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基于粗糙集理论的测试用例的优化
引用本文:贾利娟.基于粗糙集理论的测试用例的优化[J].电子测试,2019(13):59-60.
作者姓名:贾利娟
作者单位:南京工业职业技术学院计算机与软件学院,江苏南京,210023
摘    要:计算机软件技术不断发展,软件产品的功能日益庞大,软件测试也面临工作量的巨大挑战。本文利用粗糙集对知识处理的特征,将信息熵的算法引入到对测试用例数据的筛选中,并对具体的实际问题给出了解决方法,意在减少测试用例数据量,在保证软件测试质量的同时提升测试效率。

关 键 词:粗糙集  信息熵  测试用例

Optimization of Test Case Based on Orthogonal Set Theory
Jia Lijuan.Optimization of Test Case Based on Orthogonal Set Theory[J].Electronic Test,2019(13):59-60.
Authors:Jia Lijuan
Affiliation:(Nanjing Institute of Industry Technology,Nanjing Jiangsu,210023)
Abstract:With the continuous development of computer software technology,the functions of software products are becoming more and more huge.,Software testing is also facing the enormous challenge of workload.In this paper,the Informationentropy is introduced into the selection of test case based on the characteristics of Rough Set for knowledge processing,and the specific practical problems are solved to reduce the workload.The Test Case data quantity is less,and the testing efficiency is improved while ensuring the quality of software testing.
Keywords:Rough Set  Informationentropy  Test Case
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