Asupersync

Spec-first, cancel-correct, capability-secure async for Rust

Quick Install

cargo add asupersync --git https://github.com/Dicklesworthstone/asupersync

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TL;DR

The Problem: Rust's async ecosystem gives you tools but not guarantees. Cancellation silently drops data. Spawned tasks can orphan. Cleanup is best-effort. Testing concurrent code is non-deterministic. You write correct code by convention, and discover bugs in production.

The Solution: Asupersync is an async runtime where correctness is structural, not conventional. Tasks are owned by regions that close to quiescence. Cancellation is a protocol with bounded cleanup. Effects require capabilities. The lab runtime makes concurrency deterministic and replayable.

Why Asupersync?

Guarantee	What It Means
No orphan tasks	Every spawned task is owned by a region; region close waits for all children
Cancel-correctness	Cancellation is request → drain → finalize, never silent data loss
Bounded cleanup	Cleanup budgets are sufficient conditions, not hopes
No silent drops	Two-phase effects (reserve/commit) make data loss impossible for primitives
Deterministic testing	Lab runtime: virtual time, deterministic scheduling, trace replay
Adaptive preemption fairness	Deterministic EXP3/Hedge policy tunes cancel streak limits with regret-bounded updates
Drain progress certificates	Variance-adaptive Azuma/Freedman bounds classify drain phase and confidence to quiescence
Spectral early warnings	Wait-graph spectral monitor combines conformal bounds and anytime-valid evidence
Capability security	All effects flow through explicit Cx; no ambient authority

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Quick Example

use asupersync::{Cx,Scope,Outcome,Budget};// Structured concurrency: scope guarantees quiescenceasyncfnmain_task(cx:&mutCx) -> Outcome<(),Error>{
cx.region(|scope| async{// Spawn owned tasks - they cannot orphan
scope.spawn(worker_a);
scope.spawn(worker_b);// When scope exits: waits for BOTH tasks,// runs finalizers, resolves obligations}).await;// Guaranteed: nothing from inside is still runningOutcome::ok(())}// Cancellation is a protocol, not a flagasyncfnworker_a(cx:&mutCx) -> Outcome<(),Error>{loop{// Checkpoint for cancellation - explicit, not implicit
cx.checkpoint()?;// Two-phase send: cancel-safelet permit = tx.reserve(cx).await?;// Can cancel here
permit.send(message);// Linear: must happen}}// Lab runtime: deterministic testing#[test]fntest_cancellation_is_bounded(){let lab = LabRuntime::new(LabConfig::default().seed(42));
lab.run(|cx| async{// Same seed = same execution = reproducible bugs
cx.region(|scope| async{
scope.spawn(task_under_test);}).await});// Oracles verify invariantsassert!(lab.obligation_leak_oracle().is_ok());assert!(lab.quiescence_oracle().is_ok());}

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Design Philosophy

1. Structured Concurrency by Construction

Tasks don't float free. Every task is owned by a region. Regions form a tree. When a region closes, it guarantees all children are complete, all finalizers have run, all obligations are resolved. This is the "no orphans" invariant, enforced by the type system and runtime rather than by discipline.

// Typical executors: what happens when this scope exits?spawn(async{/* orphaned? cancelled? who knows */});// Asupersync: scope guarantees quiescence
scope.region(|sub| async{
sub.spawn(task_a);
sub.spawn(task_b);}).await;// ← guaranteed: nothing from inside is still running

2. Cancellation as a First-Class Protocol

Cancellation operates as a multi-phase protocol, not a silent drop:

Running → CancelRequested → Cancelling → Finalizing → Completed(Cancelled)
↓ ↓ ↓
(bounded) (cleanup) (finalizers)

• Request: propagates down the tree
• Drain: tasks run to cleanup points (bounded by budgets)
• Finalize: finalizers run (masked, budgeted)
• Complete: outcome is Cancelled(reason)

Primitives publish cancellation responsiveness bounds. Budgets are sufficient conditions for completion.

