A Feature Dataset of Microservices-Based Systems

Microservice architecture has become a dominant architectural style in the service-oriented software industry. Poor practices in the design and development of microservices are called microservice bad smells. In microservice bad smells research, the detection of these bad smells relies on feature data from microservices. However, there is a lack of an appropriate open-source microservice feature dataset. The availability of such datasets may contribute to the detection of microservice bad smells unexpectedly. To address this research gap, this paper collects a number of open-source microservice systems utilizing Spring Cloud. Additionally, feature metrics are established based on the architecture and interactions of Spring Boot style microservices. And an extraction program is developed. The program is then applied to the collected open-source microservice systems, extracting the necessary information, and undergoing manual verification to create an open-source feature dataset specific to microservice systems using Spring Cloud. The dataset is made available through a CSV file. We believe that both the extraction program and the dataset have the potential to contribute to the study of microservice bad smells.