Cost Optimization of SRGM using Genetic Algorithm

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Manish Saraswat
10.5120/ijca2016910266

Manish Saraswat. Cost Optimization of SRGM using Genetic Algorithm. International Journal of Computer Applications 144(5):13-20, June 2016. BibTeX

@article{10.5120/ijca2016910266,
	author = {Manish Saraswat},
	title = {Cost Optimization of SRGM using Genetic Algorithm},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2016},
	volume = {144},
	number = {5},
	month = {Jun},
	year = {2016},
	issn = {0975-8887},
	pages = {13-20},
	numpages = {8},
	url = {http://www.ijcaonline.org/archives/volume144/number5/25174-2016910266},
	doi = {10.5120/ijca2016910266},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The  applications  of computer  systems  have been  increased immensely during  the  last  few  decades and the system reliability is major concern which is depends upon reliability of software and hardware components. Software testing is quality assurance process which confirms that the product is error free and reliable. The reliability of software is major quality attribute which ensure failure free operations and maintainability, therefore reliability assessment is necessary. Software reliability control the optimal release time and cost of software development. In this paper various fault detection and removal strategies are discussed to increase the reliability. A software reliability growth model with imperfect debugging based on Non-homogenous Position Process (NHPP) model is incorporated. The reliability estimation is based on testing and operational reliability of systems. The various numerical parameters are examined and results are presented with the GA tool of MATLAB for optimal release policy based on cost and reliability criterion.

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Keywords

Reliability growth, Non-homogeneous Poisson process Genetic Algorithm, Optimal release policy.