Identification of microservices from monolithic applications through topic modelling

Brito, Miguel A.; Cunha, Jácome; Saraiva, João

doi:10.1145/3412841.3442016

Cited by 31 publications

(27 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, Abdullah et al, 2019's work uses dynamic analysis through the analysis of access logs and this has some limitations: the first is the overhead on the system to collect execution logs, which can be a problem on large scale systems; secondly, their approach is limited by the quality and coverage of the test cases performed to execute and collect their logs. Creating tests in an incomplete manner and with inadequate coverage will also result in an inadequate microservices proposal (Brito et al, 2021). Manual approach, despite being manual, introduce concepts and ideas that help in building an automated approach for refactoring monoliths into microservices.…”

Section: Discussionmentioning

confidence: 99%

“…Despite being a work in which there is an automatic decomposition of the monolith, Abdullah et al, 2019 not address which refactoring techniques are used and neither how the deploy process is done, giving preference to explaining the algorithm for selecting the most suitable virtual machine for each microservice. Brito et al, 2021 propose a methodology capable of identifying sets of components candidates to form microservices automatically using topic modeling and clustering techniques. To do this, a lexical extraction of all relevant terms is performed to identify what a given component represents in the context of the project domain and an extraction of structural dependencies between components is performed by analyzing an Abstract Syntax Tree (AST).…”

Section: Source-code Oriented Solutionsmentioning

confidence: 99%

“…To compare the quality of the proposed microservices Asseldonk, 2021 uses metrics proposed by the work of Jin et al, 2021 regarding independence of functionality and modularity. This work ends up going further than Brito et al, 2021 because it generates microservices proposals based on several types of analysis.…”

Section: Source-code Oriented Solutionsmentioning

confidence: 99%

“…To generate a microservices proposal for restaurantServer, to be used as input for our methodology, we used the tool developed by Brito et al, 2021 available at https://github.com/miguelfbrito/ microservice-identification. Although the tool allows the customization of the input, we use the default parameters.…”

Section: Restaurantservermentioning

confidence: 99%

See 3 more Smart Citations

Refactoring Java Monoliths into Executable Microservice-Based Applications

Freitas

Ferreira

Cunha

2021

Proceedings of the 25th Brazilian Symposium on Programming Languages

View full text Add to dashboard Cite

Refactoring de Monólitos em Java para Aplicações Baseadas em Microsserviços ExecutáveisNos últimos anos assistiu-se a uma mudança drástica na forma como o software é desenvolvido. Os projectos de software de grande escala estão a ser construídos através de uma composição flexível de pequenos componentes possivelmente escritos em diferentes linguagens de programação e com os processos de deploy independentes -as chamadas aplicações baseadas em microsserviços. Isto tem sido motivado pelos desafios associados ao desenvolvimento, manutenção e evolução de grandes sistemas de software, mas também pelo aparecimento da cloud e pela facilidade que trouxe em termos de escalabilidade horizontal, reutilização e flexibilidade na propriedade e no deploy. O crescimento dramático da popularidade dos microsserviços levou várias empresas a aplicar grandes refactorings aos seus sistemas de software. Contudo, esta é uma tarefa desafiante que pode demorar vários meses ou mesmo anos.Esta dissertação propõe uma metodologia capaz de transformar automaticamente aplicações desenvolvidas em Java sob uma arquitetura monolítica em aplicações baseadas em microserviços. A metodologia proposta é direccionada para as aplicações que tiram partido da técnica ORM para relacionar classes com as entidades da base de dados, através de anotações no código fonte. A nossa abordagem recebe como input o código fonte e uma proposta de microsserviços, e aplica técnicas de refactoring às classes para tornar cada microsserviço independente. Esta metodologia cria uma API para cada chamada de métodos de classes que se encontram noutros serviços, e as entidades da base de dados também sofrem refactoring para serem incluídas no serviço correspondente. A metodologia proposta foi implementada através da construção de uma ferramenta que suporta o refactoring de aplicações desenvolvidas em Java Spring e que utilizam as anotações da JPA para o mapeamento entre as classes e as entidades.Realizou-se um análise quantitativa e qualitativa em 120 projetos open-source aleatoriamente recolhidos do GitHub. Na avaliação quantitativa procurou-se perceber a aplicabilidade da metodologia e na analise qualitativa, através da execução de testes unitários, procurou-se avaliar se aplicação original e a aplicação baseada em microserviços gerada são funcionalmente equivalentes.Os resultados são promissores sendo a metodologia capaz de realizar o refactoring em 69% dos projetos, sendo o resultado da execução dos testes unitários igual em ambas as versões dos projetos.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Source-code Oriented Solutionsmentioning

