Software reliability model by AGP

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Yongqiang Zhang and Jingjie Yin",
  title =        "Software reliability model by AGP",
  booktitle =    "IEEE International Conference on Industrial
                 Technology, ICIT 2008",
  year =         "2008",
  month =        apr,
  pages =        "1--5",
  keywords =     "genetic algorithms, genetic programming, SBSE, AGP
                 algorithm, Armored Force Engineering Institute,
                 adaptive genetic operators, genetic programming
                 evolution algorithm, sigmoid curve, software failure
                 time series, software reliability model, software
                 testing, program testing, software reliability",
  DOI =          "doi:10.1109/ICIT.2008.4608638",
  abstract =     "To solve the problems of the incongruence of software
                 reliability models and cast off the traditional models'
                 multi-subjective assumptions, this paper adopts genetic
                 programming evolution algorithm which has adaptive
                 genetic operators (for short AGP) to establish software
                 reliability model based on software failure time
                 series. The individual of the population is according
                 to the case of the fitness of the generation to adjust
                 the probability of crossover and mutation by the
                 sigmoid curve. By evaluating the data series of the
                 software testing case in Armored Force Engineering
                 Institute, the results sufficiently testify that the
                 new AGP algorithm has better applicability and the
                 validity of fitness and forecasting. Moreover, compared
                 with standard genetic programming evolution algorithm,
                 the new AGP algorithm has the better rapidity of
                 convergence. Therefore, we can say that, this algorithm
                 can be more effectively applied to software testing and
                 ensured the validity of data.",
  notes =        "Also known as \cite{4608638}",

Genetic Programming entries for Yongqiang Zhang Jingjie Yin