计算机工程与应用2016，Vol.52Issue(6)：42-49,8.DOI:10.3778/j.issn.1002-8331.1405-0341
基于多属性决策和交叉熵优化多维测试覆盖
Optimizing multi-dimensional test coverage based on multiple attribute decision making ;and cross entropy
摘要
Abstract
With the scale and complexity of software increasing, people’s awareness of software quality assurance has gradually strengthened. How to carry out the test, test scheme optimization selection and how to improve the testing effi-ciency become the reality problems in software engineering. Using the test coverage of the multidimensional metric, it proposes the effectiveness of comprehensive test coverage, satisfaction of test coverage rate and test efficiency as the opti-mization test scheme selection, uses multiple attribute decision making lifting scheme selection algorithm to measure the optimal test program, ameliorates the severity of the past subjective experience dependent, so as to provide guidance for reasonable, effective and scientific test. The optimization of comprehensive test coverage scheme is applied to the Markov model of software testing. It obtains better coverage test section, optimizes the test process. Experimental results show that the algorithm can reduce the number of test cases required to detect and remove a certain number of software defects in comparison with the random testing strategy.关键词
多属性决策/交叉熵/多维测试覆盖/综合测试覆盖率/覆盖率满意度/覆盖测试效率Key words
multiple attribute decision making/cross entropy/multi-dimensional test coverage/integration test coverage rate/satisfaction of coverage rate/coverage test efficiency分类
信息技术与安全科学引用本文复制引用
张屹,黄海..基于多属性决策和交叉熵优化多维测试覆盖[J].计算机工程与应用,2016,52(6):42-49,8.基金项目
广东省高等学校科技创新重点项目（No.cxzd1144）；广州市属高校“羊城学者”科研项目（No.10A033D）。 （）
