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Probabilistic Graphical Framework for Predicting Software Project Risk

Authors
Ahn, GilseungKwon, MinsungKang, ChangwookHur, Sun
Issue Date
Mar-2018
Publisher
KOREAN INST INDUSTRIAL ENGINEERS
Keywords
Project Management; Project Risk Management; Software Project Management; Conditional Random Field; Risk Prediction
Citation
INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, v.17, no.1, pp.120 - 127
Indexed
SCOPUS
KCI
Journal Title
INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS
Volume
17
Number
1
Start Page
120
End Page
127
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/6426
DOI
10.7232/iems.2018.17.1.120
ISSN
1598-7248
Abstract
Project risk management is currently one of the main topics of interest for researchers and practitioners working in the area of project management. Risk management has been designated as one of the ten subject areas of the Project Management Body of Knowledge by the Project Management Institute. Since project risk management is closely associated with other project management areas, it is important to manage project risk in detail. In this paper, we suggest a method to predict software project risk by means of probabilistic graphical model. Concretely, we identify software development process referring to ISO/IEC 12207, an international standard for software lifecycle processes and construct a probabilistic model to predict risks. The framework we suggest not only forecasts the risks, but also finds critical factors to analyze project risk.
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ERICA 공학대학 (DEPARTMENT OF INDUSTRIAL & MANAGEMENT ENGINEERING)
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