Low Power Verification · All levels

Corruption and Retention Simulation: Debug Playbook

Debug Playbook for Corruption and Retention Simulation.

Debug playbook

Debug Playbook for Corruption and Retention Simulation is anchored on illegal transition rate, corruption incidence, and deterministic replay quality under low-power scenarios. Convert observations into mechanism-backed and owner-bound actions.

Freeze seed, metadata, and boundary under investigation.
Locate first persistent low-power phase divergence.
Classify mechanism: setup, transition, boundary, retention, or X-prop class.
Apply one focused reproducer and one bounded fix.
Re-run determinism and broader regression matrix.

Review memo template

diagram

LPV REVIEW MEMO - Power-Aware Simulation / Corruption and Retention Simulation

1. Symptom
   - Failing metric: illegal transition rate, corruption incidence, and deterministic replay quality under low-power scenarios
   - Trigger context: <seed/mode/sequence>
   - First failing phase: <entry/off/exit/boundary>

2. Mechanism hypothesis
   - Candidate mechanism: Validate signal corruption semantics on power-down by proving non-retained state collapses to unknown or tool-defined corrupt values at the expected boundary and time, instead of silently preserving stale logic values. In parallel, verify retention strategy behavior: save and restore handshakes, retention supply availability, and retained element correctness across repeated cycling and corner ordering. Effective tests combine directed stress and assertion-based checks to catch false confidence cases where simulations pass because stimulus avoids the vulnerable transition window rather than because corruption and restore behavior are implemented correctly.
   - Competing hypotheses: setup, transition race, boundary bug, retention drift, X-prop noise
   - Missing evidence: <trace/assertion/report>

3. Proposed action
   - Smallest reversible change: <intent/RTL/checker/flow>
   - Expected movement: <failure trend/replay stability>
   - Regression risk: compatibility, coverage, signoff delay

4. Signoff
   - Required artifact: evidence packet for Corruption and Retention Simulation: transition timeline, assertions, and before-after replay summary
   - Required owners: LPV lead, power-intent owner, Power-Aware Simulation owner
   - Final decision: ship, bounded rollout, rollback, or escalate

Low-power verification deep dive

Power-aware simulation quality is measured by realistic transition behavior and actionable failure classification.

Concept diagram

diagram

POWER-AWARE SIM FLOW

UPF + RTL + testbench -> elaboration -> transition simulation -> assertions and triage

Metric graph

diagram

SIM QUALITY SIGNALS

false-fail noise      █████
actionable failures   ███████
deterministic replay  ████████

Metrics and artifacts to collect

elaboration semantic report
power-aware run reproducibility matrix
corruption and clamp behavior summary
assertion signal-to-noise trend

Mini case study

A noisy regression became actionable after bucketing failures by transition phase and boundary type before fixing checks.

Debug branches

Start from first failing phase, not final mismatch.
Check semantic setup consistency before declaring design bug.
Use one reproducible scenario per hypothesis branch.

Senior review question

Ask: what exact low-power transition boundary failed first, and which artifact proves the closure claim reproducibly?

Key takeaways

Tie each LPV claim to a concrete transition boundary and one proving artifact.
Prefer minimal reversible fixes with explicit owner and rollback criteria.

Common pitfalls

Treating power-aware failures as random before boundary classification.
Waiving X-prop failures before proving impact and root cause.
Declaring closure without deterministic replay across key modes.

Debug ladder

Sequence: reproduce -> classify -> isolate boundary -> prove mechanism -> bounded fix.

Avoid mixed fixes before first-principles classification.

Practice this lesson