Add ~500 new E2E tests and ~300 new integration tests covering:
- 24 new GUI E2E specs: navigation, responsive layout, keyboard shortcuts,
tool UI for all 35 non-AI tools, batch/pipeline workflows, settings/RBAC,
visual regression, accessibility, and performance budgets
- 3 new E2E-Docker specs: batch workflows, advanced pipelines, cross-format
- 1 new adversarial integration test: memory pressure, corrupted files,
unicode filenames, extreme dimensions, pipeline/batch edge cases
- 29 expanded integration test files: HEIC/HEIF input, large files, parameter
boundaries, batch processing, format edge cases across all tools
- Cross-format matrix expanded: 641 tests covering every tool x 18 formats
- AI bridge unit tests expanded: lifecycle, tool modules, error propagation
- Unit test gaps filled: analytics, tool-registry, web stores
Also fixes:
- vitest.config.ts: exclude e2e-docs and e2e-landing from Vitest runner
- AI E2E specs: add sidecar health check to skip gracefully when Python
AI backend is not running instead of timing out
- Add 55 unit tests for feature-status.ts (installed.json CRUD, cache
behavior, install lock, model verification, crash recovery, composite
state) using real temp directories
- Add 36 integration tests for full install/uninstall lifecycle against
Docker containers (face-detection bundle, SSE progress, tool gates,
shared model protection, concurrent install prevention, auth guards,
container restart recovery)
- Fix noise-removal CPU timeout by adding megapixel-based timeout
calculation (120s/MP, min 5 minutes)
- Fix Playwright auth storage state race condition (mkdirSync before
saving analytics-user.json)
- Fix 2 skipped tests in fixes-verification.spec.ts by replacing
external ~/Downloads/sample dependency with existing test fixtures
- Enable skipped analytics-consent settings toggle test
- Restructure features.spec.ts to manage bundle state (uninstall/
reinstall OCR) so 501 guard tests run instead of skipping
- Update noise-removal test mock to include sharp metadata() method
Add 12 tests for background-removal downscaling (resize gate, portrait
orientation, mask upscale) and OOM model fallback (retry with u2net,
progress callback, no-retry guards, cascading failure).
Add OOM propagation tests to face-detection, noise-removal,
red-eye-removal, and OCR -- the four AI features that were missing them.
SnapOtter