Cancellation progress is continuously certifiable. ProgressCertificate tracks potential descent, classifies the current drain regime (warmup, rapid_drain, slow_tail, stalled, quiescent), and emits variance-adaptive concentration bounds (Freedman with Azuma as a conservative baseline). This turns "is shutdown actually converging?" into a measurable claim instead of a guess.

3. Two-Phase Effects Prevent Data Loss

Anywhere cancellation could lose data, Asupersync uses reserve/commit:

let permit = tx.reserve(cx).await?;// ← cancel-safe: nothing committed yet
permit.send(message);// ← linear: must happen or abort

Dropping a permit aborts cleanly. Message never partially sent.

4. Capability Security (No Ambient Authority)

All effects flow through explicit capability tokens:

asyncfnmy_task(cx:&mutCx){
cx.spawn(...);// ← need spawn capability
cx.sleep_until(...);// ← need time capability
cx.trace(...);// ← need trace capability}

Swap Cx to change interpretation: production vs. lab vs. distributed.

5. Deterministic Testing is Default

The lab runtime provides:

• Virtual time: sleeps complete instantly, time is controlled
• Deterministic scheduling: same seed → same execution
• Trace capture/replay: debug production issues locally
• Schedule exploration: DPOR-class coverage of interleavings

Concurrency bugs become reproducible test failures.

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"Alien Artifact" Quality Algorithms

Asupersync deliberately uses mathematically rigorous machinery where it buys real correctness, determinism, and debuggability. The intent is to make concurrency properties structural, so both humans and coding agents can trust the system under cancellation, failures, and schedule perturbations.

Formal Semantics (and a Lean Skeleton) for the Runtime Kernel

The runtime design is backed by a small-step operational semantics (asupersync_v4_formal_semantics.md) with an accompanying Lean mechanization scaffold (formal/lean/Asupersync.lean).

One example: the cancellation/cleanup budget composes as a semiring-like object (componentwise min, with priority as max), which makes "who constrains whom?" algebraic instead of ad-hoc:

combine(b1, b2) =
deadline := min(b1.deadline, b2.deadline)
pollQuota := min(b1.pollQuota, b2.pollQuota)
costQuota := min(b1.costQuota, b2.costQuota)
priority := max(b1.priority, b2.priority)

This is the kind of structure that lets us reason about cancellation protocols and bounded cleanup with proof-friendly, compositional rules.

Regret-Bounded Adaptive Cancel Preemption (Deterministic EXP3/Hedge)

Scheduler preemption is not fixed to one static cancel streak limit. Workers can run a deterministic EXP3/Hedge-style policy over a bounded set of candidate limits (for example, {4, 8, 16, 32}), then update weights at fixed epoch boundaries from observed reward (Lyapunov decrease + fairness + deadline pressure):

p_t(a) = (1 - γ) * w_t(a)/Σ_b w_t(b) + γ/K
w_{t+1}(a) = w_t(a) * exp((γ / K) * r̂_t(a))

with importance-weighted reward r̂_t(a_t) = r_t / p_t(a_t) for the selected action.

Why it helps: cancel-heavy workloads and latency-heavy workloads need different preemption pressure. This controller adapts online while preserving deterministic replay semantics and bounded starvation envelopes.

Variance-Adaptive Drain Certificates (Azuma + Freedman + Phase Classification)

Cancellation drain progress is monitored as a martingale-style certificate over potential deltas. The runtime reports both a worst-case Azuma bound and a variance-adaptive Freedman bound:

P(M_t - M_0 ≥ x) ≤ exp(-x² / (2(V_t + c x / 3)))

where V_t is predictable variation and c bounds one-step increments.

The same monitor classifies operational drain regime (warmup, rapid_drain, slow_tail, stalled, quiescent) so operators can distinguish "normal long tail" from "true stall".

Why it helps: shutdown and fail-fast behavior can be audited with explicit confidence numbers and phase labels, instead of timeout heuristics.

