文章基本信息

标题：RISK BASED DECISION SUPPORT SYSTEM FOR STAKEHOLDER QUANTIFICATION FOR VALUE BASED SOFTWARE SYSTEMS
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作者：MUHAMMAD IMRAN BABAR ; MASITAH GHAZALI ; DAYANG N.A. JAWAWI 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：76
期号：3
出版社：Journal of Theoretical and Applied
摘要：Stakeholder identification and quantification (SIQ) is one of the core processes in software requirements engineering (RE). The significance of stakeholders becomes more vital when a software project is a value-based software (VBS) and the value-based requirements engineering (VBRE) is involved in it.VBS systems are developed based on business concepts in order to gain market leverage in terms of financial or economic benefits. Different SIQ approaches are presented in literature. However, most of the approaches are partially effective and SIQ process is still immature. The techniques are presented and applied under different conditions in order to monitor the performance of the approach. The presented techniques are vague and difficult to initiate. In this research, a decision support system is presented for stakeholders� quantification. The proposed system predicts the risk associated with the stakeholders using back-propagation neural network (BPNN).
关键词：Value-based Software Systems; Stakeholders; Neural Networks; Decision Support System; Expert System.