Inputs and outputs contract

Inputs & Outputs for DFT Whiteboard Framework focuses on interview answer structure quality, mechanism clarity, tradeoff articulation. The goal is to convert metric movement into mechanism, owner, and release decision.

Treat these as a release contract. Ambiguity here creates expensive debug loops because teams optimize against different assumptions.

INPUTS
  - scan/ATPG architecture and constraints
  - fault model and quality target policy
  - pattern generation config + tester limits
  - timing/power/physical assumptions

OUTPUTS
  - quality metrics and closure status
  - signed artifacts and owner approvals
  - diagnosis evidence for residual risk
  - release, waiver, or escalation decision

Flow sequence

DFT FLOW - DFT Whiteboard Framework

scan insertion -> chain stitch -> compression map -> ATPG -> tester apply -> diagnosis
      |                |                |            |             |
 controllability   shift balance    channel use   coverage     silicon correlation

Primary metric: interview answer structure quality, mechanism clarity, tradeoff articulation

Ownership map

OWNERSHIP MAP - DFT Whiteboard Framework

artifact              owner
----------------      -----------------
architecture/report candidate
constraints/setup   DFT interviewer
physical/test       hiring panel

Name an owner for each failing metric cluster.

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

Strong DFT interviews follow a repeatable chain: architecture intent, controllability/observability, constraints, quality metrics, and debug loop.

Metric: interview answer structure quality, mechanism clarity, tradeoff articulation