ATPG Constraints: Silicon PPA Impact

Silicon impact

Pattern quality decisions impact production escapes and test time.

Area drivers

• compression logic footprint

• hold buffers from scan paths

Power drivers

• shift toggling peaks

• capture burst stress

Timing impact

• test-clock skew

• shift/capture path sensitivity

PD consequences

• chain route detours

• placement hotspots near test logic

Verification burden

• pattern replay correlation

• diagnosis reproducibility

SILICON IMPACT - ATPG Constraints
area/power/timing/yield tradeoff

Takeaways

• Signoff needs silicon evidence

• Ownership clarity accelerates closure

Design option snapshot

CHAIN BALANCE - ATPG Constraints

chain length
  ^
  |      o        o
  |   o    o  o
  | o
  +-----------------------------> chain index

Tight spread reduces shift time and hold-fix burden.

DFT deep dive

ATPG quality comes from fault model choice plus legal constraints, not raw pattern volume alone.

Concept diagram

ATPG FLOW

fault model -> constraints -> generation -> simulation -> coverage closure -> signoff

Metric graph

COVERAGE GAP

target coverage
  ^
  |      o before closure
  |          o after fixes
  +---------------------> iteration

Reports and artifacts

• fault model coverage

• untestable class report

• constraint legality errors

• pattern signoff memo

Mini case study

Transition coverage stalled due to clock constraints mismatch; updated at-speed capture definitions recovered target.

Debug branches

• Classify untestable faults

• Diff ATPG constraints each run

• Pair coverage with pattern budget

Senior review question

Ask: what evidence proves this DFT decision is safe for production?

Key takeaways

• State metric, lot/corner context, and pattern tag with every claim.

• Treat timing, power, and quality as one signoff problem.

Common pitfalls

• Chasing coverage without legality checks.

• Ignoring test-power side effects of pattern changes.

• Debugging silicon without reproducible tags.

Principal DFT review addendum

ATPG constraints encode legal test-mode behavior, clocks, resets, and masks so generated patterns are both executable and meaningful.

Metric: constraint consistency errors, illegal state count, pattern abort rate