改进信息熵算法的最优测试序列生成方法

Approach of optimal diagnosis test sequence based on improved information entropy

测试性设计和分析中的一个重要问题是构建一种测试序列,获得满足需求的故障隔离精度并降低测试代价。目前已提出多种研究算法,如信息熵算法、AO*算法等,但都存在一些问题。针对测试序列问题,对不同方法进行研究,针对已有算法的不足,在信息熵理论的基础上,提出了一种一步前向回溯算法,即改进信息熵算法,并给出具体的计算步骤。该算法既可应用于二值属性系统,又适用于多值属性系统。实例计算结果和算法分析表明,此算法和已有算法相比,该算法简单,计算时间短,测试代价最优,具有很好的实用价值。

One of an important issue of testability design and analysis is to construct a test sequence to obtain the accuracy of fault isolation and reduce testing costs. Now many algorithms have been proposed, such as information entropy and AO＂ algorithms, but they are not the best. Aiming at the test sequence problem,a step forward backward algorithm, namely improved information entropy algorithm,is proposed based on the re-search on many algorithms. And give the specific calculation steps. The algorithm can be applied to two value attribute system and multi-value attribute system. The design process of the algorithm and examples are presented. Compared with the existing algorithms, the algorithm is simple and has short computing time,the optimal testing cost and practical value.