Automatic Test Cases Optimization Using a Bacteriological Adaptation Model: Application to .NET Component

@inproceedings{Baudry2002AutomaticTC,
  title={Automatic Test Cases Optimization Using a Bacteriological Adaptation Model: Application to .NET Component},
  author={Benoit Baudry and Franck Fleurey and Jean-Marc J{\'e}z{\'e}quel and Yves Le Traon},
  booktitle={ASE},
  year={2002}
}
In this paper, we present several complementary computational intelligence techniques that we explored in the field of .Net component testing. Mutation testing serves as the common backbone for applying classical and new artificial intelligence (AI) algorithms. With mutation tools, we know how to estimate the revealing power of test cases. With AI, we aim at improving automatically test cases efficiency. So, we looked first at genetic algorithms (GA) to solve the problem of test. The aim of the… CONTINUE READING
Highly Cited
This paper has 48 citations. REVIEW CITATIONS