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Stefan ebdb92713a Docs: evaluation of backend-cached invoice editing over SignalR

Assesses the proposed server-held edit state + SignalR live-edit channel against
the current stateless design. Recommendation: don't do the full rewrite now (it
adds stateful-server/scaling/reconnect complexity for a single-editor back-office
flow); instead add a stateless inv/calc endpoint that reuses the backend pricing
(InvoiceSetPricing/VAT) so the editor stops duplicating the math — capturing the
real value without sockets. Add SignalR later only as transport if real-time
co-editing becomes a genuine requirement.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

2026-06-05 16:43:54 +02:00

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Evaluation — Backend-cached invoice editing over SignalR

Idea (as proposed): hold invoices that users are editing in a server-side cache, keep a SignalR / WebSocket connection open, apply each front-end change in the backend, and push the recomputed state back to the browser. The backend becomes the single source of truth for the in-progress invoice.

This note evaluates that against the current design and recommends a path.

1. How invoice editing works today

Stateless. The browser holds the editor state. It posts the whole invc JSON to req/sprep|sedit|save; the server computes/persists and returns a PDF preview (image collection). No per-user editing state lives on the server.
Totals/§13b/§35a and now set pricing are computed from posted data; the invoice total comes from the registration balance, not summed lines.
Auth is cookie-based (OCORECookieAuthenticationEvents), SQL-first data access, controller is stateless and DI-scoped.

Implication: the server is horizontally scalable and crash-tolerant for editing — there is nothing to lose if a node restarts mid-edit.

2. What the proposal would buy

Benefit	Real for Fuchs?
Server-authoritative calculation (one place for pricing/VAT/set rules)	Partly already true — the PDF/totals are server-computed; the editor only previews. The duplicated logic is the live line math in JS.
Real-time multi-user co-editing	Low value — invoices are edited by one back-office user at a time; concurrent editing of the same draft is rare.
Live validation / instant recompute without full round-trips	Some value — smoother UX than re-posting the whole `invc` for each tweak.
Reduced payload (deltas vs whole invoice)	Marginal — invoices are small.

3. Costs and risks

Server-side edit state. Per-user/per-draft cache with lifetime management (idle expiry, explicit discard, max size), or the server leaks memory. Needs a distributed cache if scaled out (Redis), or sticky sessions for SignalR.
Concurrency/locking. Two tabs or two users on the same draft → need optimistic concurrency / locking semantics that don't exist today.
Connection lifecycle. Reconnect, replay, and "lost update" handling; offline/flaky networks; auth on the socket (cookie works, but token refresh and disconnect-on-logout must be handled).
Scaling. SignalR with multiple instances needs a backplane (Redis/Azure SignalR). Today the app has none.
Big rewrite of the editor. The 1,200-line fis.inv_shared.js becomes an event-driven client of server state — a substantial, risky rewrite of working code, with new failure modes (desync between optimistic UI and server truth).
Testing surface grows (connection states, races) far beyond the current request/response model.

For a single-tenant back-office app with one editor at a time, this is a lot of accidental complexity for modest UX gains.

4. Recommendation

Do not do a full SignalR rewrite now. It optimises a problem (real-time collaboration, server-held edit state) the business doesn't strongly have, while adding stateful-server, scaling, and reconnection complexity to an app that is currently simple and robust.

Prefer an incremental, lower-risk path that captures most of the value:

Single source of pricing truth (highest value, do first). Add a stateless endpoint inv/calc that takes the invc JSON and returns the computed lines + totals + set-mode resolution using the same backend code (InvoiceSetPricing, VAT, §13b/§35a). The editor calls it on change (debounced) to recompute, instead of duplicating the math in JS. This removes the front/back duplication — the actual pain — without sockets or server state. It also makes the interplay fully unit-testable (the endpoint is pure).
Keep preview as-is (post → PDF image) but allow it to reuse inv/calc.
If/when live UX is still wanted, add SignalR only as a transport on top of the stateless calc (push recompute results), keeping persistence stateless. Defer server-held draft state until genuine multi-user co-editing is required.
If server-held drafts are truly needed, scope a pilot: one entity (invoice draft), IDistributedCache-backed, explicit acquire/release lock, idle TTL, and a reconnect/replay protocol — behind a feature flag, measured against the current flow before rollout.

Why this fits the codebase

It aligns with the just-completed DI service layer: the calc lives in IInvoiceService/InvoiceSetPricing (already tested), reused by both the preview and a future socket. We get "changes computed by the backend, reflected in the frontend" — the stated goal — without turning a stateless, scalable web app into a stateful real-time system prematurely.

Suggested next step: implement inv/calc (item 1) and migrate the editor's line math to it; revisit SignalR only if real-time/co-editing becomes a real requirement.

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