Scenario: Waiver Debate: Mechanism

Mechanism to understand

Mechanism for Scenario: Waiver Debate focuses on risk framing quality, waiver justification quality, escalation judgment. The goal is to convert issue observations into mechanism-backed closure decisions.

Waiver debates evaluate silicon-risk thinking, evidentiary discipline, and ability to defend or reject assumptions under schedule pressure. Treat each warning as a behavior contract violation candidate, then prove whether it is real risk or tool noise.

• Classify crossing type and data criticality.

• State source/destination clock or reset relationship.

• Identify when protocol semantics dominate topology choice.

System flow

CDC/RDC SIGNOFF FLOW — Scenario: Waiver Debate

crossing inventory + reset map
          |
          v
crossing classification (level/pulse/bus/reset)
          |
          v
structure + protocol + reset checks
          |
          v
critical issues + waiver review
          |
          v
fix / validate / regress / signoff

Waiver debate frame

open issue + schedule pressure
   -> quantify risk
   -> inspect evidence quality
   -> decide waive/fix/escalate

Layer responsibilities

CDC/RDC OWNERSHIP LAYERS — Scenario: Waiver Debate

layer                 owns                            common failure
------------------    -----------------------------   -----------------------------
design intent         crossing architecture           wrong topology selected
protocol semantics    req/ack, fifo, ordering        liveness/deadlock bugs
reset behavior        assert/deassert sequencing      boot instability
analysis setup        tool rules + waivers            false confidence
signoff governance    risk acceptance + dashboard     stale critical waivers

Scenario debrief

Score each response on mechanism clarity, evidence quality, and signoff decision discipline.

INTERVIEW FLOW

classify -> explain mechanism -> propose fix -> state regression

PRACTICE SCORE

session1 62%
session2 78%
session3 89%

Debrief prompts

1. Which crossing class or reset dependency failed first?

2. What evidence changed your decision?

3. Fix, waive, or escalate and why?

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.