Channel count, masking, and compaction trade tester cost and diagnosis precision.
+------------------+----------------+----------------+----------------+
| Approach | Strength | Weakness | Best when |
+------------------+----------------+----------------+----------------+
| Low volume | cheap test | coverage risk | cost pressure |
| Balanced | good quality | needs tuning | production |
| High quality | coverage | test time | safety-critical |
| Adaptive | flexible | complex flow | mature teams |
+------------------+----------------+----------------+----------------+Tie approach to product risk and tester constraints
Optimizing one metric only
No regression ownership
DFT EVIDENCE MATRIX - Pattern Volume Tradeoffs
+-------------------+------------------------+--------------------------+-------------------------+
| Evidence | Tells you | Does not prove | Next action |
+-------------------+------------------------+--------------------------+-------------------------+
| coverage report | fault detect trends | silicon root cause | inspect bucket details |
| pattern diff | generation changes | architecture quality | replay suspect patterns |
| timing/power report| test closure margin | diagnosis confidence | correlate fail logs |
| diagnosis summary | likely defect classes | ownership decision | assign action owner |
| signoff checklist | process completeness | correctness of evidence | peer review artifacts |
+-------------------+------------------------+--------------------------+-------------------------+Compression saves tester time only when diagnosis observability remains credible.
COMPRESSION LOOP
EDT/decompressor -> compressed patterns -> compactor responses -> diagnosisPATTERN vs COVERAGE
coverage up -> pattern count up
compression up -> pattern count down (until aliasing risk)compression ratio dashboard
pattern count trend
X-source report
diagnosis bucket summary
Compactor overflow plus unknown inflation caused false diagnosis; masking policy and channel map corrected.
Separate X issues from silicon defects
Replay failing patterns uncompressed
Track tester memory budget
Ask: what evidence proves this DFT decision is safe for production?
State metric, lot/corner context, and pattern tag with every claim.
Treat timing, power, and quality as one signoff problem.
Chasing coverage without legality checks.
Ignoring test-power side effects of pattern changes.
Debugging silicon without reproducible tags.
Pattern volume is a tradeoff between coverage closure aggressiveness, X-handling policy, and compression settings constrained by tester resources.
Metric: pattern count, tester memory usage, test application time
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