Title :
Enhanced DO-RE-ME based defect level prediction using defect site aggregation-MPG-D
Author :
Dworak, Jennifer ; Grimaila, Michael R. ; Lee, Sooryong ; Wang, Li C. ; Mercer, M. Ray
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
Predicting the final value of the defective part level after the application of a set of test vectors is not a simple problem. In order for the defective part level to decrease, both the excitation and observation of defects must occur. This research shows that the probability of exciting an as yet undetected defect does indeed decrease exponentially as the number of observations increases. In addition, a new defective part level model is proposed which accurately predicts the final defective part level (even at high fault coverages) for several benchmark circuits and which continues to provide good predictions even as changes are made an the set of test patterns applied
Keywords :
automatic test pattern generation; fault diagnosis; integrated circuit testing; logic testing; ATPG; MPG-D model; benchmark circuits; defect site aggregation; defective part level; defective part level model; enhanced DO-RE-ME based defect level prediction; final defective part level; high fault coverages; test vector set; Application software; Automatic test pattern generation; Benchmark testing; Circuit faults; Circuit testing; Integrated circuit modeling; Integrated circuit testing; Logic testing; Predictive models; Test pattern generators;
Conference_Titel :
Test Conference, 2000. Proceedings. International
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-7803-6546-1
DOI :
10.1109/TEST.2000.894304