Intelligent Requirement Prioritization using Fuzzy Logic

Abstract

Software Engineering (SE) is one of the youngest engineering domains emerging and developing within past four decades or so. Still, a massive amount of research work has gone into shaping it the way we see it functioning today. As a result, we have an impressive knowledge repository to work with in the form of software development models, software engineering theories and practices etc. The aim of SE is to create software products, services or their artifacts in order to meet the requirements posed by stakeholders while meeting quality constraints imposed on them. In order to meet both these objectives, any software development derives its purpose and meaning from the requirements posed by various stakeholders. Requirement Prioritization is a very critical but often neglected area of requirement engineering. Experience has shown that without proper prioritization of requirements presented by various stakeholders, the end product usually fails to meet its objectives optimally. In fact in many instances, the product is considered a failure because it fails to meet its core objectives. Several requirement prioritization techniques have been presented by various researchers over the past years. Working with these techniques has exposed several limitations when applied in software projects. In this thesis, we have presented a novel multi-level value based intelligent requirement prioritization technique using fuzzy logic and as a facilitating process, we have redefined the “value” of software to better meet its objectives. We have introduced and applied the concept of requirement value to prioritize requirements. We have performed extensive experimentation using our proposed technique along with existing techniques. Results have shown that both our proposed definition and proposed technique have achieved superior prioritization results and consistency. The experiments have also shown that proposed technique is capable of delivering impressive prioritization under varying and often conflicting circumstances.