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An Approach of Trustworthiness Evaluation of Software Behavior Based on Multidimensional Fuzzy Attributes

机译:基于多维模糊属性的软件行为可信度评估方法

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—In order to increase the accuracy of trustworthiness evaluation of software, the paper improves the traditional construction process of the expected behavior trace of software and proposes an approach of trustworthiness evaluation of software behavior based on multidimensional fuzzy attributes. First, training samples of the same monitoring point are clustered based on multidimensional fuzzy attributes to construct a more accurate expected behavior trace of software. Second, an improved weight distribution method of multidimensional fuzzy attributes is presented based on correlation coefficient and standard deviation integrated approach (CCSD) for weight distribution of attributes in multiple attribute decision making. The improved weight distribution method is suitable for one-class samples from monitoring point and it considers both the dispersion of fuzzy attribute’s value and the influence among these fuzzy attributes. Finally, experiments and analyses show that: ① the expected behavior trace of software constructed by training after clustering is more accurate than without clustering; and ② our improved weight distribution method of multidimensional fuzzy attributes has better effect of trustworthiness evaluation than CCSD and other methods of weight distribution for one-class samples.
机译:-IN为了提高软件可靠性评估的准确性,提高了软件预期行为轨迹的传统施工过程,提出了一种基于多维模糊属性的软件行为可信度评估方法。首先,基于多维模糊属性群集相同监视点的训练样本,以构建软件的更准确的预期行为轨迹。其次,基于相关系数和标准偏差综合方法(CCSD)来提出了一种改进的多维模糊属性的重量分布方法,用于多个属性决策中的属性的重量分布。改进的权重分配方法适用于来自监测点的单级样本,并且它考虑了模糊属性的分散和这些模糊属性之间的影响。最后,实验和分析表明:①聚类后通过培训构建的软件的预期行为痕迹比没有聚类; ②我们改进的多维模糊属性的重量分布方法具有比CCSD和其他一类样品的重量分布的可靠性评估的效果评估更好。

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