IEEE (1990) definem testes de integra¸c˜ao como testes em que os componentes de software, componentes de hardware ou ambos s˜ao combinados e testados para avaliar e validar as intera¸c˜oes entre os componentes. Este tipo de testes s˜ao aplicados frequentemente a APIs REST, consumindo as respostas dadas pelos recursos da API e verificando a validade das mesmas.
O xUnit.net3´e uma ferramenta open source utilizada para testar as estruturas
de software NET Framework e .NET Core. Os testes de integra¸c˜ao foram escritos com recurso `a ferramenta xUnit.net para testar as respostas da API de processamento do Swish, que incluem a tentativa de desserializa¸c˜ao dos objetos JSON devolvidos.
6.4
Considera¸c˜oes finais
Neste cap´ıtulo foram referidos alguns dos testes realizados e o impacto de tiveram na plataforma. Os testes no desenvolvimento de software s˜ao essenciais e usados como uma garantia de qualidade do trabalho realizados (Bertolino, 2007).
Foram realizados testes de funcionalidades b´asicas, entre v´arios dispositivos e navegadores Web, testes de qualidade de c´odigo com recurso ao SonarQube para aferir a qualidade do c´odigo escrito e testes de integra¸c˜ao, com recurso ao xUnit.net, para testar as intera¸c˜oes entre os v´arios componentes que constituem a solu¸c˜ao criada.
7
Conclus˜ao
O projeto presente nesta disserta¸c˜ao come¸cou com realiza¸c˜ao de um levantamento bibliogr´afico sobre a an´alise de dados espa¸cotemporais no desporto, com ˆenfase em plataformas que consigam aceitar este tipo de ficheiro e produzir visualiza¸c˜oes relevantes para os analistas. Ap´os este processo seguiram-se v´arias reuni˜oes com membros do CIDESD para determinar o conjunto de funcionalidades que a plataforma deveria possuir e de que forma poderiam ser criadas algumas das intera¸c˜oes. O planeamento foi exposto no cap´ıtulo da modelagem conceptual em que foram analisados os ficheiros com dados espa¸cotemporais disponibilizados, definido o modelo conceptual de classes e a proposta de arquitetura.
Na sequˆencia deste trabalho de investiga¸c˜ao e planeamento surgiu o Swish, uma aplica¸c˜ao Web feita em ASP.NET Core com uma base de dados em MySQL para a an´alise e a recria¸c˜ao 2D de jogos de desportos de invas˜ao, que aceita dados espa¸cotemporais de diferentes provedores. As an´alises incluem o c´alculo de distˆancias e velocidades, a an´alise de comportamento de grupos, mapas de calor, diagrama de Voronoi e entropias. Os dados s˜ao calculados por uma API de processamento feita com o ASP.NET Core Web API e mostrados aos utilizadores atrav´es de visualiza¸c˜oes criadas com recurso ao D3.js.
90 CAP´ITULO 7. CONCLUS ˜AO
Na segunda fase do projeto foi proposta a transforma¸c˜ao do Swish num produto, tendo sido escolhido o modelo multi-instance SaaS para a constru¸c˜ao da plataforma, com recurso a tecnologias como o Docker, Traefik e Portainer. Para a autentica¸c˜ao foi usado um modelo de autentica¸c˜ao centralizada com Single Sign-On, que permite a existˆencia de um ponto ´unico de autentica¸c˜ao para toda a plataforma, algo fundamental num SaaS. O IdentityServer4 foi usado em conjunto com o ASP.NET Identity numa aplica¸c˜ao ASP.NET Core para criar todo o sistema de autentica¸c˜ao. Para suportar as tarefas de gest˜ao de instˆancias e utilizadores foi criada uma aplica¸c˜ao em ASP.NET Core com uma base de dados em MySQL.
Em suma, as contribui¸c˜oes fornecidas com a realiza¸c˜ao do projeto que deu origem a esta disserta¸c˜ao foram:
• Estado da arte sobre sistemas que fa¸cam a an´alise de dados desportivos e que produzam visualiza¸c˜oes ´uteis para o analistas.
• O Swish, uma aplica¸c˜ao Web para a an´alise e a recria¸c˜ao 2D de jogos de desportos de equipa, que aceite dados produzidos pelos dispositivos de localiza¸c˜ao mais populares. As an´alises incluem o c´alculo de distˆancias e velocidades, a an´alise de comportamento de grupos, mapas de calor e diagrama de Voronoi. • Um sistema de autentica¸c˜ao centralizada, que controla o acesso a v´arias aplica¸c˜oes
e instˆancias.
• Um sistema de gest˜ao de instˆancias, com o objetivo de facilitar o processo de administra¸c˜ao das instˆancias e utilizadores existentes na plataforma.
7.1
Trabalho futuro
O ramo da an´alise de dados espa¸cotemporais desportivos ´e uma ´area em constante crescimento, com novas vari´aveis e formas de analisar os jogos a surgirem com frequˆencia. Delibas et al.(2018) usaram inteligˆencia artificial para prever a equipa que tem a posse da bola e para avaliar a probabilidade de sucesso de um passe. O
7.1. TRABALHO FUTURO 91
futuro do Swish ir´a passar pela aplica¸c˜ao de algumas destas t´ecnicas que se revelem ´
uteis para o trabalho realizado pelos analistas.
Um dos diagramas mais interessantes para se incluir num trabalho futuro seria o diagrama de Voronoi com pesos, que tivesse em conta a dire¸c˜ao e velocidade dos jogadores. A inclus˜ao deste diagrama permitiria o c´alculo da zonas de dominˆancia dos jogadores e equipas com maior precis˜ao (Taki and Hasegawa,1998).
A dete¸c˜ao dos passes a partir dos dados espa¸cotemporais e a posterior visualiza¸c˜ao pode ser ´util para a dete¸c˜ao de padr˜oes de passe nas equipas e de que forma estes influenciam a performance da equipa (Gon¸calves et al., 2017).
Neste momento o Swish s´o ´e compat´ıvel com os sistemas de tracking usados para a capta¸c˜ao dos 3 ficheiros fornecidos para a realiza¸c˜ao deste trabalho. A aplica¸c˜ao est´a preparada para que possam ser adicionados mais algoritmos de importa¸c˜ao, que permitem a inser¸c˜ao de ficheiros de provedores diferentes.
No caso da aplica¸c˜ao de gest˜ao de instˆancias, a integra¸c˜ao com um sistema de pagamento poderia ser ´util para um melhor controlo dos clientes. Poderiam ainda ser feitas altera¸c˜oes nos dados enviados para as instˆancias, passando a ser inclu´ıdas informa¸c˜oes relativas `as funcionalidades que as instˆancias podem usar. Desta forma seria poss´ıvel a cria¸c˜ao de pacotes de c´alculo de vari´aveis e diagramas, com pre¸cos diferentes e que se adaptassem `as necessidades dos utilizadores da organiza¸c˜ao espec´ıfica.
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