Q7 — Verification & Validation Status

Where REF Stands in V&V

An honest assessment of what has been formally verified, what "verified" means at each level, where known gaps remain, and what Phase 2 will address.

Phase 1 Bundle
5/5 Artifacts LOCKED
Verification Method
Bounded Model Checking + Analytic Proofs
Known Gaps
7 documented, prioritized
Phase 2 Trigger
Post-Series A ($100–175K)
Posture
REF distinguishes what is verified from what is claimed. Every evidence artifact is locked with SHA256 checksums. Every limitation is documented. We present completed work for assessment — not aspirational claims.
01 — Phase 1 Verification Bundle

5/5 Evidence Artifacts Locked

Each artifact has a unique evidence ID, a locked version with SHA256 checksum, and a quantifiable metric. These are the building blocks a formal methods engagement would assess and extend.

ID
Artifact
Type
Status
Key Metric
EV-008
REFConsensus.tla (v1.9)
TLA+ specification
Locked
152,658,351 states · 4 invariants · 0 violations
EV-009
TokenLifecycle.tla
TLA+ specification
Locked
269 states · 7 invariants · 0 violations
EV-010
THREAT_MODEL.md (v1.0.1)
Threat model
Locked
6 adversary classes · 14 attack scenarios
EV-011
ref_token_v1_1.circom (v2.1)
ZK circuit audit
Locked
1,155 constraints · 8 findings · 8 negative vectors
EV-012
DOMINANCE_PROOF.md + MC
Mechanism design
Locked
500 simulations · 100% honesty · 652× min margin
02 — The Refinement Chain

From Domain Concepts to Evidence

RDE requires an unbroken chain from domain model through to evidence. Each link in REF's chain is documented, versioned, and traceable.

D
Domain Model
THREAT_MODEL §1
R
Requirements
6 Properties (P-*)
T
Threat Model
EV-010
A
Architecture
§6 Contracts
S
TLA+ Specs
EV-008 · EV-009
C
Circuit
EV-011
E
Evidence
EV-012 · MC-500
Traceability Example

Domain concept (Purchase) → Requirement (P-AUTH: every review bound to purchase) → Threat (ATK-1: bulk fake reviews) → Mitigation (ZK proof + economic deterrence) → Artifact (TokenLifecycle.tla, DOMINANCE_PROOF.md) → Evidence (EV-009: 269 states, 0 violations; MC-500: 100% dominance).

03 — What "Verified" Means

Calibrated Claims, Not Marketing

REF uses three distinct verification methods. Each has specific strengths and limitations that we document explicitly.

▣
Model-Checked (Bounded)
TLA+ specs checked by TLC over finite state spaces. Proves no violations exist within the checked bounds. Does not prove correctness for arbitrary state spaces. This is the standard limitation of model checking vs. theorem proving.
◎
Circuit-Tested (Negative Vectors)
ZK circuit has 8 test vectors that properly reject invalid witnesses with CONSTRAINT_REJECTED. Demonstrates under-constraint defenses work. This is not a formal soundness proof — it is directed testing against specific attack patterns.
⊢
Analytically Proven + Empirically Validated
The dominance condition α·C₀·Nγ > k has a complete analytic proof (strict concavity at v=0) AND empirical validation across 500 Monte Carlo parameter combinations. Both methods agree: 100% honesty dominance.
04 — Known Gaps

Where REF Falls Short

Transparency requires enumerating deficiencies. These are documented, prioritized, and positioned within the refinement chain. Each represents a specific location where the handoff from intent to implementation can be strengthened.

Gap
Severity
Chain Location
DEF-01: Missing att_hash output from purchase_verification.circom
P0
Spec → Implementation
DEF-02: Token circuit implementation needs hardening
P0
Spec → Implementation
No Coq/Isabelle proofs for circuit correctness
High
Code → Formal Proof
View-change safety not model-checked (MaxView=0)
Medium
Architecture → Spec
P-IR (Individual Rationality) market-justified, not formally proven
Medium
Property → Proof
Hash-to-field canonical reduction not implemented
Medium
Spec → Implementation
BLS aggregation is scaffold only (Ed25519 for Phase 1)
Low
Architecture → Implementation
The Gap That Matters Most

The refinement from TLA+ specification to production code is human-maintained, not machine-checked. We have TLA+ on one side and Python/Circom on the other, with documented traceability between them. A tool like Cryptol/SAW or an assume-guarantee framework would close this gap — and is the single highest-value area for formal methods expertise. This refinement defect is catalogued as DEF-02 in the verification bundle.

05 — Phase 2 Roadmap (Post-Series A)

What External Engagement Would Deliver

Phase 2 targets the four highest-value verification activities that require external expertise and tooling beyond what a solo founder can deliver.

External Attestation
Trail of Bits or Veridise Engagement
Scoped protocol verification covering consensus + ZK + token lifecycle. Signed report from an independent trust domain. Budget: $100–175K. Phase 1 artifacts reduce their scope — they start from locked evidence, not a blank slate.
Theorem-Level Proofs
Coq / Isabelle / EasyCrypt
Circuit correctness proofs that hold for arbitrary inputs — not just tested vectors. Moves ZK verification from "directed testing" to "mathematical guarantee." Requires specialized formal methods expertise.
Spec↔Code Equivalence
Cryptol / SAW Integration
Machine-checked refinement from TLA+ specifications to Python/Circom implementation. Closes DEF-02 — the highest-priority refinement gap. Eliminates the human-maintained traceability layer.
Production Adversarial Testing
Load Testing Under Byzantine Conditions
Multi-region PBFT deployment with injected faults, network partitions, and adversarial validators. Validates that formal properties translate to operational SLOs under real-world conditions.
06 — Validation (Does It Solve the Right Problem?)

Verification ≠ Validation

Verification asks "did we build it right?" Validation asks "did we build the right thing?" Both matter. Here is REF's validation status.

$787.7B
Annual Consumer Harm
From fake online reviews globally. The problem REF addresses is validated by economic research.
$53,088
FTC Penalty per Violation
FTC Rule 465 creates regulatory urgency. REF provides compliance-enabling infrastructure.
57%
Detection Accuracy (Status Quo)
Current AI-based detection is barely better than a coin flip. REF replaces detection with prevention.
Validation Honesty

REF is pilot-stage — not yet deployed with production merchants. Market validation is supported by economic research and regulatory trends, but real-world merchant adoption is unproven. The technical architecture is ahead of commercial traction. This is typical for deep-tech infrastructure at this stage.