CDC / RDC · All levels

CDC Signoff Dashboard: Debug Playbook

Debug Playbook for CDC Signoff Dashboard.

Debug playbook

Debug Playbook for CDC Signoff Dashboard focuses on critical violations trend, closure burn-down, owner SLA adherence. 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

diagram

ROOT-CAUSE TREE — CDC Signoff Dashboard

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

Freeze RTL/config/tool tags for reproducibility.
Reproduce in smallest mode/reset/traffic scenario.
Classify mechanism: synchronizer, protocol, reset, reconvergence, or governance.
Collect one decisive artifact that proves the class.
Pick minimal fix or bounded waiver.
Run targeted and full-regression matrices before closure.

Review memo template

diagram

STAFF CDC/RDC REVIEW MEMO — CDC Signoff Methodology / CDC Signoff Dashboard

1. Symptom
   - Failing metric: critical violations trend, closure burn-down, owner SLA adherence
   - Context: <mode, traffic, reset state, corner>
   - Risk class: <critical/high/medium/low>
   - Database tags: <rtl, config, assertions, tool setup>

2. Mechanism hypothesis
   - Primary mechanism: Dashboarding translates thousands of crossings into actionable closure metrics by severity, block, owner, and risk state.
   - 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: weekly CDC dashboard, severity breakdown, closure forecast
   - Required owners: CDC lead, program management, design managers
   - Final decision: fix, bounded waiver, or escalate

CDC/RDC deep dive

Signoff is an evidence governance problem across teams.

Concept diagram

diagram

CDC SIGNOFF LOOP

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

Metric graph

diagram

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

Dashboarding translates thousands of crossings into actionable closure metrics by severity, block, owner, and risk state.

Metric: critical violations trend, closure burn-down, owner SLA adherence

Practice this lesson