Abstract

Emerging from the agile practitioner communities, the microservice-oriented architecture emphasizes implementing and employing multiple small-scale and independently deployable microservices, rather than encapsulating all function capabilities into one monolithic application. Correspondingly, microservice-oriented decomposition, which has been identified to be an extremely challenging and complex task, plays a crucial and prerequisite role in developing microservice-based software systems. To address this challenge and reduce the complexity, we proposed a top-down analysis approach and developed a dataflow-driven decomposition algorithm. In brief, a three-step process is defined: first, engineers together with users conduct business requirement analysis and construct a purified while detailed dataflow diagram of the business logic; then, our algorithm combines the same operations with the same type of output data into a virtual abstract dataflow; finally, the algorithm extracts individual modules of "operation and its output data" from the virtual abstract dataflow to represent the identified microservice candidates. We have employed two use cases to demonstrate our microservice identification mechanism, as well as making comparisons with an existing microservice identification tool. The comparison and evaluation show that, our dataflow-driven identification mechanism is able to deliver more rational, objective, understandable and consistent microservice candidates, through a more rigorous and practical implementation procedure.