An Approach to Clustering and Sequencing of Textual Requirements

Abstract

Natural language is often used to write software systems requirements. However, it may be prone to misunderstandings due to its ambiguities. Moreover, it is not easy to modularize these requirements and then find all related ones. In order to find out the impact of requirements in one another, it is necessary to look at every requirement rather than just a group of related requirements. When presented in large numbers, the understanding, organization and sequencing of requirements requires substantial time and effort. In this work, we introduce an approach based both on the clustering of textual requirements and on a data dictionary to organize them, as well as suggest a sequence for their implementation. A case study based on User Stories from Agile processes is introduced to illustrate the approach.