Spectral Wait-Graph Early Warning (Cheeger/Fiedler + Conformal + E-Process)

Asupersync treats the task wait-for graph as a dynamic signal. The monitor tracks the Fiedler trajectory (algebraic connectivity), spectral gap/radius, and a nonparametric indicator stack (autocorrelation, variance ratio, flicker, skewness, Kendall tau, Spearman rho, Hoeffding's D, distance correlation), then calibrates forward risk with split conformal bounds and an anytime-valid deterioration e-process.

Why it helps: structural degradation is detected before hard deadlock/disconnect events, with calibrated thresholds and continuously valid evidence rather than brittle one-off alarms.

DPOR-Style Schedule Exploration (Mazurkiewicz Traces, Foata Fingerprints)

The Lab runtime includes a DPOR-style schedule explorer (src/lab/explorer.rs) that treats executions as traces modulo commutation of independent events (Mazurkiewicz equivalence). Instead of "run it 10,000 times and pray", it tracks coverage by equivalence class fingerprints and can prioritize exploration based on trace topology.

Result: deterministic, replayable concurrency debugging with coverage semantics rather than vibes.

Anytime-Valid Invariant Monitoring via e-processes

Oracles can run repeatedly during an execution without invalidating significance, using e-processes (src/lab/oracle/eprocess.rs). The key property is Ville's inequality (anytime validity):

P_H0(∃ t : E_t ≥ 1/α) ≤ α

So you can "peek" after every scheduling step and still control type-I error, which is exactly what you want in a deterministic scheduler + oracle setting.

Distribution-Free Conformal Calibration for Lab Metrics

For lab metrics that benefit from calibrated prediction sets, Asupersync uses split conformal calibration (src/lab/conformal.rs) with finite-sample, distribution-free guarantees (under exchangeability):

P(Y ∈ C(X)) ≥ 1 − α

This is used to keep alerting and invariant diagnostics robust without baking in fragile distributional assumptions.

Explainable Evidence Ledgers (Bayes Factors, Galaxy-Brain Diagnostics)

When a run violates an invariant (or conspicuously does not), Asupersync can produce a structured evidence ledger (src/lab/oracle/evidence.rs) using Bayes factors and log-likelihood contributions. This enables agent-friendly debugging: equations, substitutions, and one-line intuitions, so you can see exactly why the system believes "task leak" (or "clean close") is happening.

Deterministic Algorithms in the Hot Path (Not Just in Tests)

Determinism is treated as a first-class algorithmic constraint across the codebase:

• A deterministic virtual time wheel (src/lab/virtual_time_wheel.rs) with explicit tie-breaking.
• Deterministic consistent hashing (src/distributed/consistent_hash.rs) for stable assignment without iteration-order landmines.
• Trace canonicalization and race analysis hooks integrated into the lab runtime (src/lab/runtime.rs, src/trace/dpor).

"Same seed, same behavior" holds end-to-end, not just for a demo scheduler.

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How Asupersync Compares

Feature	Asupersync	async-std	smol
Structured concurrency	✅ Enforced	❌ Manual	❌ Manual
Cancel-correctness	✅ Protocol	⚠️ Drop-based	⚠️ Drop-based
No orphan tasks	✅ Guaranteed	❌ spawn detaches	❌ spawn detaches
Bounded cleanup	✅ Budgeted	❌ Best-effort	❌ Best-effort
Deterministic testing	✅ Built-in	❌ External tools	❌ External tools
Obligation tracking	✅ Linear tokens	❌ None	❌ None
Ecosystem	✅ Tokio-scale built-in surface (runtime, net, HTTP/1.1+H2, TLS, WebSocket, gRPC, DB, distributed)	⚠️ Medium	⚠️ Small
Maturity	✅ Feature-complete runtime surface, actively hardened	✅ Production	✅ Production

When to use Asupersync:

• Systems that want a broad, integrated async stack without pulling in Tokio
• Systems where cancel-correctness is non-negotiable (financial, medical, infrastructure)
• Projects that need deterministic concurrency testing
• Distributed systems with structured shutdown requirements

When to consider alternatives:

• You need strict drop-in compatibility with libraries that are hard-wired to Tokio runtime traits
• Rapid prototyping where correctness guarantees aren't yet critical

Tokio Ecosystem Coverage Map

The table above compares runtimes. This section compares ecosystem surface area. It maps common Tokio ecosystem crates to the corresponding Asupersync modules.

