Verifiable Model Construction for Business Processes

Author:

Ji Shunhui1,Hu Liming1,Cao Yihan1,Zhang Pengcheng1,Gao Jerry2

Affiliation:

1. College of Computer and Information, Hohai University, Nanjing, Jiangsu 211100, P. R. China

2. College of Engineering, San Jose State University, San Jose, CA 95192, USA

Abstract

Business process specified in Business Process Execution Language (BPEL), which integrates existing services to develop composite service for offering more complicated function, is error-prone. Verification and testing are necessary to ensure the correctness of business processes. SPIN, for which the input language is PROcess MEta-LAnguage (Promela), is one of the most popular tools for detecting software defects and can be used both in verification and testing. In this paper, an automatic approach is proposed to construct the verifiable model for BPEL-based business process with Promela language. Business process is translated to an intermediate two-level representation, in which eXtended Control Flow Graph (XCFG) describes the behavior of BPEL process in the first level and Web Service Description Models (WSDM) depict the interface information of composite service and partner services in the second level. With XCFG of BPEL process, XCFGs for partner services are generated to describe their behavior. Promela model is constructed by defining data types based on WSDM and defining channels, variables and processes based on XCFGs. The constructed Promela model is closed, containing not only the BPEL process but also its execution environment. Case study shows that the proposed approach is effective.

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Conformance Between Choreography and Collaboration in BPMN Involving Multi-Instance Participants;International Journal of Pattern Recognition and Artificial Intelligence;2022-04-28

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