ReceiptThresholdValidator unit tests
epic-receipt-capture-and-attachment-foundation-task-013 — Write comprehensive unit tests for ReceiptThresholdValidator covering: claim exactly at threshold (boundary condition), claim below threshold returns false, claim above threshold returns true, threshold loaded from mocked org config, and offline fallback to cached default of 100 NOK when config unavailable. Use flutter_test with mocked Supabase responses.
Acceptance Criteria
Technical Requirements
Execution Context
Tier 2 - 518 tasks
Can start after Tier 1 completes
Implementation Notes
Use mocktail (preferred over Mockito for null-safety) to mock the config loader. Each test group should set up its own ProviderContainer to avoid state leakage between tests. For the boundary test, document clearly in the test name what the expected semantics are ('at threshold requires receipt'). For the multi-org isolation test, call requiresReceipt with two different orgIds sequentially and assert each returns the correct result from its respective mocked config.
Keep test data as named constants at the top of the file (e.g., const kDefaultThreshold = 100.0) for maintainability.
Testing Requirements
Use flutter_test with Mockito or mocktail to mock the config loader dependency. Create a MockOrgThresholdConfigLoader that returns controlled OrgThresholdConfig objects. Structure tests in clearly named groups: 'below threshold', 'above threshold', 'at threshold boundary', 'offline fallback', 'multi-org isolation'. Each test should have a descriptive name that reads as a specification.
Use ProviderContainer with overrides to test the Riverpod-exposed validator in isolation. No real Supabase calls — all external dependencies are mocked.
Supabase Storage RLS policies using org/user/claim path scoping may not enforce correctly if claim ownership is not present in the JWT or if path segments are constructed differently at upload vs. read time, leading to data leakage or access denial for legitimate users.
Mitigation & Contingency
Mitigation: Define and test RLS policies in isolation before wiring to app code. Write integration tests that assert cross-org and cross-user access is denied. Use service-role key only in edge functions, never in client code.
Contingency: If client-side RLS proves insufficient, route all storage reads through a Supabase Edge Function that validates ownership before generating signed URLs, adding a controlled server-side enforcement layer.
Aggressive image compression may reduce receipt legibility below the threshold required for financial auditing, causing claim rejections or compliance failures despite technically successful uploads.
Mitigation & Contingency
Mitigation: Define minimum legibility requirements with HLF finance team before implementation. Set compression targets conservatively (e.g., max 1MB, min 80% JPEG quality) and validate with sample receipt images. Provide compression statistics in verbose/debug mode.
Contingency: If post-compression quality is disputed by auditors, increase the quality floor at the cost of larger file sizes, and add a manual override allowing users to skip compression for PDFs and high-quality scans.
The Flutter image_picker package behaves differently on iOS 17+ (PHPicker) vs older Android (Intent-based), particularly for file types, permission flows, and PDF selection, which may cause platform-specific failures not caught in development.
Mitigation & Contingency
Mitigation: Test image picker integration on physical devices for both platforms early in the sprint. Pin the image_picker package version and review changelogs before updates. Write widget tests using mock file results for each platform branch.
Contingency: If PHPicker or Android Intent differences cause blocking issues, implement separate platform-specific picker delegates behind the unified interface, allowing platform-specific fixes without breaking the shared API.