基于结构分解的因果行为轮廓获取方法

计算机科学 ›› 2014, Vol. 41 ›› Issue (1): 242-245.

基于结构分解的因果行为轮廓获取方法

蔡敏,汪世义

同济大学计算机科学与技术系上海201804;巢湖学院计算机与信息工程学院合肥238000

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受安徽省高等学校省级自然科学基金项目(KJ2013B157,KJ2012Z266)资助

Capturing Causal Behavioral Profile Based on Structural Decomposition Technique

CAI Min and WANG Shi-yi

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 模型因果行为轮廓不仅可用于度量业务模型之间的一致度,还可以监控业务流程的实际执行。针对现有因果行为轮廓获取方法的局限性,提出了基于最小T-不变量分解技术的因果行为轮廓获取方法。该方法首先将工作流系统模型分解成一组完备子系统,再由各完备子系统中的局部关系推导出系统模型中的全局关系,可用于捕获任意sound自由选择工作流系统的因果行为轮廓。

关键词: T-不变量,工作流系统,因果行为轮廓,完备子系统,变迁对

Abstract: The causal behavioral profile can be applied to measure the consistency between two given process models as well as to monitor process execution．To overcome the limitation of existing approach to obtain the causal behavioral profile,a novel approach was presented based on T-invariants decomposition technique．A workflow system is first decomposed into a set of complete subsystems,and then the global relations between transitions are deduced from their local relations in each complete subsystem．The approach can be used for arbitrary sound free choice workflow systems.

Key words: T-invariants,Workflow system,Causal behavioral profiles,Complete subsystems,Transition pairs

蔡敏,汪世义. 基于结构分解的因果行为轮廓获取方法[J]. 计算机科学, 2014, 41(1): 242-245. https://doi.org/

CAI Min and WANG Shi-yi. Capturing Causal Behavioral Profile Based on Structural Decomposition Technique[J]. Computer Science, 2014, 41(1): 242-245. https://doi.org/

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