Exploring Genetic Programming and Boosting Techniques to Model Software Reliability

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@Article{Costa:2007:ieeeTR,
  author =       "Eduardo Oliveira Costa and 
                 Gustavo Alexandre {de Souza} and Aurora Trinidad Ramirez Pozo and 
                 Silvia Regina Vergilio",
  title =        "Exploring Genetic Programming and Boosting Techniques
                 to Model Software Reliability",
  journal =      "IEEE Transactions on Reliability",
  year =         "2007",
  volume =       "56",
  number =       "3",
  pages =        "422--434",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, Fault
                 prediction, machine learning techniques, software
                 reliability models",
  DOI =          "doi:10.1109/TR.2007.903269",
  ISSN =         "0018-9529",
  abstract =     "Software reliability models are used to estimate the
                 probability that a software fails at a given time. They
                 are fundamental to plan test activities, and to ensure
                 the quality of the software being developed. Each
                 project has a different reliability growth behaviour,
                 and although several different models have been
                 proposed to estimate the reliability growth, none has
                 proven to perform well considering different project
                 characteristics. Because of this, some authors have
                 introduced the use of Machine Learning techniques, such
                 as neural networks, to obtain software reliability
                 models. Neural network-based models, however, are not
                 easily interpreted, and other techniques could be
                 explored. In this paper, we explore an approach based
                 on Genetic Programming, and also propose the use of
                 Boosting techniques to improve performance. We conduct
                 experiments with reliability models based on time, and
                 on test coverage. The obtained results show some
                 advantages of the introduced approach. The models adapt
                 better to the reliability curve, and can be used in
                 projects with different characteristics.",
}

Genetic Programming entries for Eduardo Oliveira Costa Gustavo Antonio de Souza Goll Aurora Trinidad Ramirez Pozo Silvia Regina Vergilio

Citations