Combinational LEC: Key-Point Matching and Structural Normalization: Mechanism

Mechanism to understand

Mechanism for Combinational LEC: Key-Point Matching and Structural Normalization is anchored on non-vacuous closure rate, counterexample turnaround, and residual-risk trend by requirement class. Convert outcomes into assumption-aware, evidence-backed actions.

Combinational LEC proves that two designs produce identical outputs for identical inputs in the same cycle, making it ideal for pure combinational logic transformations and synthesis-preserved cone rewrites.

• Name the first boundary where requirement intent diverges.

• Prove mechanism with one high-confidence evidence packet.

• Assign owner for smallest reversible mitigation.

Execution flow

FORMAL EXECUTION FLOW - Combinational LEC: Key-Point Matching and Structural Normalization

requirement intent and risk class
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property and assumption modeling
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proof engine exploration and trace extraction
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counterexample classification and fix hypothesis
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re-proof, coverage audit, and signoff decision

Formal deep dive

Equivalence confidence comes from transformation-aware setup and rapid first-divergence diagnosis.

Concept diagram

EQUIVALENCE WORKFLOW

golden and revised design -> mapping and alignment -> mismatch triage -> closure evidence

Metric graph

LEC/SEC DEBUG SIGNALS

setup mismatches        █████
real behavioral deltas  ███
resolved divergences    ███████

Metrics and artifacts to collect

• compare-point match quality

• SEC latency-alignment success

• RTL-to-gate variant coverage

• ECO mismatch root-cause aging

Mini case study

A late ECO mismatch was traced to clock-gating setup, then closed with repeatable SEC alignment rules.

Debug branches

• Classify mismatch source before editing waiver sets.

• Use SEC when latency movement is intentional.

• Replay first divergence in simulation for cross-validation.

Senior review question

Ask: which requirement intent is proven, under which assumptions, and what residual risk remains?

Key takeaways

• Tie each proof claim to assumption boundaries and reachability evidence.

• Prefer minimal reversible fixes and preserve legal behavior visibility.

Common pitfalls

• Treating runtime reduction as proof-quality improvement without audits.

• Declaring closure while critical covers remain unreachable.

• Using broad waivers instead of first-divergence root-cause ownership.

Mechanism deep dive

Mechanism detail: Combinational LEC proves that two designs produce identical outputs for identical inputs in the same cycle, making it ideal for pure combinational logic transformations and synthesis-preserved cone rewrites. The core productivity lever is key-point strategy: tools match registers, cut-points, and internal compare points to reduce proof depth and isolate mismatches near the source transformation instead of only at top-level outputs. Pre-processing is equally critical because naming churn, hierarchy flattening, and datapath rewriting can block automatic matching even when functionality is unchanged. Mature flows therefore include black-box policy for known macros, constant-propagation awareness, and compare-point waiver rules that distinguish harmless structural drift from true behavioral divergence. When matching fails, the first debug pass should classify whether the issue is mapping incompleteness, undriven/X behavior, or actual logic difference before escalating to deep trace analysis.

Prefer requirement decomposition over monolithic assertions for debug clarity.