Dual Testing

Dual Testing

A language-agnostic strategy for code at the boundary between your application and external infrastructure: integration tests prove the full chain works for happy paths; unit/slice tests prove the error-handling and mapping logic. It aligns with the Testing Honeycomb / Test Diamond philosophy — boundary code is dominated by interaction complexity, so lean on integration for wiring and on fast mock-based tests for the branchy error logic.

The strategy is the same in every language. Only the tooling changes. Concrete per-language references are listed at the bottom; if none matches your language, the Adapt When No Reference Exists algorithm tells you how to apply it anyway.

Definitions

• Integration test — exercises the real application boundary plus a real external dependency (real database, broker, etc., typically via Testcontainers). Proves the wiring and the happy-path behavior end to end.
• Unit/slice test — the smallest test that still includes the mapping/adapter code (input validation, domain-error → outcome mapping), with the semantic dependencies mocked or faked. In some frameworks the mapping lives outside the handler class (an exception filter, @ControllerAdvice, error middleware), so the right test is a framework slice (in-process pipeline with the service mocked), not a pure class unit test.
• The rule: never duplicate happy paths in both layers. Integration proves the chain; unit/slice proves the mapping. Some overlap on boundary scenarios (e.g. not-found) is fine because they exercise different concerns.

Decision List

Where a scenario belongs. The "outcome" is described generically — map it to your transport: HTTP status, gRPC status code, CLI exit code + stderr, or queue ack/nack/retry/dead-letter.

• Happy path (successful create/read/update/delete) — Integration: proves real wiring. Outcome: success (e.g. HTTP 2xx).
• Handler input validation (bad/missing field) — Unit/slice: pure mapping logic, no infra. Outcome: client error (e.g. HTTP 400).
• Framework/middleware/filter validation (idempotency key, body binding, content negotiation) — Integration or slice that includes that pipeline: the check runs before your handler.
• Auth/authz policy (middleware-owned) — Integration/slice including the middleware.
• Resource not found — Both acceptable: integration proves the chain, unit/slice proves the mapping. Outcome: not-found (e.g. HTTP 404).
• Infrastructure/DB error — Unit/slice: cannot force reliably with real infra. Outcome: server error (e.g. HTTP 500, or queue nack→retry/DLQ).
• Circuit breaker open / resilience pattern — Unit/slice: deterministic only via a mock. Outcome: unavailable (e.g. HTTP 503).
• Timeout / cancellation — Unit/slice: drive via a cancelled context/token.
• Idempotency / deduplication — Integration: requires real state.
• Notifications / events emitted — Integration: side effect of real infra.
• Side effects in another store — Integration: verifies the real effect.
• Empty-collection serialization ([] not null) — Integration: contract verified with real data.
• Pure business/domain logic (defaults, calculations, optimistic-lock version handling) — Ordinary unit tests with real objects, no mocks or infra needed.

Do not bake specific status numbers into the strategy. HTTP 499 in particular is client-closed-request (nginx-specific), not a portable code — keep such codes in a transport-specific note, never in the portable list.

Testability Prerequisites (Principles)

Make the boundary mockable without coupling tests to infrastructure:

• Depend on a narrow semantic port. Each handler needs a small abstraction for the data operations it uses (a use-case / port / repository interface), not the DB driver. If the project already has service interfaces, ports, mediators or handlers, mock those — do not add a redundant per-controller interface.
• No external I/O at construction. A factory/constructor that wraps a connection must not ping or validate at construction time — unless the framework explicitly owns startup validation (e.g. a DI-container health check). This lets a test inject a broken or mock dependency and exercise the error path at request time.
• Inject the port at the wiring point. The setup/registration code takes the abstraction; inject the real implementation in production and integration tests, a mock in unit/slice tests.
• Mock the semantic port, not the driver. Mock domain methods (ListItems, DeleteItem); never mock Query/Rows/Tx. Driver-level mocks test SQL strings, not behavior, and are fragile.
• Encapsulate a transaction in one method. When a handler orchestrates begin → queries → commit, put the whole transaction in one port method returning a domain result or a domain error. The handler only maps result → outcome.
• Error model — two idioms, one decision. Distinguish business errors (→ not-found / client error) from infrastructure errors (→ server error). Languages that return errors use sentinels/typed errors (Go errors.Is(err, ErrNotFound), Rust Result); languages that throw use typed exceptions (NotFoundException) caught at the mapping layer (@ControllerAdvice, exception filter, error middleware). The mapping decision is identical; only the mechanism differs — and because the mapping layer is often a separate class, the test that covers it is usually a slice test.

