SPHANDLER: MULTI-CRITERIA BASED INTELLIGENT STAKEHOLDER QUANTIFICATION SYSTEM FOR VALUE-BASED SOFTWARE

Value-based is a popular term for software systems which deal with financial matters. For development of value-based software (VBS) systems the software requirements engineering (RE) process must be robust. The RE process is concerned with exploration, verification and validation of key software requirements for a given VBS system. Highly valuable requirements are required in order to design a VBS product. A set of highly valuable requirements can only be obtained from key stakeholders. Stakeholders are the entities considered as vital in success and failure of the software system. Different approaches are represented by researchers in the domain of stakeholders’ analysis. The existing stakeholders’ analysis approaches focus the problem in a diverse range of dimensions. The processes used in these approaches vary from each other and the use of stakeholder attributes is not uniform. The approaches are highly obscure in terms of guidelines for value quantification of stakeholders. In this research, a neuro-fuzzy inspired intelligent decision support system SPHandler is proposed for identification and quantification of VBS stakeholders using stakeholder metrics, Neural Network and Fuzzy C-Means in order to cope with issue of stakeholder quantification. The proposed system is efficient in terms of performance and reduces the bias induced by the experts during stakeholders’ evaluation.