Ecosystem Area	Typical Tokio Crates	Asupersync Surface	Parity status	Maturity	Determinism	Interop friction
Core runtime + task execution	tokio	src/runtime/, src/cx/, src/record/	Built-in	Mature	Lab-strong	High
Structured concurrency + cancellation protocol	usually ad hoc on Tokio	Built into Cx, regions, obligations (src/cx/, src/cancel/, src/obligation/)	Built-in	Mature	Strong	High
Channels	tokio::sync::{mpsc, oneshot, broadcast, watch}	src/channel/{mpsc,oneshot,broadcast,watch}.rs	Built-in	Mature	Lab-strong	Medium
Sync primitives	tokio::sync::{Mutex,RwLock,Semaphore,Notify,Barrier,OnceCell}	src/sync/	Built-in	Mature	Lab-strong	Medium
Time and timers	tokio::time	src/time/, src/runtime/timer*, src/lab/virtual_time_wheel.rs	Built-in	Mature	Lab-strong	Medium
Async I/O traits and extensions	tokio::io, tokio-util::io	src/io/	Built-in	Active	Mixed	Medium
Codec/framing layer	tokio-util::codec	src/codec/	Built-in	Active	Mixed	Medium
Byte buffers	bytes	src/bytes/	Built-in	Mature	N/A	Low
Reactor backends	Tokio + Mio internals	src/runtime/reactor/{epoll,kqueue,windows,lab}.rs (+ io_uring feature on Linux)	Built-in	Active	Mixed	Medium
TCP/UDP/Unix sockets	tokio::net	src/net/tcp/, src/net/udp.rs, src/net/unix/	Built-in	Active	Mixed	Medium
DNS resolution	trust-dns, hickory, custom stacks	src/net/dns/	Built-in	Active	Mixed	Medium
TLS	tokio-rustls, native-tls	src/tls/ (tls, tls-native-roots, tls-webpki-roots)	Feature-gated	Active	Mixed	Medium
WebSocket	tokio-tungstenite	src/net/websocket/	Built-in	Active	Mixed	Medium
HTTP stack (HTTP/1.1 + HTTP/2)	hyper, h2, http-body, hyper-util	src/http/h1/, src/http/h2/, src/http/body.rs, src/http/pool.rs	Built-in	Active	Mixed	Medium
QUIC + HTTP/3	quinn, h3, h3-quinn	src/net/quic_core/, src/net/quic_native/, src/http/h3_native.rs (native feature surfaces exposed via quic/http3; legacy wrappers remain parked under quic-compat/http3-compat)	In progress	Active	Mixed	High
Web framework	axum, warp, tower-http	src/web/, src/service/, src/server/	In progress	Active	Mixed	Medium
gRPC	tonic + prost + tower + hyper	src/grpc/	Built-in	Active	Mixed	Medium
Database clients	tokio-postgres, mysql_async, sqlx	src/database/{postgres,mysql,sqlite}.rs	Feature-gated	Active	Mixed	Medium
Messaging clients	async Redis/NATS/Kafka crates	src/messaging/{redis,nats,kafka}.rs	In progress	Early	Mixed	Medium
Service/middleware stack	tower, tower-layer, tower-service	src/service/ + optional tower adapter feature	Built-in	Active	Lab-strong	Low
Filesystem APIs	tokio::fs	src/fs/	In progress	Early	Mixed	Medium
Process management	tokio::process	src/process.rs	Built-in	Active	Mixed	Medium
Signals	tokio::signal	src/signal/	Built-in	Active	Mixed	Medium
Streams and adapters	tokio-stream, futures-util::stream	src/stream/	Built-in	Active	Lab-strong	Low
Observability	tracing, metrics, opentelemetry	src/observability/, src/tracing_compat.rs	Built-in + feature-gated integrations	Active	Mixed	Low
Deterministic concurrency testing	loom, tokio-test, external harnesses	src/lab/, frankenlab/, optional loom-tests feature	Built-in	Mature	Strong	Low
Tokio-locked third-party crates	crates that require Tokio runtime traits directly	boundary adapters via service/runtime integration points	Adapter needed	N/A	N/A	High

This map is about capability coverage, not API compatibility. Asupersync intentionally uses a different model centered on Cx, regions, explicit cancellation, and deterministic replay.

