计算机集成制造系统 ›› 2018, Vol. 24 ›› Issue (第7): 1858-1870.DOI: 10.13196/j.cims.2018.07.028

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过程间引发约束变化的最小高级修改序列识别

张学伟1,刘明菊2,邢建春1+,周启臻1   

  1. 1.陆军工程大学国防工程学院
    2.中国洛阳电子装备试验中心
  • 出版日期:2018-07-31 发布日期:2018-07-31
  • 基金资助:
    国家重点研发计划资助项目(2017YFC0704100);国家自然科学基金资助项目(61572171)。

Minimum sequence identification of high-level change operations changing constraints between data-aware processes

  • Online:2018-07-31 Published:2018-07-31
  • Supported by:
    Project supported by the National Key Research and Development Progran,China(No.2017YFC0704100),and the National Natural Science Foundation,China(No.61572171).

摘要: 鉴于引发约束变化的最小高级修改序列在实现数据感知过程转换、合并、版本控制等方面具有重要作用,提出一种识别数据感知过程间引发约束变化的最小高级修改序列的方法。该方法定义了数据感知过程的活动约束图,然后基于活动约束图构建两个数据感知过程的约束矩阵,最后利用约束矩阵和数字逻辑识别一个数据感知过程间转换所需引发约束变化的最小修改序列。大量实验评估了所提方法和现有方法的准确性与时效性。结果表明,所提方法比现有方法具有更高的准确性,其平均准确率达到89.89%。

关键词: 数据感知过程, 引发约束变化的最小修改序列, 程序约束图, 约束矩阵

Abstract: Owing to the importance of minimum sequence of high-level change operations changing constraints between data-aware processes in the aspects of data-aware process retrieval,merge and version control,an identification method was proposed.In this method,the activity constraint graph of data-aware process was defined.Then the constraint matrixes of a pair of data-aware processes were constructed based on activity dependence graphs.The constraint matrixes and the concept of digital logical were used to identify a minimum sequence of high-level change operations changing constraints between data-aware processes.Extensive experiments on real and synthetic datasets were conducted to evaluate the accuracy and eficiency of proposed approach and previous approaches.Experimental results demonstrated that the proposed approach could achieve a higher average accuracy (89.89%) than that of previous approaches.

Key words: data-aware process, minimum sequence of high-level change operations changing constraints, activity constraint graph, constraint matrix

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