Abstract
Conceptual class model is an essential design artifact of Software Development Life Cycle (SDLC). The involvement of several resources and additional time is required to generate the class model from early software requirements. On the other hand, Natural Language Processing (NLP) is a knowledge discovery approach to automatically extract elements of concern from initial plain text documents. Consequently, it is frequently utilized to generate various SDLC artifacts like class model from the early software requirements. However, it is usually required to perform few manual processing on textual requirements before applying NLP techniques that makes the whole process semi-automatic. This article presents a novel fully automated NLP approach to generate conceptual class model from initial software requirements. As a part of research, Automated Requirements 2 Design Transformation (AR2DT) tool is developed. The validation is performed through three benchmark case studies. The experimental results prove that the proposed NLP approach is fully automated and considerably improved as compared to the other state-of-the-art approaches.
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Ahmed, M.A., Butt, W.H., Ahsan, I., Anwar, M.W., Latif, M., Azam, F. (2017). A Novel Natural Language Processing (NLP) Approach to Automatically Generate Conceptual Class Model from Initial Software Requirements. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_55
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