Worker / Background-Job Variant

The same split applies to consumers and workers:

• One integration test drives a real message/job through the real dispatcher and real infra (happy path).
• Unit/slice tests mock the dispatch protocol to prove failure handling (retry, dead-letter, status transitions).
• Create a fresh dispatcher/engine per test when registration is one-shot — some dispatchers reject or panic on duplicate handler registration.
• Mock the full dispatch protocol the worker depends on (claim/next, resolve target, set status, succeed/fail).

Recommendations

Trade-offs, not hard rules:

• Fixed error strings on server errors for contract-stable endpoints — do not leak internal error text. This keeps integration tests from coupling to internal messages.
• Empty collections serialize as [], not null — verify in integration. (The language-specific mechanics, if any, live in the per-language reference.)
• Update the dependency manifest/lockfile after adding a mocking library (and any tidy/restore step), or CI may silently skip the new tests.

When This Strategy Does NOT Apply

• Pure functions (no external dependencies) — output-based tests directly.
• Domain logic without infrastructure — unit tests with real objects, no mocks.
• Utility code — simple tests, no strategy needed.

The dual strategy is specifically for code that sits at the boundary between your application and external infrastructure (databases, APIs, message queues).

Language References

If a reference matches your language or framework, read only that reference before writing tests. The core above tells you what belongs in each layer; the reference gives the idiomatic tooling, test shape, and language-specific gotchas — the core alone is not enough to get the idioms right.

• Go (Gin, pgx, testify, testcontainers-go) — [references/go.md](references/go.md)
• .NET / C# (ASP.NET Core; xUnit, Testcontainers for .NET, WebApplicationFactory, Moq) — [references/dotnet.md](references/dotnet.md)
• Java (Spring Boot; JUnit 5, Testcontainers @ServiceConnection, MockMvc, Mockito) — [references/java.md](references/java.md)

Adapt When No Reference Exists

No reference for your language/framework? Do not skip the strategy — adapt it. Follow this algorithm:

1. Identify the boundary adapter (handler/controller/consumer) and its transport contract (HTTP/gRPC/CLI/queue).
2. Identify the real external dependencies (DB, cache, broker, external API).
3. Write one happy-path test through the real wiring and real infrastructure. Testcontainers has libraries for most languages (Java, .NET, Go, Node, Python, Rust, and more); otherwise use an equivalent ephemeral real dependency and state the confidence gap.
4. Put each error-mapping branch in the smallest unit/slice test that still includes the mapping code.
5. Mock the semantic ports/use-cases — never the DB driver or framework internals.
6. Keep the Decision List above. Only the tooling changes, not the strategy.

Composing with Other Skills (Optional)

This skill is self-contained. If you also use them, these compose cleanly:

• /test-namer — how to name the test (this skill decides where it goes; test-namer decides what to call it).
• /vertical-slice-architecture — how to structure the feature directory.
• /low-complexity — keeps test functions readable.

None are required to apply dual testing.

Checklist

For each new handler, feature, or worker:

• [ ] Each handler depends on a narrow semantic port (or reuses an existing one), not the DB driver
• [ ] The wiring point injects the port — real in prod/integration, mock in unit/slice
• [ ] Constructors/factories do no external I/O at construction (unless the framework owns startup validation)
• [ ] One integration test per happy path, through real wiring and real infrastructure
• [ ] One unit/slice test per error-mapping branch (validation, not-found, infra error, resilience), with the port mocked
• [ ] Happy paths are NOT duplicated in the unit/slice layer
• [ ] The matching language reference was read — or, if none exists, the 6-step adaptation was applied

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mryll
• Source: mryll/skills
• License: MIT

Install and usage instructions live in the source repository linked above.