International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume4,November 2017,

Topic : An Efficient Method for Software Reliability Using Modified Genetic Algorithm: Inflection S-Shaped Model

Authors:Dr. R.Satyaprasad || G. Bharathi

Abstract:In order to assess software reliability, many software reliability growth models (SRGMs) have been proposed in the past four decades. In principle, two widely used methods for the parameter estimation of SRGMs are the maximum likelihood estimation (MLE) and the least squares estimation (LSE). However, the approach of these two estimations may impose some restrictions on SRGMs, such as the existence of derivatives from formulated models or the needs for complex calculation. In this paper, we propose a modified genetic algorithm (MGA) to assess the reliability of software considering the Time domain software failure data using Inflection S-shaped model which is NonHomogenous Poisson Process (NHPP) based. Experiments based on real software failure data are performed, and the results show that the proposed genetic algorithm is more effective and faster than traditional algorithms.

Keywords: Software reliability, Inflection S-shaped model, Time domain data, Mean Value Function, Modified Genetic Algorithm, NHPP

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DOI: 01.1617/vol4/iss11/pid81360


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
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