Unit and integration tests for service layer
epic-cognitive-accessibility-foundation-task-017 — Write flutter_test unit and integration tests for the service layer: CognitiveLoadRuleEngine (all constraint rules, violation detection, edge cases at boundaries), PlainLanguageContentService (message resolution, org overrides, fallback chain), and AccessibilityDesignTokenEnforcer (token validation, violation assertions). Include golden tests for WizardStateManager BLoC state transitions and draft auto-save trigger points.
Acceptance Criteria
Technical Requirements
Execution Context
Tier 4 - 323 tasks
Can start after Tier 3 completes
Implementation Notes
Organize CognitiveLoadRuleEngine tests around each rule, not each method — this makes it obvious which rule is broken when a test fails. Use a parameterized helper like void testBoundary(String ruleName, int passing, int failing, ...) to avoid duplicating boundary test boilerplate across all constraints. For AccessibilityDesignTokenEnforcer, define test fixtures as constants in a separate test_fixtures.dart file so token values are not scattered across test methods. The WizardStateManager golden tests should use blocTest() with verify: to assert the mock WizardDraftRepository was called the expected number of times — this is the critical correctness check for the auto-save feature.
Avoid testing private methods directly — if a private method needs independent testing, it is a sign it should be extracted into a collaborator class.
Testing Requirements
Structure tests in four files: cognitive_load_rule_engine_test.dart, plain_language_content_service_test.dart, accessibility_design_token_enforcer_test.dart, wizard_state_manager_bloc_test.dart. Use bloc_test's blocTest() helper for all WizardStateManager state transition tests — do not manually call emit() or listen to streams in tests. Use fakeAsync() from flutter_test for any time-sensitive behaviour in WizardStateManager (e.g., debounced auto-save). For PlainLanguageContentService org override chain tests, inject a mock HelpContentRegistry and mock ErrorMessageRegistry so each override level can be toggled independently.
Document the constraint boundary values being tested with inline comments so future maintainers understand the magic numbers.
The error message registry and help content registry both depend on bundled JSON assets loaded at startup. If asset loading fails silently (e.g. malformed JSON, missing pubspec asset declaration), the entire plain-language layer falls back to empty strings or raw error codes, breaking the accessibility guarantee app-wide.
Mitigation & Contingency
Mitigation: Implement eager validation of both assets during app initialisation with an assertion failure in debug mode and a structured error log in release mode. Add integration tests that verify asset loading in the Flutter test harness on every CI run.
Contingency: Ship a hardcoded minimum-viable fallback message set directly in Dart code so the app always has at least a safe generic message, preventing a blank or code-only error surface.
The AccessibilityDesignTokenEnforcer relies on dart_code_metrics custom lint rules. If the lint toolchain is not already configured in the project's CI pipeline, integrating a new linting plugin may cause unexpected build failures or require significant CI configuration work beyond the estimated scope.
Mitigation & Contingency
Mitigation: Audit the existing dart_code_metrics configuration in the project before starting implementation. Scope the lint rules to a separate Dart package that can be integrated incrementally, starting with the most critical rule (hard-coded colors) and adding others in subsequent iterations.
Contingency: Fall back to Flutter test-level assertions (using the cognitive-accessibility-audit utility) to catch violations in CI if the lint plugin integration is delayed, preserving enforcement coverage without blocking the epic.
WizardDraftRepository must choose between shared_preferences and Hive for local persistence. Choosing the wrong store for the data volume (e.g. shared_preferences for complex nested wizard state) can lead to serialisation bugs or performance degradation, particularly on lower-end Android devices used by some NHF members.
Mitigation & Contingency
Mitigation: Define a clean repository interface first and implement shared_preferences as the initial backend. Profile serialisation round-trip time with a realistic wizard state payload (≈10 fields) before committing to either store.
Contingency: Swap the persistence backend behind the repository interface without touching wizard UI code, which is possible precisely because the repository abstraction isolates the storage detail.
The AccessibilityDesignTokenEnforcer scope could expand significantly if a large portion of existing widgets use hard-coded values. Discovering widespread violations during this epic would force either a major refactor or a decision to exclude legacy components, potentially reducing the enforcer's coverage and value.
Mitigation & Contingency
Mitigation: Run a preliminary audit of existing widgets using a simple grep for hard-coded hex colors and raw pixel values before implementation begins. Use the results to set a realistic remediation boundary for this epic and log all out-of-scope violations as tracked tech-debt items.
Contingency: Scope the enforcer to new and modified components only (via file-path filters in dart_code_metrics config), shipping a partial but immediately valuable coverage rather than blocking the epic on full-codebase remediation.