Explain Hands On Lab and Phase Exit without relying on framework buzzwords.
Connect the lesson to the phase outcome: Build a testing strategy that proves pure rules, service orchestration, repositories, HTTP contracts, frontend behavior, and critical browser flows at the right cost.
Reproduce the relevant behavior and verify it with evidence.
Diagnose at least one representative failure instead of guessing.
Figure 28.12 — TaskFlow boundary map
risk/question
→
choose boundary
→
arrange controlled state
→
execute behavior
→
assert outcome/contract
→
cleanup
This lesson belongs to Phase 28. Keep the full request/data path visible even when today's code changes only one box.
Instructor workflow: predict first → implement the smallest slice → run it → inspect evidence → break one assumption → diagnose → explain it back. Do not copy the whole code block before understanding the first failing boundary.
Hands-On Lab and Phase Exit
TaskFlow - Full Stack Developer 2026
Lab 1 - Pure policy
• Write table-driven tests for every allowed and rejected Task status transition.
• Add one deterministic due-date policy test with a fixed clock input.
Lab 2 - Service
• Use FakeTaskRepository.
• Prove MEMBER can update an assigned Task.
• Prove a denied transition produces the expected application exception.
Lab 3 - Repository + PostgreSQL
• Create two Workspaces and two Tasks.
• Prove listScoped never leaks the unrelated Workspace.
• Prove pagination totalItems is computed inside the same authorization filter.
Lab 4 - HTTP security
• 401 without identity.
• 403 or scoped 404 for unauthorized resource/action.
• 400 for invalid DTO.
• 200/201 for valid authorized request.
Lab 5 - Frontend
• Form error can be found by accessible text/role.
• TanStack optimistic failure rolls back.
• No shared QueryClient state leaks between tests.
Lab 6 - Browser
• Playwright: sign in fixture -> create Task -> update status -> reload -> persisted state.
• Repeat one permission-denied workflow with MEMBER role.
Phase exit checklist
• I can explain unit vs integration vs HTTP/e2e vs browser E2E.
• I know when a fake repository is appropriate and when a real database is required.
• I can test authentication/authorization without trusting the browser.
• I can test a React form through accessible interactions rather than internals.
• I can keep TanStack Query tests isolated.
• I can design one critical Playwright journey instead of browser-testing every edge case.
• I understand that coverage is evidence, not correctness.
Sources
Source Used for
NestJS Testing Nest 12 uses runner-agnostic testing utilities; new projects use
https://docs.nestjs.com/fundamentals/testing Vitest by default and Nest integrates with Supertest for HTTP e2e
tests.
Prisma ORM v7 Testing Use a dedicated resettable test database for integration tests; unit
https://www.prisma.io/docs/orm/v7/more/best-practices tests should isolate logic from external dependencies.
Prisma Unit Testing Unit testing isolates logic; dependency injection/mocking can keep
https://docs.prisma.io/docs/orm/prisma-client/testing/unit-te database calls out of unit suites.
sting
Next.js Vitest Next.js documents Vitest + React Testing Library for
https://nextjs.org/docs/app/guides/testing/vitest unit/component testing; async Server Components are better
covered by E2E.
Next.js Playwright Next.js recommends Playwright for browser end-to-end tests and
https://nextjs.org/docs/app/guides/testing/playwright production-like testing.
React Testing Library Tests should resemble how users interact with the UI rather than
https://testing-library.com/docs/react-testing-library/intro/ assert implementation details.
TanStack Query Testing Tests should isolate QueryClient instances and avoid shared cache
https://tanstack.com/query/latest/docs/framework/react/gui state across tests.
des/testing
Playwright Playwright runs Chromium, Firefox and WebKit with isolated
https://playwright.dev/docs/browsers browser contexts.
Vitest npm Current stable used in this phase: 5.0.1.
https://www.npmjs.com/package/vitest
React Testing Library npm Current stable used in this phase: 16.3.3.
https://www.npmjs.com/package/@testing-library/react
Playwright npm Current stable used in this phase: 1.63.0.
https://www.npmjs.com/package/@playwright/test
Executable lesson studio · testing
Now turn the explanation into engineering skill.
Tests are executable behavioral contracts. Good tests protect meaningful invariants and failure cases, not implementation trivia.
By the end, you should be able to
Explain Hands On Lab and Phase Exit in terms of concrete inputs, ownership, outputs, and evidence.
Implement or reproduce the smallest TaskFlow slice that demonstrates this testing concept.
Diagnose one representative testing failure using observable evidence instead of trial-and-error.
Figure 28.12B — Mental model
behavior contract
→
arrange
→
act
→
assert
→
regression signal
Read left-to-right while implementing. When debugging, walk right-to-left until the first observed fact differs from your prediction.
Code-along sequence
One coherent change at a time
01
Restate the goal of “Hands On Lab and Phase Exit” as one observable behavior. Write the success signal before touching code.
02
Trace the boundary map: behavior contract → arrange → act → assert → regression signal. Mark the one boundary this lesson changes.
03
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
04
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
05
Connect the slice to TaskFlow’s phase artifact: Vitest + integration + Playwright test suite with deterministic fixtures and CI-ready commands.. Verify behavior from the outside as a user or API client would.
06
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
07
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Verification
Prove the happy path
Run the narrowest relevant command or request and require a clean exit/status.
Inspect the boundary-specific evidence: terminal output, Network panel, database row/query plan, test report, container health, or deployment logs.
Repeat the behavior once after the change so a one-off cached or stale result cannot masquerade as success.
Break it on purpose
Build debugging memory
E2E used for every rule, making feedback too slow
Change one assumption in the testing example—identity, input, configuration, ordering, connectivity, or state—and predict the exact symptom before running it.
SymptomInvestigation path
Test passes alone but fails in suite
Look for shared database state, timers, globals, unordered execution, or missing cleanup before adding retries.
Mock-heavy test gives false confidence
Move the highest-risk boundary to an integration test with the real adapter/database.
Closed-reference challenge
Can you transfer the idea?
Without copying the final source, create a second small scenario that applies “Hands On Lab and Phase Exit” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Explain-back
Answer these without reopening the solution
What problem does Hands On Lab and Phase Exit solve in TaskFlow, and what would be observably wrong without it?
Which part of the testing boundary owns the decision, and which neighboring layer must not own it?
What evidence proves the happy path instead of merely suggesting it worked?
Name one realistic failure or abuse case and the first place you would inspect.
If requirements doubled tomorrow, which part of this design should stay stable and which part is allowed to change?
Lesson studio
Turn the reading into skill
01
Do it
Write one Playwright flow for a critical user journey and make setup/cleanup reproducible.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.02
Break it safely
E2E used for every rule, making feedback too slow
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.03
Explain it back
Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.
Exit ticket
Before marking complete
Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.