Jing Ye 1,2, Xiaolin Zhang 1,2, Yu Hu 1, and Xiaowei Li 1 1 Key Laboratory of Computer System and...

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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

Transcript of Jing Ye 1,2, Xiaolin Zhang 1,2, Yu Hu 1, and Xiaowei Li 1 1 Key Laboratory of Computer System and...

Page 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.

Jing Ye1,2, Xiaolin Zhang1,2, Yu Hu1, and Xiaowei Li1

1Key Laboratory of Computer System and Architecture

Institute of Computing Technology

Chinese Academy of Sciences

2Graduate University of Chinese Academy of Sciences

Substantial Fault Pairs at-A-Time (SFPAT):An Automatic Diagnostic Pattern

Generation Method

Page 2: 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.

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Motivation

Fault Diagnosis Quality

Efficiency ofDiagnosis Method

Distinguishability of Used Patterns

Distinguish as ManyFault pairs as possible

Few More PatternsThan Test Patterns

Page 3: 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.

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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

Page 4: 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.

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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

abcd

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fg

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q

Fanout Free Region (FFR)

Key Observation

q p

q p

q p

p

Page 5: 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.

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Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

AVERAGE

Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

FP3 type

FP2 type

FP1 type

Distinguishability of 1-Detect Compressed Test PatternsKey Observation

Percentage of FPi-type fault pairs among all the fault pairs

Percentage of indistinguishable FPi-type fault pairs among all

the indistinguishable fault pairs

FP3 type

FP2 type

FP1 type

Page 6: 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.

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Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

AVERAGEabcd

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Distinguishability of 1-Detect Compressed Test PatternsKey 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

Page 7: 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.

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Percentage of FP3 type fault pairs among all the fault pairs Percentage of indistinguishable FP3 type fault pairs among all the indistinguishable fault pairs

Percentage of FP2 type fault pairs among all the fault pairs Percentage of indistinguishable FP2 type fault pairs among all the indistinguishable fault pairs

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Percentage of FP1 type fault pairs among all the fault pairs Percentage of indistinguishable FP1 type fault pairs among all the indistinguishable fault pairs

AVERAGEabcd

e

fg

h

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Distinguishability of 1-Detect Compressed Test PatternsKey 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

+

Page 8: 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.

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N-detect test pattern• A fault may be detected for multiple times in different ways.

Distinguishability of N-Detect Test PatternsKey Observation

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s208 s1196 s1423 s1488 s1494 s5378

Num. of indistinguished fault pairs

1-detectcompressed

1-detect 2-detect 3-detect 4-detect

FP1 type fault pairs

pat

Flt.1 Flt.2

Page 9: 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.

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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]

Page 10: 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.

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Diagnostic Pattern Generation Method OverviewProposed Diagnostic Pattern Generation Method

+ =

>

Transferred circuit netlist and fault list=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist Target fault list

END

pat.A pat.B pat.C

Flt.1 flt.2 flt.3 flt.4 flt.5

Consider Substantial Fault Pairs at-A-Time

Page 11: 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.

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Diagnostic Pattern Generation Method OverviewProposed Diagnostic Pattern Generation Method

+ =

>

Transferred circuit netlist and fault list=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist Target fault list

END

pat.A pat.B pat.C

Flt.1 flt.2 flt.3 flt.4 flt.5

Consider Substantial Fault Pairs at-A-Time

Page 12: 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.

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Diagnostic Pattern Generation Method OverviewProposed Diagnostic Pattern Generation Method

+ =

>

Transferred circuit netlist and fault list=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist Target fault list

END

pat.A pat.B pat.C

Flt.1 flt.2 flt.3 flt.4 flt.5

Consider Substantial Fault Pairs at-A-Time

Page 13: 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.

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Diagnostic Pattern Generation Method OverviewProposed Diagnostic Pattern Generation Method

+ =

>

Transferred circuit netlist and fault list=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist Target fault list

END

Consider Substantial Fault Pairs at-A-Time

Reduce noiseLower power

Compress patterns

Cont.

Page 14: 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.

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

Miter circuit• Miter circuit is a circuit consisting of two modified duplication

D1 and D2 of the original circuit.

• Different connection of D1 and D2 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).

abcd

egh

i

j

m

nf

Page 15: 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.

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abcd

egh

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

abcd

egh

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abcd

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D1

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Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 16: 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.

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

abcd

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D1

gh

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ABCD

f

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nf

Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 17: 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.

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abcd

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gh

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abcd

ABCD M

N

f

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

SA1

SA1

SA1

SA1

abcd

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D1

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abcd

ABCD M

N

SA1

SA1

SA1

SA1

f

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Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 18: 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.

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abcd

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N

SA1

SA1

SA1

SA1

sel1 sel2

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

0 1 S-fault• sel1/1 – (a/1,c/1)

• sel2/1 – (b/1,d/1)

Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 19: 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.

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abcd

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SA1

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sel1 sel2

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

0 1

FAULT-FREE

FAULT-FREE

0

0

S-fault• sel1/1 – (a/1,c/1)

• sel2/1 – (b/1,d/1)

Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 20: 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.

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abcd

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gh

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ABCD M

N

SA1

SA1

SA1

SA1

sel1 sel2

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Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

0 1

INJECT a/1

INJECT c/11

S-fault• sel1/1 – (a/1,c/1)

• sel2/1 – (b/1,d/1)

Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

Page 21: 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.

