DFT Whiteboard Framework: Reports & Metrics

Reports and metrics

Reports & Metrics 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.

A report should support a release decision for interview answer structure quality, mechanism clarity, tradeoff articulation. One headline number is rarely enough without setup tags and bucket-level evidence.

Metric movement

METRIC GRAPH - interview answer structure quality, mechanism clarity, tradeoff articulation

quality metric
  ^
  |                         target
  |                       - - - - - - -
  |                  o after fix + regression
  |              o
  |         o baseline
  |    o regressed run
  +--------------------------------------> closure iteration
    input audit     focused fix      signoff review

Readout:
  - explain what moved, why it moved, and who approved it

Distribution view

PATTERN HISTOGRAM - DFT Whiteboard Framework

pattern count
  |      ***
  |    *******
  |  ***********
  |*************  <- high-volume tail (optimize here)
  +--------------------> pattern buckets
   smoke  stuck-at  transition  diagnosis

Balance quality and tester limits together.

• Track interview answer structure quality, mechanism clarity, tradeoff articulation by context and pattern class.

• Review trend and bucket detail together.

• Keep quality, timing, and power metrics in one dashboard.

• Store each metric next to the artifact and run tag.

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.

Reading reports