White-Box Test Case Generation Based on Improved Genetic Algorithm

  • Peng Wang
  • Xiao-juan Hu
  • Ning-jia Qiu
  • Hua-min Yang
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 125)


Some intermittent or transient failures are particularly difficult to diagnose in highly complex and interconnected systems. This paper focuses on the use of genetic algorithms for automatically generating software test cases. In particular, this research extends a newly improved genetic algorithm, which adopts back propagation algorithm for local fine-tuning in the final link, and speeds up access to the best population. The various approaches offer opportunities for performance improvements that make these techniques more scalable for realistic applications.


Genetic Algorithm Fitness Function Test Case Generation Improve Genetic Algorithm Group Optimization 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 GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Peng Wang
    • 1
  • Xiao-juan Hu
    • 1
  • Ning-jia Qiu
    • 1
  • Hua-min Yang
    • 1
  1. 1.Department of Computer ScienceChangchun University of Science and TechnologyChangchunChina

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