Release review: pattern count, tester memory usage, test application time regresses after a test-flow update touching Pattern Volume Tradeoffs.
Team had prior signoff, then a new program/config introduced regressions in selected buckets.
pattern count, tester memory usage, test application time regression
Mismatch between simulation and tester
Escalation without clear owner
Hour 0: freeze pattern set, constraints, and tester program tags
Hour 1: isolate first failing bucket by mode/lot
Hour 2: verify legality and constraints assumptions
Hour 3: correlate with physical/timing/power context
Hour 4: choose minimal reversible fix
Hour 5: run full signoff regression matrix
Hour 6: publish decision memo and owners
Root cause tied to Pattern Volume Tradeoffs: Pattern volume is a tradeoff between coverage closure aggressiveness, X-handling policy, and compression settings constrained by tester resources.
Apply bounded fix with owner
Re-run ATPG pattern summary, tester memory estimate, runtime trend
Re-validate quality, timing, and test power
Tag every run artifact
Mechanism first, command second
Close with explicit release decision
CASE STUDY - Pattern Volume Tradeoffs
baseline metric / regressed metric / post-fix metricDFT FLOW - Pattern Volume Tradeoffs
scan insertion -> chain stitch -> compression map -> ATPG -> tester apply -> diagnosis
| | | | |
controllability shift balance channel use coverage silicon correlation
Primary metric: pattern count, tester memory usage, test application timeCompression 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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