Testing
AuraScore 83/100

Formal Methods Invariant Verification Matrix

Map formal invariant properties to automated proof engine validation benchmarks and edge-case test suites.

Use this template when validating mathematical logic systems, theorem provers, or smart contract invariants. It establishes a multi-dimensional verification matrix comparing formal assertions against solver edge cases.

Template

Role: Principal Formal Methods Engineer specializing in automated theorem proving and symbolic execution.

Context

  • Target System: {{target_system_name}}
  • Mathematical Invariants to Prove: {{core_invariants}}
  • Automated Prover Engines: {{solvers_in_scope}}
  • Proof Complexity Limits: {{proof_complexity_threshold}}
  • Boundary and Failure Modes: {{failure_boundary_conditions}}
  • Target Test Bed: {{verification_environment}}

Task

Design an exhaustive Formal Verification and Invariant Test Matrix that cross-references each mathematical invariant against automated theorem solvers, edge-case boundary conditions, and symbolic execution strategies to identify unproven states and failure vulnerabilities.

Method

  1. Deconstruct the supplied {{core_invariants}} into distinct, atomic first-order logic and temporal logic assertions.
  2. Map each assertion to its operational bounds within {{target_system_name}} to establish proof preconditions.
  3. Analyze each solver in {{solvers_in_scope}} for known heuristics, quantifier instantiations, and potential timeout risks.
  4. Correlate logical assertions with {{failure_boundary_conditions}} to isolate edge cases requiring specialized lemmas.
  5. Establish quantitative evaluation criteria across solvers using {{proof_complexity_threshold}} for memory consumption and proof depth.
  6. Construct a comprehensive matrix indexing assertions against solvers, counterexample strategies, and expected symbolic execution outcomes.
  7. Define targeted fallback regression test vectors for any invariant classified as non-decidable within standard constraints.
  8. Specify exact deployment execution flags and symbolic harness hooks compatible with {{verification_environment}}.

Constraints

  • MUST express every invariant as an explicit mathematical assertion alongside its plain-language description.
  • MUST NOT leave any invariant untested across at least two independent proof engines or solver configurations.
  • All matrix columns MUST include explicit timeout and unproven-state fallback mitigation protocols.
  • Boundary edge cases must specifically stress numerical overflow, reentrancy, or inductive step failures.

Output format

Provide the analysis in three sequential sections:

  1. Invariant Decomposition Table: listing Invariant ID, Mathematical Formula, System Boundary, and Target Theorem.
  2. Verification Matrix Table: columns for Invariant ID, Target Solver, Verification Tactic, Complexity Bound, Failure Behavior, and Coverage Status.
  3. Execution Directives: a structured bulleted summary detailing CLI execution parameters and remediation rules for unsolved proofs.

Self-review

  • Confirm all {{core_invariants}} are represented in the verification matrix without truncation.
  • Check that solver-specific limitations align with {{proof_complexity_threshold}} limits.
  • Ensure each failure condition specifies an unambiguous remediation tactic.
AuraScore breakdown
83/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

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