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09.01.2026

Mocks aren't Engines: Why TestSeed focuses on Data Identity over Logic

A common challenge when designing test data is complex business logic. For example: "The sum of all line items in an order must exactly match the total invoice amount." When developers encounter this, they often look for a tool that can "calculate" these values during generation. But here is the truth: Your mock data generator shouldn't be a second version of your backend. If you try to replicate complex mathematical dependencies inside your data generation tool, you are essentially building a "Shadow Business Engine" that you now have to maintain.

The Misconception of "Smart" Mocks

A common challenge when designing test data is complex business logic. For example: "The sum of all line items in an order must exactly match the total invoice amount." When developers encounter this, they often look for a tool that can "calculate" these values during generation. But here is the truth: Your mock data generator shouldn't be a second version of your backend. If you try to replicate complex mathematical dependencies inside your data generation tool, you are essentially building a "Shadow Business Engine" that you now have to maintain.

TestSeed’s Philosophy: Contract over Calculation

TestSeed is designed for Contract Fidelity and Data Identity, not for simulating your entire business logic.

1. Unit Tests vs. Integration Tests

If you want to test if your calculation logic works (Sum A + B = C), you should use a Unit Test. You don't need a complex data platform for that; you need a isolated function test with specific inputs.

TestSeed solves a different problem: System Consistency. It ensures that Service A (Ordering) and Service B (Invoicing) are talking about the same user, the same product names, and the same UUIDs—every single time.

2. Structure & Identity First

The goal of TestSeed is to ensure that the structure (Schema) and the identity (Seeds) of your data are consistent across system boundaries. We ensure the "envelope" and the "identity" are correct, so your integration tests don't fail because of mismatched IDs or malformed strings.

3. The "Override" Pattern for Extreme Logic

What if you really need that one specific mathematical edge case for an integration test?

The best practice is the Override Pattern: Use TestSeed to generate the 90% of "boilerplate" data (User profiles, Addresses, Metadata) to ensure system-wide consistency. Then, in your specific test code, simply override the two or three fields that require precise mathematical logic for that one scenario.

The Benefit: Keeping it Lean

By keeping TestSeed focused on deterministic identity rather than business simulation:

  • Your schemas stay readable and maintainable.
  • Your data generation remains lightning fast.
  • You avoid the trap of "testing your mocks" instead of your application.

Conclusion

Don't turn your test data platform into a replica of your backend. Use TestSeed to guarantee that your services are perfectly synced, and keep your business logic where it belongs: in your code.

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