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The Use of Original and Hybrid Grey Wolf Optimizer in Estimating the Parameters of Software Reliability Growth Models

by Jamal Salahaldeen Majeed Alneamy, Marwah Marwan Abdulazeez Dabdoob
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 167 - Number 3
Year of Publication: 2017
Authors: Jamal Salahaldeen Majeed Alneamy, Marwah Marwan Abdulazeez Dabdoob
10.5120/ijca2017914201

Jamal Salahaldeen Majeed Alneamy, Marwah Marwan Abdulazeez Dabdoob . The Use of Original and Hybrid Grey Wolf Optimizer in Estimating the Parameters of Software Reliability Growth Models. International Journal of Computer Applications. 167, 3 ( Jun 2017), 12-21. DOI=10.5120/ijca2017914201

@article{ 10.5120/ijca2017914201,
author = { Jamal Salahaldeen Majeed Alneamy, Marwah Marwan Abdulazeez Dabdoob },
title = { The Use of Original and Hybrid Grey Wolf Optimizer in Estimating the Parameters of Software Reliability Growth Models },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 167 },
number = { 3 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 12-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume167/number3/27750-2017914201/ },
doi = { 10.5120/ijca2017914201 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:13:50.008660+05:30
%A Jamal Salahaldeen Majeed Alneamy
%A Marwah Marwan Abdulazeez Dabdoob
%T The Use of Original and Hybrid Grey Wolf Optimizer in Estimating the Parameters of Software Reliability Growth Models
%J International Journal of Computer Applications
%@ 0975-8887
%V 167
%N 3
%P 12-21
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to optimize the use of programs, it has become necessary to focus on issues like software reliability. In this work, the parameters of Software Reliability Growth Models (SRGMs) were estimated in depending on failure data and Swarm Intelligence, namely, Grey Wolf Optimizer (GWO). Then, the (GWO) was hybrid with Real Coded Genetic Algorithm (RGA) to obtain Hybrid GWO (HGWO). The results that obtained from (GWO) are compared to the results of five algorithms: Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), the Dichotomous Artificial Bee Colony (DABC), Classic Genetic Algorithm (CGA) and the Modified Genetic Algorithm (MGA). The results showed that (GWO) outperformed the rest of the algorithms in parameters estimating accuracy and performance using identical datasets. Sometimes, the (DABC) showed better performance than (GWO). Other comparisons were made between (GWO) and (HGWO) and the results show that the hybrid algorithm outperformed the original one.

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Index Terms

Computer Science
Information Sciences

Keywords

Genetic algorithms Grey Wolf optimizer Software Reliability Growth Models .

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