CDC Review Gate: Debug Playbook

Debug playbook

Debug Playbook for CDC Review Gate focuses on gate pass rate, late-stage CDC churn, review defect leakage. The goal is to convert issue observations into mechanism-backed closure decisions.

CDC/RDC debug is about finding the earliest violated assumption. Start with intent and context before touching low-level signal traces.

Root-cause tree

ROOT-CAUSE TREE — CDC Review Gate

crossing failure observed
        |
   reproducible?
     /        \
   no          yes
   |            |
stress mode   classify issue
expansion       /      |      \
            synchronizer protocol reset/reconvergence
                 |         |           |
            MTBF fit    liveness    release ordering

1. Freeze RTL/config/tool tags for reproducibility.

2. Reproduce in smallest mode/reset/traffic scenario.

3. Classify mechanism: synchronizer, protocol, reset, reconvergence, or governance.

4. Collect one decisive artifact that proves the class.

5. Pick minimal fix or bounded waiver.

6. Run targeted and full-regression matrices before closure.

Review memo template

STAFF CDC/RDC REVIEW MEMO — CDC Signoff Methodology / CDC Review Gate

1. Symptom
   - Failing metric: gate pass rate, late-stage CDC churn, review defect leakage
   - Context: <mode, traffic, reset state, corner>
   - Risk class: <critical/high/medium/low>
   - Database tags: <rtl, config, assertions, tool setup>

2. Mechanism hypothesis
   - Primary mechanism: Gate reviews align RTL, verification, and signoff evidence before integration milestones to avoid endgame metastability surprises.
   - Competing hypothesis: <false warning / protocol bug / reset order / reconvergence>
   - Missing evidence: <assertion, waveform, formal proof, stress replay>

3. Proposed action
   - Minimal reversible change: <sync/protocol/reset/waiver decision>
   - Expected metric movement: <critical count delta>
   - Regression risk: throughput, boot, latency, mode interaction

4. Signoff
   - Re-run artifact: review checklist, gate scorecard, escalation log
   - Required owners: program lead, CDC owner, integration lead
   - Final decision: fix, bounded waiver, or escalate

CDC/RDC deep dive

Signoff is an evidence governance problem across teams.

Concept diagram

CDC SIGNOFF LOOP

analysis -> triage -> fix/waive -> review gate -> dashboard

Metric graph

CRITICAL OPEN COUNT

week1 34
week2 22
week3 10
week4 0

Reports and artifacts

• critical by owner

• waiver quality

• review gate status

• closure trend

Mini case study

Pass rates improved while critical waivers aged out of policy; dashboard exposed hidden risk.

Debug branches

• Separate quality from quantity metrics

• enforce waiver expiry

• run gate checklists consistently

Senior review question

Ask: what evidence proves this risk is closed for silicon, not just tool-clean?

Key takeaways

• State crossing class, assumptions, and owner with every issue.

• Run structural and dynamic regressions after each fix.

Common pitfalls

• Treating all warnings as equivalent risk.

• Waiving issues without containment evidence.

• Skipping reset and reconvergence stress after CDC fixes.

Principal CDC/RDC review addendum

Gate reviews align RTL, verification, and signoff evidence before integration milestones to avoid endgame metastability surprises.

Metric: gate pass rate, late-stage CDC churn, review defect leakage