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Installation

From Git (Recommended)

# Add to Cargo.toml
cargo add asupersync --git https://github.com/Dicklesworthstone/asupersync
# Or manually add:# [dependencies]# asupersync = { git = "https://github.com/Dicklesworthstone/asupersync" }

From Source

git clone https://github.com/Dicklesworthstone/asupersync.git
cd asupersync
cargo build --release

Minimum Supported Rust Version

Asupersync uses Rust Edition 2024 and tracks the pinned nightly toolchain in rust-toolchain.toml.

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Core Types Reference

Outcome — Four-Valued Result

pubenumOutcome<T,E>{Ok(T),// SuccessErr(E),// Application errorCancelled(CancelReason),// External cancellationPanicked(PanicPayload),// Task panicked}// Severity lattice: Ok < Err < Cancelled < Panicked// HTTP mapping: Ok→200, Err→4xx/5xx, Cancelled→499, Panicked→500

Budget — Resource Constraints

pubstructBudget{pubdeadline:Option<Time>,// Absolute deadlinepubpoll_quota:u32,// Max poll callspubcost_quota:Option<u64>,// Abstract cost unitspubpriority:u8,// Scheduling priority (0-255)}// Semiring: meet(a, b) = tighter constraint winslet effective = outer_budget.meet(inner_budget);

CancelReason — Structured Context

pubenumCancelKind{User,// Explicit cancellationTimeout,// Deadline exceededFailFast,// Sibling failedRaceLost,// Lost a raceParentCancelled,// Parent region cancelledShutdown,// Runtime shutdown}// Severity: User < Timeout < FailFast < ParentCancelled < Shutdown// Cleanup budgets scale inversely with severity

Cx — Capability Context

pubstructCx{/* ... */}implCx{pubfnspawn<F>(&self,f:F) -> TaskHandle;pubfncheckpoint(&self) -> Result<(),Cancelled>;pubfnmask(&self) -> MaskGuard;// Defer cancellationpubfntrace(&self,event:TraceEvent);pubfnbudget(&self) -> Budget;pubfnis_cancel_requested(&self) -> bool;}

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Architecture

┌─────────────────────────────────────────────────────────────────────────────┐
│ EXECUTION TIERS │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │
│ │ FIBERS │ │ TASKS │ │ ACTORS │ │ REMOTE │ │
│ │ │ │ │ │ │ │ │ │
│ │• Borrow-safe │ │• Parallel │ │• Long-lived │ │• Named compute│ │
│ │• Same-thread │ │• Send │ │• Supervised │ │• Leases │ │
│ │• Region-pinned│ │• Work-stealing│ │• Region-owned │ │• Idempotent │ │
│ │• Cancel-safe │ │• Region-heap │ │• Mailbox │ │• Saga cleanup │ │
│ └───────────────┘ └───────────────┘ └───────────────┘ └───────────────┘ │
│ │ │ │ │ │
│ └──────────────────┴────────┬─────────┴──────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ REGION TREE │ │
│ │ │ │
│ │ Root Region ──┬── Child Region ──┬── Task │ │
│ │ │ ├── Task │ │
│ │ │ └── Subregion ── Task │ │
│ │ └── Child Region ── Actor │ │
│ │ │ │
│ │ Invariant: close(region) → quiescence(all descendants) │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ OBLIGATION REGISTRY │ │
│ │ │ │
│ │ SendPermit ──→ send() or abort() │ │
│ │ Ack ──→ commit() or nack() │ │
│ │ Lease ──→ renew() or expire() │ │
│ │ IoOp ──→ complete() or cancel() │ │
│ │ │ │
│ │ Invariant: region_close requires all obligations resolved │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ SCHEDULER │ │
│ │ │ │
│ │ Cancel Lane ──→ Timed Lane (EDF) ──→ Ready Lane │ │
│ │ ↑ │ │
│ │ (priority) Lyapunov-guided: V(Σ) must decrease │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘

