期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：12
页码：48-54
出版社：Science and Information Society (SAI)
摘要：The paper presents a software design methodology
based on computational experiments for effective selection of
software component set. The selection of components is
performed with respect to the numerical quality criteria
evaluated in the reproducible experiments with various sets of
components in the virtual infrastructure simulating the operating
conditions of a software system being developed. To reduce the
number of experiments with unpromising sets of components the
genetic algorithm is applied. For representing the sets of
components in the form of natural genotypes, the encoding
mapping is introduced, reverse mapping is used to decipher the
genotype. In the first step of the technique, the genetic algorithm
creates an initial population of random genotypes that are
converted into the assessed sets of software components. The
paper shows the application of the proposed methodology to find
the effective choice of Node.js components. For this purpose, a
MATLAB program of genetic search and experimental scenario
for a virtual machine running Ubuntu 16.04 LTS operating
system were developed. To guarantee the proper reproduction of
the experimental conditions, the Vagrant and Ansible
configuration tools were used to create the virtual environment
of the experiment.
