Detecting Data Flow Errors Across Processes in Business Process Collaboration

被引:1
|
作者
Xiong, Tianhong [1 ]
Pan, Maolin [1 ]
Yu, Yang [1 ]
Lou, Dingjun [1 ]
机构
[1] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
基金
中国国家自然科学基金;
关键词
Collaboration; Business; Correlation; Receivers; Data models; Standards; Detection algorithms; Business process management; business process collaboration; data flow error across processes; data dependency; VERIFICATION;
D O I
10.1109/ACCESS.2020.3024689
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In business process collaboration (BPC), especially when it comes to message communication and data exchange, there are complex data dependencies among sender process, receiver process and messages. However, each participant of the overall BPC develops its part independently as a service, including its own communication part and data flow. As a result, data flow errors across processes may occur easily. In this article, we propose a method based on BPMN to detect these errors caused by data dependency violations. Our method is inspired by the study of detecting data flow errors within a single process and focuses on a subset of the elements of the BPC model, without having to consider the complete set. In particular, we define a set of data flow error patterns by analyzing and formalizing data dependencies in order to clearly clarify and identify errors. Then we give the corresponding automatic detection algorithm. Finally, through two evaluations, we demonstrate the effectiveness of our proposal.
引用
收藏
页码:170862 / 170871
页数:10
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