Scheduler Priority Lanes

Lane	Purpose	Priority
Cancel Lane	Tasks in cancellation states	200-255 (highest)
Timed Lane	Deadline-driven tasks (EDF)	Based on deadline
Ready Lane	Normal runnable tasks	Default priority

Scheduler behavior is intentionally explicit:

• Cancel preemption is bounded, not unbounded. With the default cancel_streak_limit=16, ready or timed work gets a dispatch slot within limit + 1 steps per worker (src/runtime/scheduler/three_lane.rs).
• During DrainObligations and DrainRegions, the effective bound is temporarily widened to 2 * cancel_streak_limit to finish cleanup without starving everything else (src/runtime/scheduler/three_lane.rs).
• Workers track fairness telemetry (fairness_yields, max_cancel_streak) so starvation claims can be checked against runtime counters, not guesses (src/runtime/scheduler/three_lane.rs).
• Local dispatch uses single-lock multi-lane pops (try_local_any_lane and pop_any_lane_with_hint) to reduce lock traffic on the hot path while keeping lane ordering rules intact (src/runtime/scheduler/three_lane.rs).
• An optional Lyapunov governor can steer lane ordering from periodic runtime snapshots. It is off by default, and when enabled it runs at a configurable interval (governor_interval, default 32) (src/runtime/config.rs, src/runtime/builder.rs, src/runtime/scheduler/three_lane.rs).
• Adaptive cancel preemption is available as a deterministic no-regret online controller: workers run an EXP3/Hedge-style policy over candidate cancel-streak limits, updating from reward signals that blend Lyapunov decrease, fairness pressure, and deadline pressure (src/runtime/scheduler/three_lane.rs, src/runtime/config.rs, src/runtime/builder.rs).
• When governor mode is enabled, scheduling suggestions can be modulated by a decision contract with Bayesian posterior updates over healthy, congested, unstable, and partitioned runtime states (src/runtime/scheduler/decision_contract.rs, src/runtime/scheduler/three_lane.rs).
• Dispatch follows an explicit multi-phase path: global lanes, fast ready paths, one local-lane lock acquisition, steal attempts, then fallback cancel handling (src/runtime/scheduler/three_lane.rs).
• Worker wakeups are coordinated through round-robin targeted unparks, with a bitmask fast path when worker count is a power of two (src/runtime/scheduler/three_lane.rs).
• I/O polling uses a leader/follower turn: the worker that acquires the I/O driver lock runs the reactor turn while peers continue scheduling (src/runtime/scheduler/three_lane.rs).
• Local !Send tasks are pinned to owner workers and routed through non-stealable queues; steal paths explicitly reject moving them across workers (src/runtime/scheduler/three_lane.rs, src/runtime/scheduler/local_queue.rs).
• Local queue discipline is asymmetric on purpose: owner operations are LIFO for cache locality, while thief operations are FIFO to keep stolen work older and reduce starvation pressure (src/runtime/scheduler/local_queue.rs).
• Idle-worker parking uses a permit-style Parker and explicit queue rechecks after wakeups, which closes lost-wakeup races between work injection and parking (src/runtime/scheduler/worker.rs, src/runtime/scheduler/three_lane.rs).

Sharded Runtime State and Lock Discipline

Runtime state is split into independently locked shards so hot-path polling can proceed without serializing every region or obligation mutation.

• Shard A (tasks): task table, stored futures, intrusive queue links.
• Shard B (regions): region ownership tree and state transitions.
• Shard C (obligations): permit/ack/lease lifecycle and leak tracking.
• Shard D (instrumentation): trace and metrics surfaces.
• Shard E (config): immutable runtime config.

