1) Testing Domain Reduction
测试域约简
2) test suite reduction
测试用例集约简
1.
Survey of test suite reduction problem;
测试用例集约简问题研究及其进展
2.
Three algorithms are proposed in optimizing the regression test suite when the test suite reduction technique and test case prioritization technique are combined together.
将测试用例集约简技术和优先级技术相结合,提出3种回归测试用例集优化策略:①渐增式约简算法BU,首先选择必不可少用例,然后选择额外贡献度最大的用例直至覆盖全部需求;②精简式算法BD,每次选择必不可少用例,如果没有,则不断删除贡献度最小的用例,直至覆盖全部需求;③优先级策略BUP,每次将需求集重置为待覆盖,然后调用BU直到所有用例排序完毕。
4) Positive domain reduction
正域约简
1.
The relationship of the positive domain reduction with other reductions of inconsistent decision tables;
不协调决策表正域约简与其它约简的关系
5) universe reduct
论域约简
1.
Decision table reduct mainly consists of attribute reduct and attribute value reduct, this paper focuses on the universe reduct.
属性约简和属性值约简是决策表的两种简化方法,本文研究决策表的论域约简。
6) observation reduction
观测约简
1.
This paper improves the methods of observation reduction in non-deterministic planning(NDP) in three aspects:in finding MOS(minimal observation set);in finding out the optimal observation set(OOS) when observations have different costs;and in finding fault-tolerant OOS.
从3个方面改进了不确定规划(non-deterministic planning,简称NDP)中的观测约简:一是如何找最小观测集合(minimal observation set,简称MOS),二是如何在观测代价不均等时找最优观测集合(optimal observation set,简称OOS),三是如何找到容错的OOS。
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