Compression & Diagnosis

Section goal

Compression architecture, EDT channels, pattern volume control, diagnosis loops, and yield learning workflows.

How to study this section

1. Start with the topic hub for architecture and ownership context.

2. Use mechanism and reports pages to map assumptions to metrics.

3. Use debug and worked examples for real closure patterns.

4. Finish with checklist and silicon impact before release decisions.

Topics

1. compression-architectures/ - Compression Architectures

2. pattern-volume-tradeoffs/ - Pattern Volume Tradeoffs

3. diagnosis-and-yield/ - Diagnosis & Yield Learning

4. compression-debug/ - Compression Debug

Related topics

• DFT course hub

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?