摘要
提出了一种基于粗糙集的不完备测试数据填补方法。该方法首先利用粗糙集中下近似集的性质对随机生成的测试数据进行填补,然后根据属性数据的取值概率函数求出的结果进行二次填补,从而完成对不完备测试数据的完备化处理,生成最优测试用例。采用本方法可以较好地反映待测系统所蕴含的规则,且可以避免测试数据的冲突。
This paper brought forward a testing data packing method of incomplete information system based on rough sets and grey system theory. First, this method takes advantage of the lower approximation in rough sets to do random producing testing data packing, and then, according to the value-taking probability of the attribute value, finds the result to do the second packing, thus accomplishes the completion of incomplete information system, so producing great value test case. This method can adequately reflect the testing system rules and avoid the conflict in test data.
出处
《自动化与仪器仪表》
2009年第3期87-90,共4页
Automation & Instrumentation
基金
甘肃省自然科学基金项目(ZS031-A25-019-G)
关键词
软件测试
不完备数据
粗糙集
灰色理论
测试用例
Software testing
Incomplete data
Rough sets
Grey system theory
Test case
