A curated dataset of microservices-based systems
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
Original language | English |
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Title of host publication | SSSME-2019 |
Subtitle of host publication | Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution |
Publisher | CEUR-WS |
Publication status | Published - 2019 |
Publication type | A4 Article in a conference publication |
Event | Joint of the Summer School on Software Maintenance and Evolution - Tampere, Finland Duration: 2 Sep 2019 → 4 Sep 2019 |
Publication series
Name | CEUR Workshop Proceedings |
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Volume | 2520 |
ISSN (Print) | 1613-0073 |
Conference
Conference | Joint of the Summer School on Software Maintenance and Evolution |
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Country | Finland |
City | Tampere |
Period | 2/09/19 → 4/09/19 |
Abstract
Microservices based architectures are based on a set of modular, independent and fault-tolerant services. In recent years, the software engineering community presented studies investigating potential, recurrent, effective architectural patterns in microservices-based architectures, as they are very essential to maintain and scale microservice-based systems. Indeed, the organizational structure of such systems should be reflected in so-called microservice architecture patterns, that best fit the projects and development teams needs. However, there is a lack of public repositories sharing open sources projects microservices patterns and practices, which could be beneficial for teaching purposes and future research investigations. This paper tries to fill this gap, by sharing a dataset, having a first curated list microservice-based projects. Specifically, the dataset is composed of 20 open-source projects, all using specific microservice architecture patterns. Moreover, the dataset also reports information about inter-service calls or dependencies of the aforementioned projects. For the analysis, we used two different tools (1) SLOCcount and (2) MicroDepGraph to get different parameters for the microservice dataset. Both the microservice dataset and analysis tool are publicly available online. We believe that this dataset will be highly used by the research community for understanding more about microservices architectural and dependencies patterns, enabling researchers to compare results on common projects.
ASJC Scopus subject areas
Keywords
- Another keyword, First keyword, Second keyword