A Novel Framework to Automatically Generate IFML Models From Plain Text Requirements

• Main Authors: Maryum Hamdani, Wasi Haider Butt, Muhammad Waseem Anwar, Imran Ahsan, Farooque Azam, Mudassar Adeel Ahmed
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: IFML; NLP; T2IF tool; user interfaces; artificial intelligence
• Online Access: https://ieeexplore.ieee.org/document/8933019/

User Interfaces (UI's) are highly important in this era of web and mobile applications. Therefore, an efficient and accurate development of UI's is desirable in early Software Development Life Cycle (SDLC) phases. To achieve this, Object Management Group (OMG) introduced Interaction Flow Modeling Language (IFML) standard in 2013. IFML provides the modeling of manifold UI's for different applications like mobile, web and desktop. Although IFML is based on Model Driven Engineering (MDE) principle, the development of user interface models from initial requirements is still complex and time consuming task. Particularly, it requires domain expertise to understand several IFML concepts like domain model, view container etc. for the proper modeling of user interfaces. Consequently, there is a strong need of an approach to automate the development of IFML models from initial plain text requirements. This article presents a novel framework to automatically generate IFML models from textual requirements by utilizing the features of Natural Language Processing (NLP). Particularly, a set of NLP rules are developed to extract important IFML elements like View Components, Events etc. from textual requirements. Furthermore, a comprehensive algorithm is developed for the systematic execution of NLP rules in order to generate both IFML Domain and Core models. As a part of research, a sophisticated $T$ ext to IF ML (T2IF) tool is developed. The feasibility of proposed framework is demonstrated through movie manager and online bookstore case studies. The evaluation results prove that the proposed framework is capable of generating IFML models from textual requirements with high accuracy.