Software reliability model by AGP

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Zhang:2008:ieeeICIT,

• 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

Citations