Test data regeneration: generating new test data from existing test data

  • Authors:

  • S. Yoo;M. Harman

  • Affiliations:

  • King's College London, Centre for Research on Evolution, Search & Testing, Strand, London WC2R 2LS, U.K.;King's College London, Centre for Research on Evolution, Search & Testing, Strand, London WC2R 2LS, U.K.

  • Venue:
  • Software Testing, Verification & Reliability
  • Year:
  • 2012

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Abstract

Existing automated test data generation techniques tend to start from scratch, implicitly assuming that no pre-existing test data are available. However, this assumption may not always hold, and where it does not, there may be a missed opportunity; perhaps the pre-existing test cases could be used to assist the automated generation of additional test cases. This paper introduces search-based test data regeneration, a technique that can generate additional test data from existing test data using a meta-heuristic search algorithm. The proposed technique is compared to a widely studied test data generation approach in terms of both efficiency and effectiveness. The empirical evaluation shows that test data regeneration can be up to 2 orders of magnitude more efficient than existing test data generation techniques, while achieving comparable effectiveness in terms of structural coverage and mutation score. Copyright © 2010 John Wiley & Sons, Ltd.