A Bi-metric and Fuzzy c-means Based Intelligent Stakeholder Quantification System for Value-based Software

Requirements engineering (RE) deals with the software requirements elicitation, validation and verification processes and implementation of elicited requirements. The RE process, for value-based software (VBS) development, is one of the highly complex and non-linear processes which mainly depends on the key stakeholders. VBS systems are extremely different from traditional systems due to their association with financial streams. There is a need of value-based RE practices. Stakeholders’ analysis plays a vital role in the selection of critical stakeholders for RE phase in VBS development. Different stakeholders’ identification and quantification (SIQ) approaches are presented by researchers in order to identify and quantify the stakeholders. The existing approaches are not uniform in terms of process activities and different stakeholders’ attributes. Nonuniformity results in higher time consumption and higher complexity. The existing SIQ approaches are not suitable for current value-based RE practices. Hence, this research presents an intelligent decision support system for the VBS SIQP using stakeholder metrics and fuzzy logic. The data is finally divided into three clusters in order to select the highly prioritized stakeholders for VBS systems.