Deterministic Artifact Creation: The Foundation of Medical Software Verification
When building software for regulated applications, one fundamental question haunts every engineer: How do you prove that your system produces the exact same output every time? This isn't just about repeatability—it's about creating artifacts that are verifiable, auditable, and trustworthy enough to support critical decisions.
The Olexian Evidence Platform (OEP) is a deterministic verification instrument designed for audit-grade evidence artifacts used in regulated engineering workflows. But before we explore what OEP verifies, let's understand why deterministic artifact creation matters in the first place.
The Determinism Problem
Most software operates in a world of convenient chaos. Timestamps vary. Hash functions change. File systems reorder directory listings. Floating-point operations produce subtly different results across hardware. JSON libraries serialize objects in unpredictable orders.
For a typical web application, this doesn't matter. For software used in regulated contexts, it's unacceptable.
Deterministic artifact creation means that given identical inputs, the system can reproduce byte-identical evidence artifacts under a defined compatibility profile (contract + toolchain + policy). Not "similar" outputs. Not "functionally equivalent" outputs. Identical.
Why Byte-for-Byte Matters
Consider this scenario: A test lab runs an analysis pipeline on a dataset and issues a third-party report. Six months later, during an audit, they need to prove the exact computation that produced those results. If the software produces different evidence artifacts on replay—even if the meaning is the same—trust collapses.
This is where OEP's verification model shines:
OEP verifies that a bundle is intact, contract-conformant, and reproducibly verifiable.
OEP doesn't claim to judge whether your science is correct. It doesn't attest to regulatory compliance. It doesn't certify safety. What it does do is verify structural integrity, contract conformance, and deterministic reproducibility—the foundational layer upon which trust is built.
The Evidence Bundle Approach
At the heart of OEP's approach is a versioned evidence-bundle contract: a precise definition of what files must exist, how they are normalized, and how integrity is proven. The goal is simple: eliminate avoidable sources of nondeterminism so that a replay can be independently verified later, offline.
A typical evidence bundle contains:
Input manifests describing what data entered the system
Output manifests listing every artifact produced
Cryptographic hashes binding each artifact to the bundle
Metadata documenting the computational environment
Every file follows strict canonicalization rules to eliminate common sources of non-determinism:
Consistent character encoding (no surprises from legacy encodings)
Normalized line endings (cross-platform compatibility)
Deterministic serialization (eliminates ordering randomness)
Content-addressed filenames (hash-based naming for integrity)
These aren't arbitrary restrictions—they're surgical removals of non-determinism sources. Each rule eliminates a potential point of divergence.
A Single Hash Standard per Contract Version
To avoid ambiguity, OEP standardizes on a single cryptographic hashing algorithm per contract version. This ensures there's one unambiguous integrity dialect for bundles, evidence packets, and verification reports.
Why force a single hash function? Because having multiple hash algorithms in play introduces ambiguity. Which hash do you trust? Which one was used for this artifact?
By standardizing on a modern, cryptographically strong hash function, OEP eliminates an entire class of verification failures. This is a hard choice—standardization always involves tradeoffs. But it's the right choice when auditability and long-term trust are the goals.
What OEP Verifies (and What It Doesn't)
Here's where OEP's design philosophy gets interesting:
OEP may verify that:
The bundle declares a supported contract version
Required artifacts are present and valid
Declared hashes match observed content
OEP does not attest to:
Regulatory compliance or device classification
Clinical performance, safety class, or effectiveness
Scientific validity or correctness of results
Any interpretation derived from visualization or user interfaces
This narrow scope is intentional. OEP is verification middleware—a deterministic witness that confirms what happened, not whether it was correct.
Think of OEP as a notary: it attests that a document was signed and unaltered, but it doesn't judge the document's legal merit. Similarly, OEP confirms that your evidence bundle is intact and reproducible, but you remain responsible for system-level validation and risk management.
