DFT / ATPG · All levels
Pattern Volume Tradeoffs: Design Space
Design Space for Pattern Volume Tradeoffs.
Design space exploration
For Pattern Volume Tradeoffs, release options trade quality, tester cost, and schedule risk.
Option A - conservative
Conservative quality: helps debug confidence
Risk: higher test cost
Validate with: first production ramps
Option B - balanced
Balanced release: helps quality and cost
Risk: needs discipline
Validate with: mainstream products
Option C - aggressive
Aggressive schedule: helps faster closure
Risk: escape risk
Validate with: late tapeout pressure
Option D - architecture change
Architecture change: helps long-term quality
Risk: schedule hit
Validate with: chronic recurring failures
DESIGN SPACE - Pattern Volume Tradeoffs
quality <-> tester cost <-> scheduleDesign pitfalls
No ownership for quality gap
Fixing one metric while regressing another
Tradeoff curve
BEFORE / AFTER - Pattern Volume Tradeoffs
metric quality
^
| --- release target
| o regressed
| o baseline
| o after fix
+-------------------------------> closure iteration
Prove quality, timing, and test-power all moved safely.DFT deep dive
Compression saves tester time only when diagnosis observability remains credible.
Concept diagram
COMPRESSION LOOP
EDT/decompressor -> compressed patterns -> compactor responses -> diagnosisMetric graph
PATTERN vs COVERAGE
coverage up -> pattern count up
compression up -> pattern count down (until aliasing risk)Reports and artifacts
compression ratio dashboard
pattern count trend
X-source report
diagnosis bucket summary
Mini case study
Compactor overflow plus unknown inflation caused false diagnosis; masking policy and channel map corrected.
Debug branches
Separate X issues from silicon defects
Replay failing patterns uncompressed
Track tester memory 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
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