Low Power Verification · All levels
LPV Flow and Tooling in Practice: Debug Playbook
Debug Playbook for LPV Flow and Tooling in Practice.
Debug playbook
Debug Playbook for LPV Flow and Tooling in Practice 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
LPV REVIEW MEMO - Low Power Verification Foundations / LPV Flow and Tooling in Practice
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: A robust LPV flow starts with intent authoring and structural linting, then moves to power-aware elaboration, static low-power checks, dynamic simulation, assertion-driven debug, and closure with transition-focused coverage. Static tools catch missing/incorrect low-power structures early, while power-aware simulation validates temporal behavior under realistic control sequences and stress traffic. Mature teams also include formal apps for protocol/sequence proofs, automated waiver governance, and regression gating that combines bug trend, coverage quality, and unresolved risk. The goal is repeatable signoff evidence that low-power implementation is both structurally correct and behaviorally safe across all supported operating modes.
- 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 LPV Flow and Tooling in Practice: transition timeline, assertions, and before-after replay summary
- Required owners: LPV lead, power-intent owner, Low Power Verification Foundations owner
- Final decision: ship, bounded rollout, rollback, or escalateLow-power verification deep dive
LPV foundations are strongest when power intent, simulation semantics, and ownership boundaries are explicit from day one.
Concept diagram
LPV FOUNDATION LOOP
intent definition -> setup and modeling -> scenario execution -> evidence-based closure
^ |
+------------------------ owner feedback ----------------------+Metric graph
FOUNDATION HEALTH
setup escapes █████
intent mismatch defects ██████
stable regressions █████████Metrics and artifacts to collect
intent-to-RTL alignment checklist
power-mode onboarding packet
ownership map for controls and checks
first-failure boundary report
Mini case study
A project reduced LPV bring-up churn after requiring explicit domain-control ownership and transition evidence in every review.
Debug branches
Prove setup correctness before chasing downstream symptoms.
Record domain ownership for each control and checker.
Distinguish intent mismatch from RTL implementation bugs.
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.