Research Article
CPN Model Based Standard Feature Verification Method for REST Service Architecture
@INPROCEEDINGS{10.1007/978-3-030-12981-1_48, author={Jing Liu and Zhen-Tian Liu and Yu-Qiang Zhao}, title={CPN Model Based Standard Feature Verification Method for REST Service Architecture}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 14th EAI International Conference, CollaborateCom 2018, Shanghai, China, December 1-3, 2018, Proceedings}, proceedings_a={COLLABORATECOM}, year={2019}, month={2}, keywords={REST service architecture colored Petri nets model Verification of standard features}, doi={10.1007/978-3-030-12981-1_48} }- Jing Liu
Zhen-Tian Liu
Yu-Qiang Zhao
Year: 2019
CPN Model Based Standard Feature Verification Method for REST Service Architecture
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-12981-1_48
Abstract
The representational state transfer (REST) service architecture is widely used in large-scale and scalable distributed web systems. If the REST service architecture does not comply with its standard feature constrains, it can result in degraded performance or low scalability of the REST-based web systems. Therefore, in order to enhance the quality of system designing, it is necessary to verify whether the system design meets the standard feature constrains of the REST service architecture. In this paper, we propose a standard feature constrains verification method for REST service architecture based on Colored Petri Nets (CPN) model. Firstly, five standard feature constrains of the REST service architecture are modeled using the CPN. Then a verification method is proposed based on synchronized matching of the execution paths in model state space. Lastly, we validate the usability and validity of the proposed verification method using a practical course management web system based on the REST service architecture. Experimental results show that our method can effectively confirm whether the web application system design based on REST service architecture conforms to the standard feature constrains of the REST service architecture. Besides, it can also provide intuitive and feasible execution data when the standard feature constraints are not met, which can facilitate the defects location and correction of the following design of application systems.