Semi-Automated Classification of Arabic User Requirements into Functional and Non-Functional Requirements using NLP Tools

Abstract

Requirement engineering plays a very important role in the software development life cycle. The success or failure of a software project depends prominently on the requirement engineering phase. Requirement documents commonly have two types of requirements, one is Functional Requirements, which defines the features of the system-to-be, and the other is Non-Functional Requirements, which defines the quality attributes of the system features and development environment. They are predominantly documented in natural language. A lot of human effort is required for manual classification, which is a challenging and delicate task. Software requirements classification process has been improved in recent years by classification requirements using automated or semi-automated methods for the same purpose of Automated Software Engineering which helps developers to deliver quality software that meets users’ expectations completely with saving time and cost. In this thesis, we presented a new Semi-Automated classification approach of Arabic functional and non-functional requirements using a natural language processing tools, namely CAMeL Tools. We proposed a set of heuristics based on basic constructs of Arabic sentences in order to extract information from software requirements written in Arabic to classify the requirements vi