# CB-RES-0001: game-state kernel capability: game.kernel.authoritative-state status: draft # becomes approved only after adversarial review (T04) tier: L (structural L, chaos roll pending at T04 declaration — see history trail) runnable-baseline: invoked — harness in research/CB-RES-0001-harness/boardgame-io/ Survey of the best existing implementations of a **turn/phase game-state kernel**: deterministic authoritative state, command → validation → events, simultaneous commit/reveal, hidden information, replay. Conducted 2026-07-31; research trail in [history/260731-game-kernel-research.md](../history/260731-game-kernel-research.md). --- ## Candidates ### 1. boardgame.io 0.50.2 (JS/TS) — measured The most direct comparator: a declarative turn-based game engine. - **Data model:** single plain-object `G` (game state) + framework `ctx` (turn/phase bookkeeping). Game defined declaratively: `setup`, `moves`, `phases`, `turn.stages`. - **Mutation:** moves are reducer functions run through Redux + Immer; mutate a draft, framework produces immutable next state and appends to an action **log** (basis for time travel). - **Determinism/replay:** seeded RNG via `random` plugin; log + seed give replay and time travel. Measured: same seed → identical state hash across runs; different seed diverges. ✅ - **Hidden information:** `playerView` projection (e.g. `STRIP_SECRET`) — server strips secret state per player. - **Simultaneous actions:** `activePlayers` stages give simultaneous move windows; no built-in cryptographic commit/reveal — commitment is plain state the server can see (fine for server-authoritative, nothing for peer settings). - **Maturity:** 12.4k GitHub stars, but **inactive** — last npm release 0.50.2 ≈ 4 years ago (Snyk: "maintenance: Inactive"). - **Measured performance** (our harness, synthetic 3-player GROUND-shaped commit/reveal workload, Node v24, this machine `bnt-lap001`): | applied moves | moves/s | elapsed | RSS | |---:|---:|---:|---:| | 5,000 | 1,930 | 2.6 s | 224 MB | | 10,000 | 1,605 | 6.2 s | 229 MB | | 20,000 | 870 | 23.0 s | 271 MB | | 100,000 | did not finish in 300 s | — | — | **Per-move cost grows with history length** (log accumulation + state pipeline): throughput halves as move count doubles — superlinear total cost. This is architectural (unbounded redux log per client), not a tuning artifact. - **Weight:** 120 transitive npm packages, 37 MB `node_modules`, core package 3.9 MB. ### 2. Tabletop Simulator scripting model (Lua) — cited The dominant commercial virtual tabletop; reference for *tabletop semantics*, not a rules kernel. - **Data model:** none authoritative — game state *is* the physical scene; Lua state serialized as strings into the save JSON (`onSave`/`onLoad`). - **Mutation:** imperative Lua in a Global script + per-object scripts with event hooks; **no move validation or rules engine** — rules are social, physics is primary (sandbox mode in Clay-Borg terms). - **Determinism/replay:** none. Hidden info via hand zones (engine feature, not a projection model). - Valuable as the pattern source for object-attached behavior and hand zones; architecturally the anti-model for an authoritative kernel. ### 3. Rune SDK (JS) — cited Modern (active, 2024–2026) deterministic multiplayer engine for casual web games. - **Data model/mutation:** pure `logic.js` — game state + action functions, statically checked for nondeterminism (mutation escape, `Math.random` patched deterministic). - **Sync:** predict-rollback: all clients + server simulate the same deterministic logic; server authoritative, clients predict. Strongest determinism *discipline* of the candidates — enforced by tooling, not convention. - **Limits:** platform-bound (Rune's hosted app ecosystem), not an embeddable open kernel; no phase/stage framework, hidden-information projection, or event-sourced replay surface comparable to boardgame.io. ### 4. Event-sourcing kernels (Rust `cqrs-es` pattern / EventStoreDB) — cited The general-purpose form of our