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請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/5994
標題: Graph-based and scenario-driven microservice analysis, retrieval, and testing
作者: Ma, Shang-Pin 
Fan, Chen-Yuan
Chuang, Yen
Liu, I-Hsiu
Lan, Ci-Wei
關鍵字: DISCOVERY
公開日期: 十一月-2019
出版社: ELSEVIER
卷: 100
起(迄)頁: 724-735
來源出版物: FUTURE GENER COMP SY
摘要: 
The microservice architecture (MSA) differs fundamentally from the monolithic, layered architecture. The use of microservices provides a high degree of autonomy, composability, scalability, and fault-tolerance. MSA is regarded by many as a promising architecture for smart-city applications; however, a number of issues remain, including (1) the management of complex call relationships among microservices; (2) ensuring the quality of the overall software system even as new microservices are added and existing ones are modified, and (3) locating existing microservices that satisfy new requirements. In this paper, we propose a novel approach to the development of microservice-based systems, referred to as GSMART (Graph-based and Scenario-driven Microservice Analysis, Retrieval and Testing). GSMART enables the automatic generation of a Service Dependency Graph (SDG)'' by which to visualize and analyze dependency relationships between microservices as well as between services and scenarios. It also enables the automatic retrieval of test cases required for system changes to reduce the time and costs associated with regression testing. A microservice retrieval method using VSM and word2vec accelerates the development of new microservices tailored specifically to the needs of users based on user-provided scenarios. Experiment results demonstrate the feasibility, effectiveness, and efficiency of all of the main features of GSMART. (C) 2019 Elsevier B.V. All rights reserved.
URI: http://scholars.ntou.edu.tw/handle/123456789/5994
ISSN: 0167-739X
DOI: 10.1016/j.future.2019.05.048
顯示於:資訊工程學系
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