A comparative evaluation of using genetic programming for predicting fault count data

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Afzal08d,
  author =       "Wasif Afzal and Richard Torkar",
  title =        "A comparative evaluation of using genetic programming
                 for predicting fault count data",
  booktitle =    "Proceedings of the Third International Conference on
                 Software Engineering Advances (ICSEA'08)",
  year =         "2008",
  pages =        "407--414",
  address =      "Sliema, Malta",
  month =        "26-31",
  keywords =     "genetic algorithms, genetic programming, prediction,
                 software reliability growth modeling, SBSE",
  isbn13 =       "978-1-4244-3218-9",
  DOI =          "doi:10.1109/ICSEA.2008.9",
  abstract =     "There have been a number of software reliability
                 growth models (SRGMs) proposed in literature. Due to
                 several reasons, such as violation of models'
                 assumptions and complexity of models, the practitioners
                 face difficulties in knowing which models to apply in
                 practice. This paper presents a comparative evaluation
                 of traditional models and use of genetic programming
                 (GP) for modeling software reliability growth based on
                 weekly fault count data of three different industrial
                 projects. The motivation of using a GP approach is its
                 ability to evolve a model based entirely on prior data
                 without the need of making underlying assumptions. The
                 results show the strengths of using GP for predicting
                 fault count data.",
  notes =        "Also known as \cite{4668139}

                 ",
}

Genetic Programming entries for Wasif Afzal Richard Torkar

Citations