mutation pipeline (command → validate → events → fold). - Aggregates validate commands and emit events; state is a fold over the append-only log; snapshots bound replay cost. Replay/audit are native. - **Performance (cited/estimated):** in-process Rust event application is memory-bandwidth-bound — order 10⁵–10⁶ small events/s per core is the commonly reported range for fold-style aggregates; dedicated stores (EventStoreDB) sustain tens of thousands of appends/s over the network. No game semantics: phases, visibility, simultaneity all DIY. ### 5. bevy_ecs 0.x (Rust) — cited Archetypal ECS; the world/spatial layer in our architecture, surveyed as a kernel candidate for completeness. - Cache-friendly iteration: millions of entity-component accesses per frame (cited from Bevy's own benches; ns-scale per component access). - No authoritative command/event pipeline, no replay, no hidden-info projection; determinism requires care (system ordering, hash maps). Confirms the ADR-anticipated split: ECS for world representation, **typed aggregates for the semantic kernel** — not a competitor on this capability. --- ## Baselines (benchmark-to-beat) | Dimension | Baseline holder | Metric | Value | Provenance | |---|---|---|---|---| | D1 ease of specification | boardgame.io | LOC to express the synthetic 3p commit/reveal game (declarative object) | ~45 LOC | measured (harness bench.js game def) | | D1 | — (no candidate) | rule-to-scenario traceability (M-D1-COV) | 0 % — none of the candidates link rules to tests | measured/observed | | D2 implementation weight | boardgame.io | transitive deps / install size | 120 pkgs / 37 MB | measured | | D3 throughput | boardgame.io | applied moves/s, 3p workload @5k moves | 1,930 moves/s | measured, bnt-lap001 | | D3 scaling | boardgame.io | throughput @20k vs @5k moves | 0.45× (superlinear cost) | measured, bnt-lap001 | | D3 memory | boardgame.io | RSS @5k moves | 224 MB | measured, bnt-lap001 | | D3 ceiling (adjacent layer) | in-proc event-sourcing (Rust) | events applied/s per core | ~10⁵–10⁶ | cited/estimated — directional, caps our verdict at parity unless we measure a Rust comparator | | D4 optionality | Rune | determinism enforced by tooling | static nondeterminism checks | cited | | D4 | boardgame.io | replaceability of subsystems | plugin API, but JS-ecosystem-locked; no null/reference impl pattern | observed | **Headline benchmark-to-beat for the Clay-Borg kernel (proposed for the ADR):** ≥ 100,000 applied events/s sustained with **flat scaling** (throughput @100k events within 10% of @5k), deterministic replay bit-identical, on the same machine and workload shape as the boardgame.io harness. ## Verdict - **Per dimension:** D1 — boardgame.io's declarative game object is the bar to match; nobody has rule-to-scenario traceability (open surpass lane). D2 — boardgame.io's 120-dep footprint is beatable by an order of magnitude in Rust. D3 — boardgame.io is slow *and* degrades; the honest comparison class is in-proc event sourcing (10⁵–10⁶/s), and our D3 advantage over boardgame.io is partly language choice — the meaningful target is **flat scaling + the 100k/s floor**, not the ×50 headline. D4 — Rune's tooling-enforced determinism is the discipline to assimilate; no candidate offers a null/reference/optimized port pattern. - **What none of them do:** combine deterministic replayable authoritative state, first-class simultaneous commit/reveal with hidden-information projection, flat per-event cost with snapshots, and an embeddable language-portable boundary. That combination is the surpass opportunity. - **Risks in these baselines:** the boardgame.io harness measures the headless *client* pipeline (includes subscription/log overhead — canonical usage, but a bare server-side master could differ); the event-sourcing numbers are cited, not locally measured; TTS and Rune numbers are qualitative. The D3 event-sourcing row is directional and caps related evidence verdicts at parity per MetricsAndScenarios §3.