Requirement Prioritization Using Adaptive Fuzzy Hierarchical Cumulative Voting

Requirement prioritization is very useful for making decisions about product plan but most of the time it is ignored. In many cases it seems that the product hardly attains its principal objectives due to improper prioritization. Increased emphasis on requirement prioritization and highly dynamic requirements makes management of composite services time consuming and difficult task. When software project has rigid timelines, limited resources, but high client expectations, an instantaneous deployment of most vital and critical features becomes mandatory. The problem can be solved by prioritizing the requirements. Over the past years, various techniques for requirement prioritization are presented by a variety of researchers in software engineering domain. The proposed Adaptive Fuzzy Hierarchical Cumulative Voting (AFHCV) uses adaptive mechanism with existing Fuzzy Hierarchical Cumulative Voting (FHCV) technique, in order to increase the coverage of events that can occur at runtime. The adaptive mechanism includes Addition of new requirement set, Analysis and Reallocation of requirements, Assignment and Alteration of priorities and Re-prioritization. The re-prioritization is used to improve the results of proposed AFHCV. The proposed system compares the results of proposed AFHCV technique to the existing FHCV technique and the comparison shows the proposed AFHCV yields better results than FHCV.