Requirement Formalisation Using Natural Language Processing and Machine Learning: A Systematic Review

descriptionPublicationkeyboard_double_arrow_right Article , Conference object , Preprint 01 Jan 2023Embargo end date: 01 Mar 2023Publisher:SCITEPRESS - Science and Technology PublicationsJournal:Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering

Authors: Shekoufeh Kolahdouz Rahimi; Kevin Lano; Chenghua Lin;

doi: 10.5220/0011789700003402 , 10.5281/zenodo.7337228 , 10.5281/zenodo.7337229 , 10.48550/arxiv.2303.13365

arXiv: 2303.13365

Requirement Formalisation Using Natural Language Processing and Machine Learning: A Systematic Review

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Abstract

Selected studies for classifying NLP and ML techniques to formalise requirement are presented in this repository.

Related Organizations

University of Roehampton
United Kingdom
King's College London
United Kingdom
University of Sheffield
United Kingdom

Keywords

Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Software Engineering, Computer Science - Computation and Language, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Requirement Formalisation, Natural Language Processing, Machine Learning, Computation and Language (cs.CL), Machine Learning (cs.LG)

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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%