软件安全测试的四叉树模型研究  

Research on quadtree model for software security testing

作　　者：张承谦 李超 ZHANG Chengqian;LI Chao(Zhengzhou Vocational College of Intelligent Technology,Zhengzhou 450000,China)

机构地区：[1]郑州智能科技职业学院,郑州450000

出　　处：《计算机应用文摘》2024年第12期105-107,共3页Chinese Journal of Computer Application

摘　　要：文章利用四叉树结构寻找初始的聚类中心,并以此为基础对软件模块的故障进行预测,从而提出一种基于四叉树和K-均值聚类算法的软件故障预测方法。该方法旨在提高软件测试的效率和准确性,并通过调整门限参数来允许用户根据需求获取合适的聚类中心。此外,为了评估算法的有效性,引入了一个新的性能指标,即聚类收益。经对比分析发现,该方法在聚类收益方面表现优异,能够在多数情况下实现较低的总体错误率。The article uses a quadtree structure to search for initial cluster centers and based on this,predicts software module faults,thus proposing a software fault prediction method based on quadtree and K-means clustering algorithm.This method aims to improve the efficiency and accuracy of software testing,and allows users to obtain appropriate clustering centers based on their needs by adjusting threshold parameters.In addition,to evaluate the effectiveness of the algorithm,a new performance metric,namely clustering profit,has been introduced.Through comparative analysis,it was found that this method performs excellently in clustering benefits and can achieve a lower overall error rate in most cases.

关 键 词：软件安全测试 四叉树模型 K-均值聚类算法 聚类收益 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]