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Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method

In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learning models provides numerous advantages for the sof...

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Autor principal: Alshammari, Fahad H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556201/
https://www.ncbi.nlm.nih.gov/pubmed/36248934
http://dx.doi.org/10.1155/2022/1960684
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author Alshammari, Fahad H.
author_facet Alshammari, Fahad H.
author_sort Alshammari, Fahad H.
collection PubMed
description In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learning models provides numerous advantages for the software development industry. Testing and maintaining software is a critical concern today. Software engineers have many responsibilities while developing a software system, including coding, testing, and delivering the software to users via the cloud. From this list, it is easy to see that each task calls for extensive organization and preparation, as well as access to a variety of resources. A developer may consult other code repositories, websites with related programming content, and even colleagues for information before attempting to build and test a solution to the problem at hand. In this investigation, we aim to identify the factors that led to developing the recommender. This system analyzes the recommender's performance and provides suggestions for improving the software based on users' opinions.
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spelling pubmed-95562012022-10-13 Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method Alshammari, Fahad H. Comput Intell Neurosci Research Article In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learning models provides numerous advantages for the software development industry. Testing and maintaining software is a critical concern today. Software engineers have many responsibilities while developing a software system, including coding, testing, and delivering the software to users via the cloud. From this list, it is easy to see that each task calls for extensive organization and preparation, as well as access to a variety of resources. A developer may consult other code repositories, websites with related programming content, and even colleagues for information before attempting to build and test a solution to the problem at hand. In this investigation, we aim to identify the factors that led to developing the recommender. This system analyzes the recommender's performance and provides suggestions for improving the software based on users' opinions. Hindawi 2022-10-05 /pmc/articles/PMC9556201/ /pubmed/36248934 http://dx.doi.org/10.1155/2022/1960684 Text en Copyright © 2022 Fahad H. Alshammari. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Alshammari, Fahad H.
Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title_full Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title_fullStr Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title_full_unstemmed Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title_short Trends in Intelligent and AI-Based Software Engineering Processes: A Deep Learning-Based Software Process Model Recommendation Method
title_sort trends in intelligent and ai-based software engineering processes: a deep learning-based software process model recommendation method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556201/
https://www.ncbi.nlm.nih.gov/pubmed/36248934
http://dx.doi.org/10.1155/2022/1960684
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