VSEL

Document

Constraint Derivation

**Verifiable Semantic Execution Layer (VSEL)**

Verifiable Semantic Execution Layer (VSEL)

1. Purpose

This document defines how formal semantics are transformed into constraint systems suitable for proof generation.

It establishes a deterministic, verifiable transformation:

[ \mathcal{D}: SIR \rightarrow C ]

Where:

  • ( SIR ) is the semantic intermediate representation
  • ( C ) is the constraint system

The core requirement is:

Constraints must encode semantic validity, not just computational execution.


2. Constraint Objective

Given a trace ( \tau ), constraints must enforce:

[ SatisfiesConstraints(\tau) \Leftrightarrow ValidTrace(\tau) ]

This implies two properties:

2.1 Soundness

[ SatisfiesConstraints(\tau) \Rightarrow ValidTrace(\tau) ]

No invalid execution may satisfy constraints.


2.2 Completeness

[ ValidTrace(\tau) \Rightarrow SatisfiesConstraints(\tau) ]

All valid executions must be representable.


3. Constraint Domains

Constraints are derived over:

  • state variables
  • inputs
  • transition relations
  • invariants
  • trace structure

Each domain must be explicitly mapped.


4. State Constraints

Let ( s = (C, D, E, \tau) )

Constraints enforce:

4.1 Canonical State Validity

[ C \in ValidC ]

Includes:

  • structural checks
  • domain constraints
  • encoding correctness

4.2 Derived State Consistency

[ D = Derive(C) ]

Derived values must be recomputed, not trusted.


4.3 Environment Validity

[ E \in ValidE ]

All environmental assumptions must be constrained.


4.4 Metadata Consistency

[ \tau_{i+1} = Update(\tau_i) ]

Ensures trace continuity.


5. Input Constraints

For each input ( \sigma ):

5.1 Canonical Form

[ \sigma = Canonical(\sigma) ]

Reject ambiguous encodings.


5.2 Authorization

[ Auth(\sigma) = true ]

Signature or permission checks must be fully constrained.


5.3 Domain Validity

[ \sigma \in \Sigma ]

Input must belong to valid input space.


6. Transition Constraints

For each transition:

[ (s, \sigma) \rightarrow s' ]

Constraints must enforce:

[ Apply(s, \sigma) = s' ]


6.1 Functional Correctness

Each field in ( s' ) must be derived from:

  • ( s )
  • ( \sigma )

No unconstrained fields allowed.


6.2 Mutation Scope

Only allowed fields may change:

[ Diff(s, s') \subseteq AllowedFields ]


6.3 No Implicit State

All state changes must be explicit in constraints.

If a value changes and is not constrained, that is a vulnerability.


7. Invariant Constraints

All invariants must be encoded.


7.1 Local Invariants

[ L(s, \sigma, s') ]

Example:

  • resource conservation
  • bounded changes

7.2 Global Invariants

[ G(s) ]

Example:

  • valid structure
  • commitment consistency

7.3 Temporal Invariants

[ TInv(\tau) ]

Example:

  • monotonic counters
  • no rollback

8. Trace Constraints

Constraints must enforce:

8.1 Transition Linking

[ s_{i+1} = Apply(s_i, \sigma_i) ]


8.2 Ordering

[ i < j \Rightarrow Order(i, j) ]

No reordering unless explicitly modeled.


8.3 Completeness

All transitions must be present.

No skipped states.


9. Observable Constraints

For each transition:

[ Obs(s, \sigma, s') = o ]

Constraints must enforce:

[ o = ComputeObservable(s, \sigma, s') ]

Ensures external outputs are correct.


10. Constraint Generation Rules

The derivation process must be:

  • deterministic
  • formally specified
  • auditable

10.1 Rule-Based Mapping

Each SIR construct maps to constraint templates.

Example:

  • assignment → equality constraint
  • arithmetic → arithmetic circuit
  • condition → boolean constraint

10.2 No Manual Constraint Injection

Constraints must not be handwritten outside the derivation system.

Manual constraints introduce semantic drift.


11. Underconstraint Prevention

The system must prevent:

11.1 Unused Variables

Every variable must be constrained.


11.2 Free Witness Values

Witness assignments must be uniquely determined.


11.3 Partial Constraints

All branches must be constrained, not only the executed one.


12. Constraint Completeness Verification

The system must validate:

[ ValidTrace(\tau) \equiv SatisfiesConstraints(\tau) ]

Using:

  • differential testing
  • symbolic execution
  • adversarial witness generation

13. Cross-Layer Consistency

13.1 Semantic Mapping Alignment

[ \mu_{Tr}(\tau_c) = \tau_f ]

Constraints must apply to ( \tau_f ).


13.2 Execution Alignment

[ Apply_{impl} = Apply_{constraint} ]


13.3 Proof Alignment

[ Verify(\pi) \Rightarrow SatisfiesConstraints(\tau) ]


14. Failure Modes

14.1 Underconstraint

Invalid execution satisfies constraints.


14.2 Overconstraint

Valid execution cannot be proven.


14.3 Constraint Drift

Constraints diverge from formal semantics.


14.4 Witness Ambiguity

Multiple witnesses represent same constrained output.


15. Minimal Validation Conditions

A valid constraint system must satisfy:

  • soundness
  • completeness
  • determinism
  • semantic alignment

16. Closing Statement

Constraints are not the system.

They are a projection of the system.

If that projection is incomplete, you are proving a shadow and calling it truth.