DFT Interview Q&A Bank: Debug Playbook

Debug playbook

Debug Playbook for DFT Interview Q&A Bank focuses on breadth of scenario coverage, answer depth consistency, trap avoidance rate. The goal is to convert metric movement into mechanism, owner, and release decision.

Debug aims to find the first incorrect assumption, not the loudest downstream symptom. Start with reproducibility and ownership.

Root-cause tree

ROOT-CAUSE TREE - DFT Interview Q&A Bank

breadth of scenario coverage, answer depth consistency, trap avoidance rate regresses
        |
  setup changed?
    /        \
  yes         no
  |            |
constraint    silicon or
or ATPG       physical/test path
 /    \          |
SDC   model    chain/clock/power/diagnosis
diff  diff     isolate first failing signature

1. Freeze run tags for patterns, constraints, and tester setup.

2. Isolate first failing metric bucket and scenario.

3. Classify failure source: model, constraints, physical, or silicon.

4. Prove mechanism with one reduced replay or targeted run.

5. Apply smallest owner-controlled fix.

6. Re-run timing, power, and quality regression matrix.

Review memo template

STAFF DFT REVIEW MEMO - DFT Interview Prep / DFT Interview Q&A Bank

1. Symptom
   - Watched metric: breadth of scenario coverage, answer depth consistency, trap avoidance rate
   - Failing scenario: <mode/lot/corner/program>
   - Pattern class: <scan/transition/compressed/BIST/JTAG>
   - Tags: <constraints, patterns, tester program, netlist>

2. Mechanism hypothesis
   - Primary mechanism: A curated Q&A bank builds reusable answers around scan, ATPG, BIST, JTAG, and test-signoff judgment under ambiguity.
   - Competing hypothesis: <constraint issue, model issue, physical issue, silicon issue>
   - Missing evidence: <report, replay, diagnosis trace>

3. Proposed action
   - Minimal reversible change: <constraint fix, architecture tweak, pattern update>
   - Expected metric movement: <delta>
   - Regression risk: timing, power, quality, schedule

4. Signoff
   - Re-run artifact: Q&A bank, trap catalog, review scorecard
   - Required owners: candidate, mentor, DFT panel
   - Final decision: release, waive, rollback, or escalate

DFT deep dive

Senior DFT interviews test tradeoff judgment under imperfect data.

Concept diagram

INTERVIEW ANSWER LOOP

state metric -> explain mechanism -> request evidence -> propose fix -> list regression

Metric graph

ANSWER QUALITY

mechanism clarity + ownership clarity + regression discipline

Reports and artifacts

• whiteboard rubric

• scenario scorecard

• trap checklist

• follow-up depth index

Mini case study

Candidate improved from tool-only answers to mechanism-first narratives by using metric->artifact->decision template.

Debug branches

• Always state assumptions

• Name cross-team owners

• Discuss risk and fallback plan

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

A curated Q&A bank builds reusable answers around scan, ATPG, BIST, JTAG, and test-signoff judgment under ambiguity.

Metric: breadth of scenario coverage, answer depth consistency, trap avoidance rate