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 <-> schedule

Design 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 -> diagnosis

Metric 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