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docs: frontend architecture plan — Tauri desktop + Flutter mobile #10

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gabogg merged 1 commit from docs/frontend-architecture into dev 2026-06-23 15:58:29 +00:00
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gabogg commented 2026-06-23 15:53:03 +00:00
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Comprehensive architecture plan for the new frontend stack, detailing:

Tech stack:

  • Desktop: Tauri 2.x + Svelte 5 (~30-60 MB RAM, ~5 MB binary)
  • Mobile: Flutter (Android + iOS, single Dart codebase)

Covers:

  • Technology rationale with benchmarks (RAM, binary size, startup)
  • Barcode vs QR strategy — support both, detect automatically
  • Development standards (git flow, linting, formatting, typing)
  • Styling standards (dark-mode-first desktop, Material 3 mobile)
  • Testing & QA (unit, widget, E2E with specific tooling per layer)
  • Build optimization & tree-shaking (expected ~5 MB desktop bundle)
  • Full library manifest with justification for every dependency
  • API contract compatibility (zero backend changes needed)
  • 6-phase implementation plan

Resolves the barcode vs QR question: QR is technically superior for cameras, but we detect both automatically because warehouses have existing 1D labels we must support.

Comprehensive architecture plan for the new frontend stack, detailing: **Tech stack:** - Desktop: Tauri 2.x + Svelte 5 (~30-60 MB RAM, ~5 MB binary) - Mobile: Flutter (Android + iOS, single Dart codebase) **Covers:** - Technology rationale with benchmarks (RAM, binary size, startup) - Barcode vs QR strategy — support both, detect automatically - Development standards (git flow, linting, formatting, typing) - Styling standards (dark-mode-first desktop, Material 3 mobile) - Testing & QA (unit, widget, E2E with specific tooling per layer) - Build optimization & tree-shaking (expected ~5 MB desktop bundle) - Full library manifest with justification for every dependency - API contract compatibility (zero backend changes needed) - 6-phase implementation plan Resolves the barcode vs QR question: QR is technically superior for cameras, but we detect both automatically because warehouses have existing 1D labels we must support.
Covers full architecture breakdown, technology rationale, development
standards, styling standards, testing/QA strategy, barcode vs QR
analysis, build optimization & tree-shaking, dependency manifest,
API contract compatibility, and phased implementation plan.

Co-authored-by: CommandCodeBot <noreply@commandcode.ai>
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