Micro-service architecture identification method based on multiple types of features and multiple measurement indexes

Abstract

The invention discloses a micro-service architecture identification method based on multiple types of features and multiple measurement indexes, and the method comprises the steps: constructing a decision model for micro-service architecture identification according to the features of a micro-service architecture relative to other software architectures, and obtaining the feature measurement indexinformation of the micro-service architecture in a target software project through a static analysis technology; and finally, calculating the probability that the input project uses the micro-servicearchitecture by using the decision model. Compared with an existing architecture recognition method, the method has the advantages that the characteristics of the micro-service architecture are expanded, the calculation function conforming to the characteristics of each measurement index is designed for each measurement index, the recognition accuracy is higher, and the recognition result contains richer content.

Description

technical field [0001] The invention belongs to the field of architecture pattern recognition in software engineering reverse engineering, and in particular relates to a microservice architecture recognition method based on multi-type features and multiple measurement indexes. Background technique [0002] A software system with a certain scale is likely to have a complicated evolution process, and during the evolution process of the system, there may be problems that the system architecture information cannot be updated in time or the documents are missing, which makes the real architecture information of the software system deviate, and then Bring a huge burden to the later maintenance. Therefore, in the field of software engineering reverse engineering, it is an important task to identify the architecture of the software system so as to obtain the real architecture information of the system as much as possible. [0003] In the research of architecture recognition technol...

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Problems solved by technology

However, like software clustering, these architecture recognition technologies are more aimed at general scenarios and do not consider the characteristics of specific architectures. The results obtained by these methods are likely to lose a lot of information related to the actual architecture, making the recognition results There is a large difference from the real results. Therefore, it is necessary to design targeted architecture identification methods for different software architectures.

[0004] At present, the most commonly used software architectures include layered architecture, event-driven architecture, micro-service architecture, etc. In recent years, academia has proposed many identification methods for layered architecture, and the recognition effect has also made great progress; for event-driven architecture In contrast, the research data on recognition is much less. In 2019, some relevant scholars proposed an ontology-based event-driven program architecture pattern recognition method, which provided new ideas for related research to a certain extent; For the extensive microservice architecture, there are no relevant targeted research results yet

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