Sinplafut: A microservices – based application for soccer training

Abstract

Microservices are an architectural style of service-oriented applications that allow the application to be divided into independent and autonomous units, which can be individually developed, tested, deployed (mainly in the cloud), scaled and monitored. The application then becomes a composition and integration of small distributed systems. In this paper, a case study is presented, where the Information system for the planning of soccer training, is developed, following the architectural style of microservices. It presents the architecture defined for the information system and its implementation using DevOps practices, among them, continuous delivery, continuous deployment and automated tests. The level of granularity of each microservice is evaluated using domain-driven design and the definition of delimited contexts. Defining the optimal size of microservices is fundamental, directly affecting performance, maintainability, storage, transactions, distributed queries, use and consumption of network and computational resources. On the other hand, the development of the information system allows improving the planning of soccer training using modern sports training techniques. System for the planning of soccer training can be used by soccer teams, clubs, physical trainers, coaches and technical directors both amateur and professional, as a software as a service application.

SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories

“… Create grouping algorithm: It was implemented in Python using the artificial intelligence and natural language processing libraries Spacy ( Spacy.io, 2020 ) for vector algebra and distance between points. Evaluation of a case study: The evaluation was carried out in two academic projects (Cargo Tracking ( Baresi, Garriga & De Renzis, 2017 ) and JPetStore ( Jin et al, 2019 )) and two industry projects (Foristom Conferences and Sinplafut ( Vera-Rivera, Vera-Rivera & Gaona-Cuevas, 2019 )). Compare the results of the algorithm with other methods: We compared the decompositions proposed by our algorithm with those proposed by other state-of-the-art microservices identification methods: domain-driven design (DDD), service cutter ( Gysel et al, 2016 ), Microservices identification trough interface analysis (MITIA) ( Baresi, Garriga & De Renzis, 2017 ), and our own genetic programming technique ( Vera-Rivera, Gaona & Astudillo, 2021 ).…”

“…Evaluation of a case study: The evaluation was carried out in two academic projects (Cargo Tracking ( Baresi, Garriga & De Renzis, 2017 ) and JPetStore ( Jin et al, 2019 )) and two industry projects (Foristom Conferences and Sinplafut ( Vera-Rivera, Vera-Rivera & Gaona-Cuevas, 2019 )).…”

“…We validated SEMGROMI with the same three projects used to validate MB, namely Cargo Tracking ( Baresi, Garriga & De Renzis, 2017 ; Li et al, 2019 ), JPetStore ( Jin et al, 2019 ; Saidani et al, 2019 , Ren et al, 2018 ) and Foristom Conferences ( Vera-Rivera et al, 2021 ). We have also evaluated it with Sinplafut ( Vera-Rivera, Vera-Rivera & Gaona-Cuevas, 2019 ), an industrial case study with 92 user stories. Design time metrics were adapted and calculated to evaluate the granularity level of each microservice in the proposed decomposition.…”

“…The proposed technique was validated with actual projects from a state-of-the-art review ( Vera-Rivera, Gaona & Astudillo, 2021 ; Vera-Rivera, Gaona Cuevas & Astudillo, 2019 ). We did not find a catalog of projects with user stories available for testing and comparing state-of-the-art methods, but we were able to use four interesting candidates: two educational projects (Cargo Tracking ( Baresi, Garriga & De Renzis, 2017 ; Li et al, 2019 ) and JPetStore ( Jin et al, 2019 ; Saidani et al, 2019 ; Ren et al, 2018 )) and two industry projects (Foristom Conferences ( Vera-Rivera et al, 2021 ) and Sinplafut ( Vera-Rivera, Vera-Rivera & Gaona-Cuevas, 2019 )). In general, it’s hard to find test data from software systems developed with microservices that also include a requirements document or user stories.…”