Simulation is often treated as a paper appendix. In software development, simulation should be an operational quality system.
Why Independent Simulation Matters
If simulation logic is derived from implementation logic, both can be wrong together. Independent simulation acts as an external measurement instrument.
A good simulator should answer: if the world followed assumptions $A$, would this implementation recover the right behavior?
Build A Scenario Matrix
Use a matrix rather than one benchmark setting. At minimum include:
- Nominal settings where assumptions hold.
- Boundary settings near identifiability limits.
- Violation settings that test graceful degradation.
This gives you a behavioral map, not a single point estimate of quality.
Core Metrics
Track metrics aligned with method goals:
- Bias: $E[\hat{\theta}] - \theta$.
- Variance and RMSE.
- Confidence interval coverage.
- Convergence and runtime stability.
Metrics should be pre-registered for release gating, not selected after seeing results.
Failure Interpretation
When diagnostics fail, classify root causes:
- Specification mismatch.
- Optimization instability.
- Numerical precision issues.
- Incorrect uncertainty calculations.
This prevents the common anti-pattern of patching symptoms without fixing structure.
Key Takeaway
Independent simulations convert correctness from opinion into measurable evidence.