基于马尔可夫决策模型的测试向量排序新方法  

Research on Novel Test Vector Ordering Approach Based on Markov Decision Processes

作　　者：王冠军[1] 王茂励[2] 赵莹 

机构地区：[1]中国矿业大学计算机学院信息科学系,徐州221116 [2]山东省计算中心,济南250014 [3]哈尔滨工程大学计算机科学与技术学院,哈尔滨150001

出　　处：《计算机科学》2010年第5期287-290,共4页Computer Science

基　　金：国家自然科学基金(60273081和69973014)资助

摘　　要：时延测试向量排序是降低测试功耗的有效技术。提出了基于马尔可夫决策模型的时延测试向量排序新方法。对时延测试向量进行重排序,利用基于转换频度的诱导开关方程和海明距离来定义测试向量序列的转移概率,根据转移概率决定测试向量的顺序,降低测试电路的开关翻转频率,以达到降低峰值功耗和平均功耗的目的。给出了完整的算法TVO-MDP并进行算法最优性和复杂性分析。实验结果证实了本方法的有效性。Delay test vector ordering is an efficient technique to reduce test power. Proposed a new delay test vector order approach based on Markovian decision process. To reorder delay test vector, defined transfer probability with the induced activity functions based on transition probability and hamming distance, determined the test vector sequence according to transfer probability. Reduced the swtiching activity of the CUT（Cirscuits Under Test）,so we could get a better result to reduce peak power and average power. Proposed the TVO-MDP algorithm and conducted optimization and complexity analysis. The experiment results show our method＇s effectiveness.

关 键 词：测试功耗 时延测试向量排序 马尔可夫决策过程 转移概率 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]