Predicting Defects in Software Using Grammar-Guided Genetic Programming

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@InProceedings{conf/setn/TsakonasD08,
  author =       "Athanasios Tsakonas and Georgios Dounias",
  title =        "Predicting Defects in Software Using Grammar-Guided
                 Genetic Programming",
  booktitle =    "Proceedings 5th Hellenic Conference on AI, SETN 2008",
  year =         "2008",
  editor =       "John Darzentas and George A. Vouros and 
                 Spyros Vosinakis and Argyris Arnellos",
  series =       "Lecture Notes in Computer Science",
  volume =       "5138",
  pages =        "413--418",
  address =      "Syros, Greece",
  month =        oct # " 2-4",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 Software engineering, defect prediction",
  isbn13 =       "978-3-540-87880-3",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.3005",
  DOI =          "doi:10.1007/978-3-540-87881-0_42",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  contributor =  "CiteSeerX",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  language =     "en",
  oai =          "oai:CiteSeerXPSU:10.1.1.149.3005",
  abstract =     "The knowledge of the software quality can allow an
                 organization to allocate the needed resources for the
                 code maintenance. Maintaining the software is
                 considered as a high cost factor for most
                 organizations. Consequently, there is need to assess
                 software modules in respect of defects that will arise.
                 Addressing the prediction of software defects by means
                 of computational intelligence has only recently become
                 evident. In this paper, we investigate the capability
                 of the genetic programming approach for producing
                 solution composed of decision rules. We applied the
                 model into four software engineering databases of NASA.
                 The overall performance of this system denotes its
                 competitiveness as compared with past methodologies,
                 and is shown capable of producing simple, highly
                 accurate, tangible rules.",
}

Genetic Programming entries for Athanasios D Tsakonas Georgios Dounias

Citations