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Testing, Quality, and Code Health ​

Testing, Quality, and Code Health Graphics Coverage ​

Primary chapter graphic: System Functionality Test Stack. Accepted graphics: 1. Reviewed non-signal pages: 1. Open graphics in review: 0. QA status lives in graphics audit and visual review ledger.

Corpus pages: p. 40-41, p. 139, p. 149-150, p. 185, p. 216-217, p. 294 Coverage: 9 pages

This chapter is part of Marius's owned architecture build corpus. The text routes decisions; durable implementation signal is carried by accepted graphics, reviewed non-signal decisions, and the linked QA audit.

Chapter Visuals ​

Accepted graphics carry the canonical design signal for this chapter. Each selected source page is either accepted as a graphic or explicitly marked non-signal in the source-faithful ledger. Review and QA state live in visual inventory, visual review ledger, and graphics audit.

System Functionality Test Stack ​

System Functionality Test Stack

Open Review Queue ​

  • none

Reviewed Non-Signal Pages ​

  • Testing, Quality, And Code Health: RAG + Rag Map: source p. 40; batch 31; status non-signal/reviewed; ledger reason in visual-review-ledger.json

Use When ​

  • Change safety, regression risk, or maintainability matters more than raw delivery speed.

Avoid When ​

  • The artifact is disposable and has no repeated use.

Core Model ​

  • Tests and code health are feedback systems. They should cover the risks users and operators actually face.
  • Prefer explicit ownership over accidental coupling. Every boundary should say who owns correctness, cost, data, recovery, and change.
  • Use corpus page pointers for inspection, and keep the chapter notes focused on reusable design decisions.

Implementation Guidance ​

  • Pair unit tests for rules with integration tests for boundaries and smoke tests for critical workflows.
  • Write the smallest useful design note: purpose, inputs, outputs, state, failure behavior, observability, and rollback.
  • Choose the first implementation that can be tested against the real workflow without hiding a known production risk.

Tradeoffs ​

  • Broad tests catch integration drift but cost more to maintain.
  • Centralization reduces duplicated work but can become a bottleneck when every team needs exceptions.
  • Specialized infrastructure helps at scale, but it must earn its operational cost.

Failure Modes ​

  • Mocks prove the implementation, not the behavior users rely on.
  • The diagram shows boxes but not ownership, retry behavior, data freshness, or user-visible failure.
  • The system has no proof path for the highest-risk assumption.

Decision Checklist ​

  • Cover happy path, known edge case, failure mode, and one integration boundary.
  • Name the owner, source of truth, timeout, retry policy, and evidence that the path works.
  • Add one regression check for the failure mode most likely to recur.

Neutral Automation Examples ​

  • A notification service tests message formatting separately from provider delivery and retry behavior.
  • A neutral internal automation starts with fixtures, then adds credentials, permissions, and production scheduling only after the boundary is tested.
  • A customer-facing workflow keeps irreversible actions behind explicit approval until metrics show it is safe to automate further.