1. Jing Ye 1,2, Xiaolin Zhang 1,2, Yu Hu 1, and Xiaowei Li 1 1 Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences 2 Graduate University of Chinese Academy of Sciences Substantial Fault Pairs at-A-Time (SFPAT): An Automatic Diagnostic Pattern Generation Method

2. 2 Motivation Fault Diagnosis Quality Efficiency of Diagnosis Method Distinguishability of Used Patterns Distinguish as Many Fault pairs as possible Few More Patterns Than Test Patterns

3. 3 Outline Key Observation Distinguishability of 1-detect compressed Test Patterns Distinguishability of N-detect Test Patterns Related Work Proposed Diagnostic Pattern Generation Method Diagnostic Pattern Generation Method Overview Circuit Transformation and Fault List Creation Diagnostic Pattern Generation Flow Experimental Result Experimental Setting

4. 4 Distinguishability of 1-Detect Compressed Test Patterns Experiment Setting ISCAS’89 benchmark circuits 1-detect compressed test patterns (TetraMax Ver.A-2007.12) Fault Pairs Classification two faults in the fault pair are in the same FFR. FP1 type two faults in the fault pair are in different FFRs but with the same observation points. FP2 type two faults in the fault pair are in different FFRs but with at least one different observation points. FP3 type Fanout Free Region (FFR) Key Observation q pq p q pq p q pq p p

5. 5 AVERAGE FP3 typeFP2 typeFP1 type Distinguishability of 1-Detect Compressed Test Patterns Key Observation Percentage of FP i -type fault pairs among all the fault pairs Percentage of indistinguishable FP i -type fault pairs among all the indistinguishable fault pairs FP3 type FP2 type FP1 type

6. 6 AVERAGE Distinguishability of 1-Detect Compressed Test Patterns Key Observation FP1 type fault pairs Two faults in the fault pair are in the same FFR FP2 type fault pairs Two faults in the fault pair are in different FFRs but with the same observation points FP3 type fault pairs Two faults in the fault pair are in different FFRs but with at least one different observation point FP1 > FP2 > FP3 ‘>’ : harder to be distinguished

7. 7 AVERAGE Distinguishability of 1-Detect Compressed Test Patterns Key Observation FP1 type fault pairs Two faults in the fault pair are in the same FFR FP2 type fault pairs Two faults in the fault pair are in different FFRs but with the same observation points FP3 type fault pairs Two faults in the fault pair are in different FFRs but with at least one different observation point FP1 > FP2 > FP3 ‘>’ : harder to be distinguished

8. 8 N-detect test pattern A fault may be detected for multiple times in different ways. Distinguishability of N-Detect Test Patterns Key Observation FP1 type fault pairs

9. 9 Related Work Test elimination process of modifying test patterns [I. Pomeranz, S. M. Reddy TCAD2000] [I. Pomeranz, S. M. Reddy ETS2007] Exclusive test pattern generation [V. D. Agrawal, D. H. Baik, et al. ICVD2003] Pattern generation for fault-tuple modeled faults [N. K. Bhatti, R. D. Blanton ITC2006] Integer linear program formulation [M. A. Shukoor, V. D. Agrawal ETS2009] Pattern distinguishability and N-detect patterns [Z. Wang, M. Marek-Sadowska, et al. ICCD2003] Pattern reordering algorithm for truncated fail data [C. Gang, S. M. Reddy, et al. DAC2006]

10. 10 Diagnostic Pattern Generation Method Overview Proposed Diagnostic Pattern Generation Method

11. 11 Diagnostic Pattern Generation Method Overview Proposed Diagnostic Pattern Generation Method

12. 12 Diagnostic Pattern Generation Method Overview Proposed Diagnostic Pattern Generation Method

13. 13 Diagnostic Pattern Generation Method Overview Proposed Diagnostic Pattern Generation Method Cont.

14. 14 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation Miter circuit Miter circuit is a circuit consisting of two modified duplication D 1 and D 2 of the original circuit. Different connection of D 1 and D 2 is proposed in previous works. S-fault The pattern which can detect a S-fault in the transformed circuit can distinguish its related fault pair in the original circuit. Example Stuck-at v fault at l: l/v. We will work on other fault models in the future. Distinguish the fault pair (a/1,c/1) and the fault pair (b/1,d/1).

15. 15 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

16. 16 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

17. 17 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

18. 18 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation S-fault sel 1 /1 – (a/1,c/1) sel 2 /1 – (b/1,d/1) Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

19. 19 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation FAULT-FREE 0 0 S-fault sel 1 /1 – (a/1,c/1) sel 2 /1 – (b/1,d/1) Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

20. 20 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation INJECT a/1 INJECT c/1 1 S-fault sel 1 /1 – (a/1,c/1) sel 2 /1 – (b/1,d/1) Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’

21. 21 Proposed Diagnostic Pattern Generation Method Circuit Transformation and Fault List Creation Fault in original circuit Constrain the value of sel to 0 S-fault sel 1 /1 – (a/1,c/1) sel 2 /1 – (b/1,d/1) Target fault pair (a/1,c/1) (b/1,d/1) SA1-module ‘out’ = ‘sel’ | ‘in’ INJECT h/1 FAULT-FREE 0 0

22. 22 Proposed Diagnostic Pattern Generation Method Diagnostic Pattern Generation Flow FP1 > FP2 > FP3

23. 23 Proposed Diagnostic Pattern Generation Method Diagnostic Pattern Generation Flow

24. 24 Proposed Diagnostic Pattern Generation Method Diagnostic Pattern Generation Flow SAT tool

25. 25 Experimental Setting Experimental Result Benchmark circuit ISCAS’89 ITC’99 Test Pattern TetraMax Ver.A-2007.12 1-detect compressed test patterns

26. 26 Experimental Data Experimental Result Circuit s5378s9234s13207s15850s35932s38417s38584 Stuck-at faults 45636473966411336351103101534797 Test patterns 12315626412824111144 Indistinguished fault pairs 5931621227629711443838503242 FP1 type S-faults 18006243704209926584189243405767871 Diagnostic patterns 12416427314628118155 Remaining indistinguished S-faults 5781552206229091312336732808 Diagnostic patterns 207152631913 Total diagnostic patterns 14423527817231137168 Fault pairs which cannot be distinguished by any patterns 5231229204328011289333722696 The number of S-faults is mainly determined by the circuit structure The number of S-faults becomes much smaller

27. 27 Comparison with Previous Work Experimental Result [12] I. Pomeranz and S. M. Reddy, "Diagnostic Test Generation Based on Subsets of Faults," Proc. of European Test Symposium (ETS), pp. 151-158, 2007. Comparison with [12] ISCAS’89: almost the same for the small circuits ITC’99: different version of benchmark circuits

28. 28 Comparison with Previous Work Experimental Result [12] I. Pomeranz and S. M. Reddy, "Diagnostic Test Generation Based on Subsets of Faults," Proc. of European Test Symposium (ETS), pp. 151-158, 2007. Comparison with [12] Number of diagnostic patterns in [12] Number of test patterns in [12] About 90% of distinguished fault pairs under diagnostic patterns among indistinguished fault pairs under test patterns in [12] Number of diagnostic patterns in this work Number of test patterns in this work 100% in this work

29. 29 Conclusion Distinguishability of patterns are important ! Distinguishability of 1-detect compressed test patterns FP1 > FP2 > FP3 Miter-circuit and S-fault The pattern which can detect a S-fault in the miter-circuit can distinguish its related fault pair in the original circuit. There is no need to modify the ATPG tool, and the functions of ATPG tool can also be applied.

30. Thank You for Your Attention ! Any Questions?