Applying Search in an Automatic Contract-Based Testing Tool

  • Alexey Kolesnichenko
  • Christopher M. Poskitt
  • Bertrand Meyer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8084)


Automated random testing has been shown to be effective at finding faults in a variety of contexts and is deployed in several testing frameworks. AutoTest is one such framework, targeting programs written in Eiffel, an object-oriented language natively supporting executable pre- and postconditions; these respectively serving as test filters and test oracles. In this paper, we propose the integration of search-based techniques—along the lines of Tracey—to try and guide the tool towards input data that leads to violations of the postconditions present in the code; input data that random testing alone might miss, or take longer to find. Furthermore, we propose to minimise the performance impact of this extension by applying GPU programming to amenable parts of the computation.


Random Testing Software Test Test Oracle Boolean Query Metaheuristic Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alexey Kolesnichenko
    • 1
  • Christopher M. Poskitt
    • 1
  • Bertrand Meyer
    • 1
  1. 1.ETH ZürichSwitzerland

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