A review of the generation of requirements specification in natural language using objects UML models and domain ontology

Journal article

Abdalazeima, Alaa and Meziane, Farid 2021. A review of the generation of requirements specification in natural language using objects UML models and domain ontology. Procedia Computer Science. 189, pp. 328-334. https://doi.org/10.1016/j.procs.2021.05.102
AuthorsAbdalazeima, Alaa and Meziane, Farid
Abstract

In the software development life cycle, requirements engineering is the main process that is derived from users by informal interviews written in natural language by requirements engineers (analysts). The requirements may suffer from incompleteness and ambiguity when transformed into formal or semi-formal models that are not well understood by stakeholders. Hence, the stakeholder cannot verify if the formal or semi-formal models satisfy their needs and requirements. Another problem faced by requirements is that when code and/or designs are updated, it is often the case that requirements and specifically the requirements document are not updated. Hence ending with a requirements document not reflecting the implemented software.Generating requirements from the design and/or implementation document is seen by many researchers as a way to address the latter issue. This paper presents a survey of some works undertaken in the field of generation natural language specifications from object UML model using the support of an ontology. and analyzing the robustness and limitations of these existing approaches. This includes studying the generation of natural language from a formal model, review the generation of natural language from ontologies, and finally reviews studies about check to generate natural language from OntoUML.

KeywordsRequirements Specification; Natural Language Generation; Object UML Model; Ontology
Year2021
JournalProcedia Computer Science
Journal citation189, pp. 328-334
PublisherElsevier
ISSN18770509
Digital Object Identifier (DOI)https://doi.org/10.1016/j.procs.2021.05.102
Web address (URL)http://hdl.handle.net/10545/626344
http://creativecommons.org/licenses/by-nd/4.0/
hdl:10545/626344
Publication dates14 Jul 2021
Publication process dates
Deposited07 Mar 2022, 12:30
Accepted12 Apr 2021
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© 2021 The Author(s). Published by Elsevier B.V.

Attribution-NoDerivatives 4.0 International

ContributorsUniversity of Bahri, Sudan and University of Derby
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