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abcd

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gh

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abcd

ABCD M

N

SA1

SA1

SA1

SA1

sel1 sel2

f

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gh

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nf

Proposed Diagnostic Pattern Generation Method

Circuit Transformation and Fault List Creation

Fault in original circuit• Constrain the value of sel to 0

S-fault• sel1/1 – (a/1,c/1)

• sel2/1 – (b/1,d/1)

Target fault pair• (a/1,c/1)• (b/1,d/1)

SA1-module• ‘out’ = ‘sel’ | ‘in’

MU

XS0

S11

in

sel

out

SA1

INJECT h/1

FAULT-FREE

0

0

Page 22: 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.

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Some of faults arecertain distinguished if they are detected.(1) All the faults in original circuits.(2) S-faults of FP1 type fault pairs which may not be distinguished when they are detected.

Proposed Diagnostic Pattern Generation Method

Diagnostic Pattern Generation Flow

+ =

>=

>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist

END

FP1 type fault pairsOriginal circuit netlist

+ =

>

Transferred circuit netlist and fault list=>

=>

Indistinguished fault pairs

Transferred circuit netlist and S-fault list

ATPG tool

+ =

>

Transferred circuit netlist and fault list=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist Target fault list

END

FP1 > FP2 > FP3

Page 23: 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.

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+ =

>=

>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist

END

FP1 type fault pairsOriginal circuit netlist

+ =

>

Transferred circuit netlist and fault list=>

=>

Indistinguished fault pairs

Transferred circuit netlist and S-fault list

ATPG tool

Some of faults arecertain distinguished if they are detected.(1) All the faults in original circuits.(2) S-faults of FP1 type fault pairs which may not be distinguished when they are detected.

Proposed Diagnostic Pattern Generation Method

Diagnostic Pattern Generation Flow

+ =>=>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist

END

FP1 type fault pairsOriginal circuit netlist

+ =>

Transferred circuit netlist and fault list=>=>

Indistinguished fault pairs

Transferred circuit netlist and S-fault list

ATPG tool

Is a fault pair distinguished if both faults are detected?(a/1,b/1) (a/1,e/0) (a/1,c/1) (a/1,d/1) (a/1,f/0) (a/1,g/1) (a/1 g/0)

Yes Yes No No Yes Yes Yes(b/1,e/0) (b/1,c/1) (b/1,d/1) (b/1,f/0) (b/1,g/1) (b/1,g/0) (e/0,c/1)

Yes No No Yes Yes Yes Yes(e/0,d/1) (e/0,f/0) (e/0,g/1) (e/0,g/0) (c/1,d/1) (c/1,f/0) (c/1,g/1)

Yes Yes Yes Yes Yes Yes Yes(c/1,g/0) (d/1,f/0) (d/1,g/1) (d/1,g/0) (f/0, g/1) (f/0,g/0) (g/1,g/0)

Yes Yes Yes Yes Yes Yes Yes

abcd

egh

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nf

Page 24: 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.

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Some of faults arecertain distinguished if they are detected.(1) All the faults in original circuits.(2) S-faults of FP1 type fault pairs which may not be distinguished when they are detected.

Proposed Diagnostic Pattern Generation Method

Diagnostic Pattern Generation Flow

+ =

>=

>

ATPG tool=>

More indistinguished fault pairs?Yes!

No!

Original circuit netlist

END

FP1 type fault pairsOriginal circuit netlist

+ =

>

Transferred circuit netlist and fault list=>

=>

Indistinguished fault pairs

Transferred circuit netlist and S-fault list

ATPG tool

(1) No patterns can distinguish a target fault pair.(2) ATPG tool cannot achieve 100% S-fault coverage.

BREAK

SAT tool

Page 25: 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.

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Experimental SettingExperimental Result

Benchmark circuit• ISCAS’89• ITC’99

Test Pattern• TetraMax Ver.A-2007.12• 1-detect compressed test patterns

Page 26: 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.

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Experimental DataExperimental Result

Circuit s5378 s9234 s13207 s15850 s35932 s38417 s38584

Stuck-at faults 4563 6473 9664 11336 35110 31015 34797

Test patterns 123 156 264 128 24 111 144

Indistinguished fault pairs 593 1621 2276 2971 14438 3850 3242

FP1 typeS-faults 18006 24370 42099 26584 18924 34057 67871

Diagnostic patterns 124 164 273 146 28 118 155

Remaining indistinguished

S-faults 578 1552 2062 2909 13123 3673 2808

Diagnostic patterns 20 71 5 26 3 19 13

Total diagnostic patterns 144 235 278 172 31 137 168

Fault pairs which cannot be distinguished by any patterns 523 1229 2043 2801 12893 3372 2696

The number of S-faults is mainly determined by the circuit structure

The number of S-faults becomes much smaller

Page 27: 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.

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Comparison with Previous WorkExperimental Result

s5378 s9234 s13207 s15850 s359320

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

[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

Page 28: 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.

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Comparison with Previous WorkExperimental 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]

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Number of diagnostic patterns in [12] Number of diagnostic patterns in this work

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

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Number of diagnostic patterns in [12] Number of diagnostic patterns in this work

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

s5378 s9234 s13207 s15850 s359320

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Number of diagnostic patterns in [12] Number of diagnostic patterns in this work

Number Percentage

Number of test patterns in [12] Number of test patterns in this work

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Percentage of distinguished fault pairs under diagnostic patterns among indistinguishable fault pairs under test patterns [12] this work

Number of diagnostic patterns in [12]

Number of test patterns in [12]

About 90% of distinguished fault pairs under diagnostic patterns

among indistinguished fault pairsunder test patterns in [12]

Number of diagnosticpatterns in this work

Number of testpatterns in this work

100% in this work

Page 29: 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.

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ConclusionDistinguishability 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.

Page 30: 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.

Thank You for Your Attention !

Any Questions?