...
首页> 外文期刊>Journal of environmental protection and ecology >REGRESSION TESTING FOR TEST CASE PRIORITISATION USING K-MEANS CLUSTERING AND MIN-MAX NEURAL NETWORK
【24h】

REGRESSION TESTING FOR TEST CASE PRIORITISATION USING K-MEANS CLUSTERING AND MIN-MAX NEURAL NETWORK

机译:REGRESSION TESTING FOR TEST CASE PRIORITISATION USING K-MEANS CLUSTERING AND MIN-MAX NEURAL NETWORK

获取原文
获取原文并翻译 | 示例

摘要

An evaluation of modifications was created for the performances of regression testing through softer maintenance. This important process is more costly since the total test set is very big and the reevaluation test takes more calculation resources and time. In the process of regression testing, the arrangements of test cases are very crucial. It programs the test sets to enhance certain objectives that aid to minimise the time and costs for the applications of service orientation. In the proposed study we have improved fault detection in finding test cases from the rejected set of detection capabilities. The goal of this article is to optimise a list of test cases to make regression testing efficient. As a result, the test's efficiency was improved by reducing the time and cost required to conduct it, which increased the tester's and software's productivity, allowing for the discovery of the greatest number of flaws.

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号