From last few decades, researchers and practitioners have well recognized the significance of Requirements Engineering. Requirements Engineering stage is the foundation stone on which the entire building named software can be built. There are several Requirements Engineering (RE) techniques exists but requirements engineer choose a specific technique for a particular software project with their own preferences or organization standards. There is not only little guidance available for analyzing Requirements Engineering techniques but also all the existing researches focus on qualitative measures. There is no consideration of physical measures while analyzing and accepting a technique for a particular project. Nowadays customers satisfaction is also gaining great importance so customer perspective should also be taken into account. We have performed deep literature review and noted that analysis and selection of Requirements Engineering technique should consider all relevant attributes of each techniques and their mapping with project, people or other factors. There is a need to thoroughly comprehend and evaluate all the existing techniques with respect to analyst preferences, client experiences, project attributes, software process model characteristics. To do so, fuzzy clustering method is implemented in MATLAB. The key emphasis of this paper is to study and list all possible Requirements Engineering techniques related to Elicitation, Prioritization, Documentation, Verification and Validation, etc. The research work also analyzes attributes of each RE technique using Fuzzy C mean clustering and K mean clustering methods. The results of clustering provide a set of techniques, from which requirements engineer can select for specific phase of Requirements Engineering. The substantiation of the research work is done with the help of a case study that is having some known problem domain characteristics
A Proposal of a Process Model for Requirements Elicitation in Information Mining Projects
