Research Article
Automated Use Case Diagram Generation with Non-functional Requirements using Neural Network
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
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| Volume 12 - Issue 34 |
| Published: October 2020 |
| Authors: Israa Abdulruof Othman Ahmed, Mubarak Elamin Elmubarak Daleel |
10.5120/ijais2020451885
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Israa Abdulruof Othman Ahmed, Mubarak Elamin Elmubarak Daleel . Automated Use Case Diagram Generation with Non-functional Requirements using Neural Network. International Journal of Applied Information Systems. 12, 34 (October 2020), 1-4. DOI=10.5120/ijais2020451885
@article{ 10.5120/ijais2020451885,
author = { Israa Abdulruof Othman Ahmed,Mubarak Elamin Elmubarak Daleel },
title = { Automated Use Case Diagram Generation with Non-functional Requirements using Neural Network },
journal = { International Journal of Applied Information Systems },
year = { 2020 },
volume = { 12 },
number = { 34 },
pages = { 1-4 },
doi = { 10.5120/ijais2020451885 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2020
%A Israa Abdulruof Othman Ahmed
%A Mubarak Elamin Elmubarak Daleel
%T Automated Use Case Diagram Generation with Non-functional Requirements using Neural Network%T
%J International Journal of Applied Information Systems
%V 12
%N 34
%P 1-4
%R 10.5120/ijais2020451885
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The Unified Modeling Language (UML) is an excellent and well known powerful recognized leading diagrammatic modeling language. Recently, there have many efforts addressing automating these models, such as the Use Cases model where natural languages are used and giving the system a set of rules to be able to extract the actors and use cases from textual requirements. These rules confirm that all user requirements are included there in .In this paper a model has been developed using natural languages in addition to neural networks where the network is trained in the way of extracting Functional and nonfunctional requirements, which helps in producing more effective models that minimizing the time and effort of both the user and the analyst.
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