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Hybridizing Evolutionary Testing with the Chaining Approach

  • Phil McMinn
  • Mike Holcombe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3103)

Abstract

Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often this is because the search does not take into account data dependencies within the program, and the fact that some special intermediate statement (or statements) needs to have been executed in order for the target structure to be feasible. This paper proposes a solution which combines ET with the Chaining Approach. The Chaining Approach is a simple method which probes the data dependencies inherent to the test goal. By incorporating this facility into ET, the search can be directed into potentially promising, unexplored areas of the test object’s input domain. Encouraging results were obtained with the hybrid approach for seven programs known to originally cause problems for ET.

Keywords

Event Sequence Target Structure Evolutionary Test Approach Level Evolutionary 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 2004

Authors and Affiliations

  • Phil McMinn
    • 1
  • Mike Holcombe
    • 1
  1. 1.Department of Computer ScienceThe University of SheffieldSheffieldUK

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