Browsing by Author "Arias Barros, Jhoan Sebastian"

Now showing 1 - 2 of 2

Desarrollo de un proceso de creación y despliegue de microservicios a partir de requerimientos funcionales
(Universidad de Cuenca, 2023-07-17) Arias Barros, Jhoan Sebastian; Suquisupa Nacipucha, Pamela Aracely; Saquicela Galarza, Víctor Hugo
With the gradual advancement of microservices-based software architectures and the increas- ing relevance of requirements engineering in the development of applications and web sys - tems, there is a need for methods or processes that automate the creation and deployment of microservices. The combination of Natural Language Processing (NLP) techniques with graph analysis and community detection offers a powerful approach to address challenges in various fi el ds. In the real m of software engi neeri ng, this combi nati on has been expl ored to enh ance the design and deployment process of microservices-based architectures. Additionally, in recent times, language models of artificial intelligence, such as ChatGPT, have gained great popu - larity and attention in various domains. The ability to improve and generate existing text has sparked interest among researchers, companies, and users in general. In this context, the fol- lowing thesis work proposes a process for the identification and deployment of microservices, leveraging the advantages of natural language processing techniques and graph analysis. It is expected that this approach will contribute to improving and automating the development of microservices-based applications.
Generation of Microservice Names from Functional Requirements: An Automated Approach
(Springer Science and Business Media Deutschland GmbH, 2024) Granda Juca, María Fernanda; Saquicela Galarza, Víctor Hugo; Arias Barros, Jhoan Sebastian; Suquisupa Nacipucha, Pamela Aracely
In the context of the advancement of software architectures based on microservices and the relevance of requirements engineering in application development, the problem of manual creation and the need for expertise to define microservices, a human activity that requires a high level of knowledge and experience, arises. To address this challenge, a solution is proposed that consists of finding the ideal names for microservices. To automate the process of identifying microservice names, this proposal is based on the application of Natural Language Processing (NLP) techniques, graph analysis and community detection, including the use of artificial intelligence language models such as ChatGPT.