基于变量依赖关系模型的变量重要性度量方法
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TP311

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北京市自然科学基金资助项目(Z160002)和本项目得到网络文化与数字传播北京市重点实验室开放课题资助(5221935409)


Variable Importance Measurement Method Based on Variable Dependency Model
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Supported by Beijing Natural Science Foundation (Z160002);Supported by the Opening Project of Beijing Key Laboratory of Internet Culture and Digital (5221935409)

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    摘要:

    为了减少变量变更的代价,需要评估变量在程序中的重要程度。对变量的重要性度量有利于合理安排软件测试资源,保证软件质量。论文通过分析程序中各变量状态,利用变量间的依赖关系构建变量依赖关系模型,将图论和变量重要性度量相结合。针对现有节点重要性度量方法存在的局限性问题,提出一种新的基于变量依赖关系模型的变量重要性度量方法。实验表明,该方法在变量重要性度量方面的准确性相比其他方法有所提升。

    Abstract:

    In order to reduce the cost of variable change, it is necessary to evaluate the importance of variables in the program. The measure of the importance to the variables is beneficial to arrange the software test resources reasonably and ensure the software quality. In this paper, by analyzing the states of variables in the program, the model of variable dependency is constructed by using the dependency between variables, and the graph theory and the measure of variable importance are combined. Aiming at the limitations of the existing methods, a new method based on the variable dependency model is proposed. The experimental results show that the accuracy of this method is better than that of other methods.

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引用本文

田兴亚,牟永敏,张志华. 基于变量依赖关系模型的变量重要性度量方法[J]. 科学技术与工程, 2020, 20(19): 7772-7779.
Tian Xingya, Mu Yongmei, Zhang Zhihua. Variable Importance Measurement Method Based on Variable Dependency Model[J]. Science Technology and Engineering,2020,20(19):7772-7779.

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  • 收稿日期:2020-01-13
  • 最后修改日期:2020-03-24
  • 录用日期:2020-02-23
  • 在线发布日期: 2020-07-28
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