublisherIEEE Computer Society
Pages544-548
Number of pages5
ISBN (Print)9780769551227
DOIs
StatePublished - 2013
Event3rd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2013 - Shenyang, Liaoning, China
Duration: 21 Sep 201323 Sep 2013

Publication series

NameProceedings - 3rd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2013

Conference

Conference3rd International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2013
Country/TerritoryChina
CityShenyang, Liaoning
Period21/09/1323/09/13

Keywords

  • Differential Evolution
  • Momentum Term
  • test data generation
  • the degree of unfinished interaction

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