A proposed model for eliminating nonfunctional requirements in Agile Methods using natural language processes

A critical step in the creation of software is the elicitation of requirements. According to most of the research, nonfunctional requirements get less attention from nonfunctional requirements, also necessary for the creation of every new application. A poor choice of elicitation causes the system to malfunction. Without the use of an elicitation approach, the needs and requirements of users cannot be ascertained. Ensuring efficient communication between analysts and users during the elicitation process is the biggest challenge for analysts. This study’s major artifact is a proposed model that creates a conceptual model automatically from a series of agile requirements given as user stories. The accuracy, especially when user stories are succinct assertions that identify the issue to be handled, was one of our case study’s positive outcomes. The objective was to prove that artificial intelligence can be used to elicit software requirements for software systems, and the findings support this claim. An elicitation model for NFR in agile methodology is proposed by this work. The approach will help the software business identify and collect needs for all kinds of software. as well as directing both users and developers in the development of software. Due to the elicitations of both FRs and NFRs of the initial phase in agile projects, which receive less attention, this study decreased the time, effort, and risk.