SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories
Microservices is an architectural style for service-oriented distributed computing, and is being widely adopted in several domains, including autonomous vehicles, sensor networks, IoT systems, energy systems, telecommunications networks and telemedicine systems. When migrating a monolithic system to...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2023-05-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-1380.pdf |
| _version_ | 1797827229804134400 |
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| author | Fredy H. Vera-Rivera Eduard Gilberto Puerto Cuadros Boris Perez Hernán Astudillo Carlos Gaona |
| author_facet | Fredy H. Vera-Rivera Eduard Gilberto Puerto Cuadros Boris Perez Hernán Astudillo Carlos Gaona |
| author_sort | Fredy H. Vera-Rivera |
| collection | DOAJ |
| description | Microservices is an architectural style for service-oriented distributed computing, and is being widely adopted in several domains, including autonomous vehicles, sensor networks, IoT systems, energy systems, telecommunications networks and telemedicine systems. When migrating a monolithic system to a microservices architecture, one of the key design problems is the “microservice granularity definition”, i.e., deciding how many microservices are needed and allocating computations among them. This article describes a semantic grouping algorithm (SEMGROMI), a technique that takes user stories, a well-known functional requirements specification technique, and identifies number and scope of candidate microservices using semantic similarity of the user stories’ textual description, while optimizing for low coupling, high cohesion, and high semantic similarity. Using the technique in four validation projects (two state-of-the-art projects and two industry projects), the proposed technique was compared with domain-driven design (DDD), the most frequent method used to identify microservices, and with a genetic algorithm previously proposed as part of the Microservices Backlog model. We found that SEMGROMI yields decompositions of user stories to microservices with high cohesion (from the semantic point of view) and low coupling, the complexity was reduced, also the communication between microservices and the estimated development time was decreased. Therefore, SEMGROMI is a viable option for the design and evaluation of microservices-based applications. The proposed semantic similarity-based technique (SEMGROMI) is part of the Microservices Backlog model, which allows to evaluate candidate microservices graphically and based on metrics to make design-time decisions about the architecture of the microservices-based application. |
| first_indexed | 2024-04-09T12:44:55Z |
| format | Article |
| id | doaj.art-314e21bc82c84c86835de3d3d6e15ee7 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-04-09T12:44:55Z |
| publishDate | 2023-05-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-314e21bc82c84c86835de3d3d6e15ee72023-05-14T15:05:14ZengPeerJ Inc.PeerJ Computer Science2376-59922023-05-019e138010.7717/peerj-cs.1380SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user storiesFredy H. Vera-Rivera0Eduard Gilberto Puerto Cuadros1Boris Perez2Hernán Astudillo3Carlos Gaona4Grupo de Investigación GIA, Universidad Francisco de Paula Santander, Cúcuta, Norte de Santander, ColombiaGrupo de Investigación GIA, Universidad Francisco de Paula Santander, Cúcuta, Norte de Santander, ColombiaGrupo de Investigación GIA, Universidad Francisco de Paula Santander, Cúcuta, Norte de Santander, ColombiaDepartamento de Informática, Universidad Técnica Federico Santa María, Santiago, Santiago, ChileGrupo de Investigación GEDI, Universidad del Valle, Cali, Valle del Cauca, ColombiaMicroservices is an architectural style for service-oriented distributed computing, and is being widely adopted in several domains, including autonomous vehicles, sensor networks, IoT systems, energy systems, telecommunications networks and telemedicine systems. When migrating a monolithic system to a microservices architecture, one of the key design problems is the “microservice granularity definition”, i.e., deciding how many microservices are needed and allocating computations among them. This article describes a semantic grouping algorithm (SEMGROMI), a technique that takes user stories, a well-known functional requirements specification technique, and identifies number and scope of candidate microservices using semantic similarity of the user stories’ textual description, while optimizing for low coupling, high cohesion, and high semantic similarity. Using the technique in four validation projects (two state-of-the-art projects and two industry projects), the proposed technique was compared with domain-driven design (DDD), the most frequent method used to identify microservices, and with a genetic algorithm previously proposed as part of the Microservices Backlog model. We found that SEMGROMI yields decompositions of user stories to microservices with high cohesion (from the semantic point of view) and low coupling, the complexity was reduced, also the communication between microservices and the estimated development time was decreased. Therefore, SEMGROMI is a viable option for the design and evaluation of microservices-based applications. The proposed semantic similarity-based technique (SEMGROMI) is part of the Microservices Backlog model, which allows to evaluate candidate microservices graphically and based on metrics to make design-time decisions about the architecture of the microservices-based application.https://peerj.com/articles/cs-1380.pdfMicroservicesMicro-services granularitySemantic similarityUser storiesServices computingMicro-services decompositions |
| spellingShingle | Fredy H. Vera-Rivera Eduard Gilberto Puerto Cuadros Boris Perez Hernán Astudillo Carlos Gaona SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories PeerJ Computer Science Microservices Micro-services granularity Semantic similarity User stories Services computing Micro-services decompositions |
| title | SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| title_full | SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| title_fullStr | SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| title_full_unstemmed | SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| title_short | SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| title_sort | semgromi a semantic grouping algorithm to identifying microservices using semantic similarity of user stories |
| topic | Microservices Micro-services granularity Semantic similarity User stories Services computing Micro-services decompositions |
| url | https://peerj.com/articles/cs-1380.pdf |
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