confidence: 99%

Section: Source-code Oriented Solutionsmentioning

confidence: 99%

Section: Restaurantservermentioning

confidence: 99%

See 2 more Smart Citations

Refactoring Java Monoliths into Executable Microservice-Based Applications

Freitas

Ferreira

Cunha

2021

Proceedings of the 25th Brazilian Symposium on Programming Languages

View full text Add to dashboard Cite

show abstract

“…Cosine Similarity is basically a measurement that quantifies the similarity between two or more vectors. Cosine Similarity is a common approach and has been used in many other related studies for microservice identification[20],[21]. This score indicates how much two use cases are related in terms of accessing the database entities.…”

mentioning

confidence: 99%

GreenMicro: Identifying Microservices From Use Cases in Greenfield Development

2022

View full text Add to dashboard Cite

Microservices architecture is a new paradigm for developing a software system as a collection of independent services that communicate through lightweight protocols. In greenfield development, identifying the microservices is not a trivial task, as there is no legacy code lying around and no old development to start with. Thus, identification of microservices from requirements becomes an important decision during the analysis and design phase. Use cases play a vital role in the requirements analysis modeling phases in a model-driven software engineering process. It is a technique of capturing high-level user functions and scope of the system. In this paper, we propose GreenMicro, an automatic microservice identification technique that utilizes the use cases model and the database entities. Both features are the artifacts of analysis and design phase that depict complete functionality of an overall system. In essence, a collection of related use cases indicates a bounded context of the system that can be grouped in a suitable way as microservices. Therefore, our approach GreenMicro clusters close-knit use cases to recover meaningful microservices. We investigate and validate our approach on an in-house proprietary web application and three sample benchmark applications. We have mapped our approach to state-of-the-art software quality assessment attributes and have presented the results. Preliminary results are motivating and the proposed methodology works as anticipated in producing functionally cohesive and loosely coupled microservice candidate recommendations. Our approach enables the system architects to identify microservice candidates at an early analysis and design phase of development.

show abstract

From legacy to microservices: A type‐based approach for microservices identification using machine learning and semantic analysis

Trabelsi

Abdellatif

Abubaker

et al. 2022

J Software Evolu Process

View full text Add to dashboard Cite

The microservices architecture (MSA) style has been gaining interest in recent years because of its high scalability, ability to be deployed in the cloud, and suitability for DevOps practices. While new applications can adopt MSA from their inception, many legacy monolithic systems must be migrated to an MSA to benefit from the advantages of this architectural style. To support the migration process, we propose MicroMiner, a microservices identification approach that is based on static‐relationship analyses between code elements as well as semantic analyses of the source code. Our approach relies on machine learning (ML) techniques and uses service types to guide the identification of microservices from legacy monolithic systems. We evaluate the efficiency of our approach on four systems and compare our results to ground‐truths and to those of two state‐of‐the‐art approaches. We perform a qualitative evaluation of the resulted microservices by analyzing the business capabilities of the identified microservices. Also a quantitative analysis using the state‐of‐the‐art metrics on independence of functionality and modularity of services was conducted. Our results show the effectiveness of our approach to automate one of the most time‐consuming steps in the migration of legacy systems to microservices. The proposed approach identifies architecturally significant microservices with a 68.15% precision and 77% recall.

show abstract

Identification of microservices from monolithic applications through topic modelling

Cited by 31 publications

References 34 publications

Refactoring Java Monoliths into Executable Microservice-Based Applications

Refactoring Java Monoliths into Executable Microservice-Based Applications

GreenMicro: Identifying Microservices From Use Cases in Greenfield Development

From legacy to microservices: A type‐based approach for microservices identification using machine learning and semantic analysis

Contact Info

Product

Resources

About