An Evidential Software Risk Evaluation Model

Xingyuan Chen and Yong Deng
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Xingyuan Chen: College of Information and Engineering, Kunming University, Kunming 650214, China
Yong Deng: Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu 610054, China

Mathematics, 2022, vol. 10, issue 13, 1-19

Abstract: Software risk management is an important factor in ensuring software quality. Therefore, software risk assessment has become a significant and challenging research area. The aim of this study is to establish a data-driven software risk assessment model named DDERM. In the proposed model, experts’ risk assessments of probability and severity can be transformed into basic probability assignments (BPAs). Deng entropy was used to measure the uncertainty of the evaluation and to calculate the criteria weights given by experts. In addition, the adjusted BPAs were fused using the rules of Dempster–Shafer evidence theory (DST). Finally, a risk matrix was used to get the risk priority. A case application demonstrates the effectiveness of the proposed method. The proposed risk modeling framework is a novel approach that provides a rational assessment structure for imprecision in software risk and is applicable to solving similar risk management problems in other domains.

Keywords: software risk evaluation; Dempster–Shafer evidence theory; Deng entropy; risk matrix (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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