Open AccessOPTIMIZATION OF SOFTWARE RISK ASSESSMENT MODEL USING GENETIC ALGORITHM
Publication year - 2019
Publication title -
umudike journal of engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2545-5257
DOI - 10.33922/j.ujet_v5i1_13
Subject(s) - risk assessment , software , computer science , matlab , genetic algorithm , risk model , reliability engineering , risk analysis (engineering) , data mining , machine learning , engineering , operating system , medicine , computer security
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.