首页> 外文期刊>Data & Knowledge Engineering >Stepwise structural verification of cyclic workflow models with acyclic decomposition and reduction of loops
【24h】

Stepwise structural verification of cyclic workflow models with acyclic decomposition and reduction of loops

机译:具有非循环分解和循环减少的循环工作流模型的逐步结构验证

获取原文
获取原文并翻译 | 示例
           

摘要

Existence of cycles (or loops) is one of the main sources that make the analysis of workflow models difficult. Several approaches of structural verification exist in the literature, but how to verify cyclic workflow models efficiently in a comprehensible form remains an open research question. Thus, a novel structural verification approach for cyclic workflow models by means of acyclic decomposition and reduction of loops is introduced in this paper with the following contributions. First, acyclic decomposition of natural loops, further enhanced by reduction of nested loops, enables existing verification techniques, normally dealing with acyclic models, to handle workflow models with natural loops. Second, instantiation of an irreducible loop into natural loops, altogether with reduction of concurrent loop entries, enables the proposed approach to handle workflow models with irreducible loops. Last, diagnostic information, provided by the proposed approach, helps stakeholders correct and improve their workflow models. Two examples are provided to show that the proposed approach is systematic and practical. In addition, a prototype of the proposed approach is developed. Its execution result shows that, while providing diagnostic information, the proposed approach can handle workflow models with arbitrary cycles effectively.
机译:循环(或循环)的存在是使工作流模型分析变得困难的主要来源之一。文献中存在几种结构验证方法,但是如何以可理解的形式有效地验证循环工作流模型仍然是一个开放的研究问题。因此,本文介绍了一种通过非循环分解和循环减少对循环工作流模型进行结构验证的新方法,并做出了以下贡献。首先,通过减少嵌套循环进一步增强了自然循环的非循环分解,使现有的验证技术(通常处理非循环模型)能够处理具有自然循环的工作流模型。其次,将不可约循环实例化为自然循环,同时减少并发循环条目,使所提出的方法能够处理不可约循环。最后,建议的方法提供的诊断信息可帮助涉众纠正和改善其工作流程模型。提供了两个示例,表明所提出的方法是系统的和实用的。另外,开发了所提出的方法的原型。它的执行结果表明,该方法在提供诊断信息的同时,可以有效地处理任意周期的工作流模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号