Low Power Verification · All levels

Building a Power Coverage Model: Debug Playbook

Debug Playbook for Building a Power Coverage Model.

Debug playbook

Debug Playbook for Building a Power Coverage Model 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 - Low Power Assertions & Coverage / Building a Power Coverage Model

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 credible power coverage model measures intent realization across states, transitions, and boundary behaviors instead of relying on generic functional bins. Core bins should include each legal state entry/exit, allowed transition arcs, forbidden arc attempts, and transition latency classes under varied traffic and reset conditions. Boundary-focused coverage must capture isolation enable/disable timing relative to power-good and clock/reset qualifiers, retention save/restore success and failure scenarios, and protocol behavior while one side is off or recovering. Useful crosses combine state transitions with isolation strategy, retention class, control source, and interface activity type (idle, burst, backpressure) so hidden corner interactions become visible. Coverage model maturity is shown when every bin maps back to a concrete low-power risk statement and can be traced to a checker or scenario family, making gaps actionable rather than statistical noise.
   - 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 Building a Power Coverage Model: transition timeline, assertions, and before-after replay summary
   - Required owners: LPV lead, power-intent owner, Low Power Assertions & Coverage owner
   - Final decision: ship, bounded rollout, rollback, or escalate

Low-power verification deep dive

Assertions and coverage translate LPV intent into measurable closure confidence and prioritized risk reduction.

Concept diagram

diagram

COVERAGE CLOSURE LOOP

intent risk -> assertions and checkers -> coverage evidence -> closure gaps -> targeted scenarios

Metric graph

diagram

COVERAGE MATURITY

raw hits                 ███████
actionable closure hits  █████
uncovered high-risk bins ███

Metrics and artifacts to collect

assertion failure taxonomy
mode-transition coverage heatmap
crossing risk coverage report
coverage closure readiness packet

Mini case study

Coverage closure accelerated once failures were grouped by transition risk class instead of tool report order.

Debug branches

Prioritize coverage by product-risk scenarios.
Separate actionable assertion classes from setup noise.
Use closure criteria with explicit waiver governance.

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.

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