摘要
传统的面向故障的测试方法存在限制条件高精确程度与低误报率无法兼得的瓶颈效果,而高误报率直接导致了测试成本的增加和效率的低下。本文在面向故障的测试框架下,深入研究了探索性软件测试方法,对该测试过程进行了量化处理,提取出一系列指标和效应函数,作为所采用的用于优化的遗传算法中的迭代条件,进而寻找出在有限测试成本内的最佳检查点组合,最终实现了既定精确程度的条件下测试成本的优化。
There is a bottleneck effect between high accuracy of restricted condition and low false alarm rate in traditional testing way of fault oriented.The high false alarm rate directly leads to high cost and low efficiency.In this paper,under the frame of fault oriented,exploratory testing has been researched and quantized,some indexes and functions has been given,as the iterative condition for Genetic Algorithm,which is used for optimizing.Then,optimal combination of alarm points in limited cost is revealed,task of optimizing in established accuracy of restricted condition is completed.
出处
《微计算机信息》
2010年第25期145-146,232,共3页
Control & Automation
关键词
探索性测试
面向故障
遗传算法
检查点
Exploratory Testing
Fault Oriented
Genetic Algorithm
Alarm Point
