Análise de Repositórios GIT com Recurso a GraphQL

• Autor(a) principal: Pinto, Miguel de Morais Teixeira
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.22/20850
• topic: GraphQL; Microservices; GIT

Currently, GIT repositories analysis tools play an important role in all software development teams, as they allow a detailed analysis of the interaction of all team members. It is important for a team leader to understand if the team is in fact being productive, and if not, he can use these tools to understand what can be improved to achieve that goal. In 2012, facebook launched a query language called GraphQL, which was only released to the general public in 2015. Since then, this language has been gaining more and more popularity, being touted as a possible successor to the REST API. This language has several advantages, namely in terms of application performance and flexibility. Currently this language is already used by large companies such as Facebook, Netflix, GitHub and PayPal. Given the evolution of the language, the possibility of creating a solution capable of providing a GraphQL API emerged in an academic context. As the use of this tool is often associated with a microservices architecture, this architecture was also chosen for the construction of the solution. The fact that both are recent concepts also contributes to the choice, thus ensuring a greater ease of updating the solution over time. One of the conclusions of this study is that the use of a GraphQL API makes it easier for the user to obtain the desired answer. It is not possible to say that the use of GraphQL is always advantageous over the use of REST, being necessary to evaluate for any solution which tool is most justified or else the use of both simultaneously, which is also a possibility. Regarding the integrated tools, it was also concluded that the application of MapReduce techniques does not improve the performance of the solution, producing exactly the opposite effect.