The Architecture of Determinism
Achieving byte-for-byte reproducibility requires discipline at every layer:
1. Canonicalization at Ingestion
Data entering the system must be normalized immediately. Floating-point values are handled with explicit precision controls. Timestamps go into designated metadata fields, never mixed into hash computations.
2. Manifest-Driven Outputs
Every output artifact is listed in a manifest with its cryptographic hash. The manifest itself is deterministically serialized using stable formatting rules. Hash the manifest, and you've created a cryptographic seal over the entire run.
3. Registry-Based Governance
Critical field values are drawn from explicit, versioned registries rather than free-form strings. This eliminates typos and version drift while maintaining a clear audit trail.
4. Separation of Authority and Orchestration
Verification and custody logic are implemented as a small, strict authority core, separate from higher-level orchestration. The authority core is designed to be deterministic, auditable, and stable across time. This separation reduces variability and tightens custody chains.
5. Self-Check Mechanisms
OEP includes a self-check mechanism: known test vectors that must verify successfully before a toolchain is trusted for real evidence verification. If your OEP installation can't reproduce these reference hashes, something is wrong with your environment.
Environment-Characterized Workloads
Some workloads (e.g., certain ML or numerical pipelines) may not be expected to produce byte-identical results. In those cases, OEP can still produce audit artifacts that bind the output to a declared environment and inputs, so reviewers can understand exactly what ran even when the computation itself is not strictly reproducible at the byte level.
Retention and Auditability
Determinism is useless if you can't retrieve the original artifacts years later. OEP is designed to support long-term retention with a minimal evidence set:
Original input bundle (as received)
Verification evidence
Verification report
Referenced registry and schema versions
Retention timeframes are customer-determined based on their regulatory context, but OEP's architecture ensures that verification logic remains time-independent. No timestamps leak into hash computations. No clock drift affects verification outcomes.
The Hazard Boundary
Medical software regulation often hinges on "intended use." OEP explicitly positions itself as a verification instrument, not a clinical tool:
OEP emits verification artifacts. OEP does not generate clinical guidance, dosing, diagnoses, alarms, or treatment recommendations.
This design choice has important implications. By staying in the verification lane, OEP outputs serve as engineering evidence and audit artifacts. Customers who integrate OEP into larger clinical systems remain responsible for their own system-level risk management and regulatory compliance.
OEP does not make claims about regulatory classification, device class, or compliance status. Those determinations depend on the complete system context and intended use, which only the customer can define.
Practical Implications
What does deterministic artifact creation mean for developers?
Separate timestamps from canonical data. Keep them in metadata only.
Use deterministic serialization. Ensure your output format is stable and repeatable.
Pin your dependencies. Container images, library versions, toolchain versions—everything matters.
Control floating-point behavior. Use explicit precision models or fixed-point representations in authority paths.
Test reproducibility, not just correctness. Hash your outputs and compare across runs.
These constraints feel restrictive—because they are. But restriction is the price of auditability.
The Broader Vision
OEP is designed as part of a layered architecture where different components have clearly separated responsibilities:
A strict authority core handles custody and verification
Specialized computation engines handle domain-specific calculations
Orchestration layers coordinate workflows without touching canonical data
Each layer's outputs are deterministically verifiable by the next, creating a chain of custody from raw inputs to final evidence.
Conclusion: Determinism as a Foundation
OEP doesn't solve every problem in medical software verification. It doesn't attest to clinical validity. It doesn't grant regulatory approval. It doesn't make your code correct.
What it does provide is a solid, deterministic foundation—a way to prove that your system produces the exact same evidence artifacts every time, in a verifiable, auditable, and trustworthy manner.
In medical software, where critical decisions may depend on computational results, that foundation isn't optional. It's essential.
Value proposition:
OEP verifies that a bundle is intact, contract-conformant, and reproducibly verifiable - nothing more, nothing less.
And in a world of increasing software complexity, that might be the most important thing we can guarantee.
For inquiries, contact the OEP team.
