ADAPTIVE FUZZY HIERARCHICAL CUMULATIVE VOTING: A NOVEL APPROACH TOWARD REQUIREMENT PRIORITIZATION

Abstract

In Software Engineering (SE) process Requirement Engineering (RE) is considered as an important part in Software Development Life Cycle (SDLC). Requirement Prioritization is very useful for making good decisions about product plan but most of the times it is ignored. In many cases it is seem that the product fails to meet its core objectives because lack of proper prioritization. Increased emphasis on requirement prioritization and high changing requirements makes management of composite services time consuming and a complicated task. When a project has tight schedule, restricted resources and high customer expectations, it becomes necessary to deploy the most critical and important features as early as possible. The problem can be solved by prioritizing the requirements. In Software Engineering process numbers of requirement prioritization methods are already present. This paper shows the comparison of some of these techniques and based on its advantages and disadvantages a new technique 'Adaptive Fuzzy Hierarchical Cumulative Voting' is proposed. Fuzzy logic is used with adaptation mechanism, to target the situations where composite service behaviour can be deviated from customer expectations and to also deal with uncertainty and ambiguity. The proposed Adaptive Fuzzy Hierarchical Cumulative Voting includes the analysis of different self-adaptive properties such as self-heal, self-configure, self-optimize, self-protect and the addition to Fuzzy HCV, in order to increase the coverage of events that can occur at runtime. It may be useful to prioritize the requirements at run time.