Efficient Static Compaction of Test Patterns Using Partial Maximum Satisfiability  

作　　者：Huisi Zhou Dantong Ouyang Liming Zhang 

机构地区：[1]the Laboratory of Symbol Computation and Knowledge Engineering,College of Computer Science and Technology,Jilin University,Changchun 130012,China

出　　处：《Tsinghua Science and Technology》2021年第1期1-8,共8页清华大学学报（自然科学版（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.61672261 and 61872159)。

摘　　要：Static compaction methods aim at finding unnecessary test patterns to reduce the size of the test set as a post-process of test generation.Techniques based on partial maximum satisfiability are often used to track many hard problems in various domains,including artificial intelligence,computational biology,data mining,and machine learning.We observe that part of the test patterns generated by the commercial Automatic Test Pattern Generation(ATPG)tool is redundant,and the relationship between test patterns and faults,as a significant information,can effectively induce the test patterns reduction process.Considering a test pattern can detect one or more faults,we map the problem of static test compaction to a partial maximum satisfiability problem.Experiments on ISCAS89,ISCAS85,and ITC99 benchmarks show that this approach can reduce the initial test set size generated by TetraMAX18 while maintaining fault coverage.

关 键 词：test compaction partial maximum satisfiability Automatic Test Pattern Generation(ATPG) 

分 类 号：TN407[电子电信—微电子学与固体电子学]