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An Evidential Software Risk Evaluation Model

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  • Xingyuan Chen

    (College of Information and Engineering, Kunming University, Kunming 650214, China
    Key Laboratory of Data Governance and Intelligent Decision, Universities of Yunnan, Kunming 650214, China)

  • Yong Deng

    (Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu 610054, China)

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.

Suggested Citation

  • Xingyuan Chen & Yong Deng, 2022. "An Evidential Software Risk Evaluation Model," Mathematics, MDPI, vol. 10(13), pages 1-19, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2325-:d:854705
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    References listed on IDEAS

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    1. Cui, Huizi & Zhou, Lingge & Li, Yan & Kang, Bingyi, 2022. "Belief entropy-of-entropy and its application in the cardiac interbeat interval time series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Wang, Hongping & Fang, Yi-Ping & Zio, Enrico, 2022. "Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Seyed Morteza Hatefi & Mohammad Ehsan Basiri & Jolanta Tamošaitienė, 2019. "An Evidential Model for Environmental Risk Assessment in Projects Using Dempster–Shafer Theory of Evidence," Sustainability, MDPI, vol. 11(22), pages 1-16, November.
    4. Xin Ruan & Zhiyi Yin & Dan M. Frangopol, 2015. "Risk Matrix Integrating Risk Attitudes Based on Utility Theory," Risk Analysis, John Wiley & Sons, vol. 35(8), pages 1437-1447, August.
    5. Fergus Bolger, 2018. "The Selection of Experts for (Probabilistic) Expert Knowledge Elicitation," International Series in Operations Research & Management Science, in: Luis C. Dias & Alec Morton & John Quigley (ed.), Elicitation, chapter 0, pages 393-443, Springer.
    6. Mehran Khalaj & Reza Tavakkoli-Moghaddam & Fereshteh Khalaj & Ali Siadat, 2020. "New definition of the cross entropy based on the Dempster-Shafer theory and its application in a decision-making process," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(4), pages 909-923, February.
    7. Xiaoqing Li & Qingquan Jiang & Maxwell K. Hsu & Qinglan Chen, 2019. "Support or Risk? Software Project Risk Assessment Model Based on Rough Set Theory and Backpropagation Neural Network," Sustainability, MDPI, vol. 11(17), pages 1-12, August.
    8. Luyuan Chen & Zhen Li & Xinyang Deng, 2020. "Emergency alternative evaluation under group decision makers: a new method based on entropy weight and DEMATEL," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(3), pages 570-583, February.
    9. Markos V. Koutras & Ioannis S. Triantafyllou & Serkan Eryilmaz, 2016. "Stochastic Comparisons Between Lifetimes of Reliability Systems with Exchangeable Components," Methodology and Computing in Applied Probability, Springer, vol. 18(4), pages 1081-1095, December.
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    Cited by:

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