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Aru, O. E.
Department of Computer Engineering, Michael Okpara University of Agriculture Umudike, P.M.B. 7276, Umuahia Nigeria.
Adimora, K. C.
Department of Computer Engineering, Michael Okpara University of Agriculture Umudike, P.M.B. 7276, Umuahia Nigeria.
ABSTRACT
The existing software Risk Assessment Model uses
nine Critical Risk Elements (CRE) in its risk assessment. As the complexity of
the software increases, the existing model becomes obsolete and experiences
some limitations in assessing risk efficiently. In this paper, an optimized
software risk assessment model with twelve critical risk elements was developed
using genetic algorithm to efficiently manage risk elements. All simulations
were performed in Matlab. Quantitative research methodology was deployed for
data collections and results obtained show that the model with twelve critical
risk elements optimally manages and assesses risk than the one with just nine
CRE.
Keywords: Optimized, Genetic Algorithms, Risk Assessment, Critical Risk Elements, Simulation
https://doi.org/10.33922/j.ujet_v5i1_13
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View: 270 | Download: 27
Published
Saturday, September 14, 2019
Issue
Vol. 5 No. 1, JUNE 2019
Article Section
GENERAL
The contents of the articles are the sole opinion of the author(s) and not of UJET.
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