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Adaptive Random Testing by Bisection and Localization

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Book cover Formal Approaches to Software Testing (FATES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 3997))

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Abstract

Adaptive Random Testing (ART) denotes a family of test case generation algorithms that are designed to detect common failure patterns better than pure Random Testing. The best known ART algorithms, however, use many distance computations. Therefore, these algorithms are quite inefficient regarding runtime. New algorithms combining Adaptive Random Testing by Bisection and the principle of localization are presented. These algorithms heavily reduce the amount of distance computation while exhibiting very good performance measured in terms of the number of test cases necessary to detect the first failure.

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Author information

Authors and Affiliations

  1. Dept. of Applied Information Processing, University of Ulm, 89069, Ulm, Germany

    Johannes Mayer

Authors
  1. Johannes Mayer
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Editor information

Editors and Affiliations

  1. Microsoft Research, Redmond, WA, USA

    Wolfgang Grieskamp

  2. Ericsson Deutschland GmbH, 52134, Herzogenrath, Germany

    Carsten Weise

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© 2006 Springer-Verlag Berlin Heidelberg

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Mayer, J. (2006). Adaptive Random Testing by Bisection and Localization. In: Grieskamp, W., Weise, C. (eds) Formal Approaches to Software Testing. FATES 2005. Lecture Notes in Computer Science, vol 3997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759744_6

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  • DOI: https://doi.org/10.1007/11759744_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34454-4

  • Online ISBN: 978-3-540-34455-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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