Multi-shard operations use ShardGuard with canonical acquisition order E -> D -> B -> A -> C, and debug checks enforce that order to prevent deadlocks (src/runtime/sharded_state.rs). Shard locks are ContendedMutex instances, and optional lock-metrics instrumentation can measure wait/hold behavior (src/sync/contended_mutex.rs).

Region Heap Handles and Quiescent Reclamation

Region memory uses stable handles (HeapIndex) with slot index, generation, and type tag metadata instead of exposing raw allocation addresses.

• Generation increments on slot reuse, so stale handles fail closed and ABA-style reuse bugs are blocked (src/runtime/region_heap.rs).
• Reuse order is deterministic for identical allocation/deallocation sequences, which keeps trace behavior stable across runs (src/runtime/region_heap.rs).
• Heap reclamation is wired to region close/quiescence, not opportunistic frees, and stats track live vs. reclaimed objects for runtime auditing (src/runtime/region_heap.rs).

Runtime Control Surfaces: Causal Time, Cancel Attribution, and Deadline Signals

Asupersync exposes runtime controls that are usually hidden behind ad hoc instrumentation. These controls are wired into scheduler and trace behavior directly.

Control	API	Runtime Behavior
Logical clock mode	RuntimeBuilder::logical_clock_mode(...)	Select Lamport, Vector, or Hybrid logical clocks for causal ordering; defaults are chosen from runtime context and carried into event timelines (src/runtime/config.rs, src/trace/distributed/vclock.rs, src/runtime/state.rs)
Cancel attribution bounds	RuntimeBuilder::cancel_attribution_config(...)	Bound cancellation cause-chain depth and memory while preserving root-cause lineage and explicit truncation metadata when limits are hit (src/types/cancel.rs, src/runtime/state.rs)
Deadline monitor	RuntimeBuilder::deadline_monitoring(...)	Run a background monitor with configurable check cadence, warning thresholds, adaptive history percentiles, and custom warning callbacks (src/runtime/deadline_monitor.rs, src/runtime/builder.rs)

• Deadline checks are logical-time aware and fall back to wall-clock progression when logical time is stable, so stalled-task warnings work in both lab and production-style runs (src/runtime/deadline_monitor.rs).
• Warning emission is per-task deduplicated until task removal, so deadline diagnostics stay high-signal under repeated scans (src/runtime/deadline_monitor.rs).
• Deadline warnings carry the most recent checkpoint message when available, which makes stalled-task alerts actionable without digging through a full trace first (src/runtime/deadline_monitor.rs).

How We Made It Fast

This runtime got fast through many small, verified runtime changes by the project owner and collaborating coding agents. The method stayed consistent: profile the hot paths, remove one source of contention or allocation at a time, then keep cancellation and determinism guarantees intact.

• Scheduler lock traffic: dispatch uses a multi-phase path, and local cancel/timed/ready checks run under one local lock acquisition instead of repeated lock round-trips (src/runtime/scheduler/three_lane.rs).
• Hot-path task isolation: scheduler queues can run against a dedicated sharded TaskTable, so push/pop/steal paths avoid full runtime-state lock pressure (src/runtime/task_table.rs, src/runtime/scheduler/local_queue.rs, src/runtime/scheduler/three_lane.rs).
• Targeted wake coordination: worker wakeups go through a coordinator with round-robin unparks and a power-of-two bitmask fast path, so wake selection avoids heavier arithmetic in steady state (src/runtime/scheduler/three_lane.rs).
• Centralized wake dedup: scheduling paths route through wake_state.notify() with an explicit Idle -> Polling -> Notified state machine, so wakes that arrive during poll are coalesced once instead of double-enqueueing (src/record/task.rs, src/runtime/scheduler/three_lane.rs, src/runtime/scheduler/worker.rs).
• Cheaper wake bookkeeping: waiter registration paths use Waker::will_wake guards to skip redundant clones and refresh only when the executor context actually changes (src/transport/sink.rs, src/transport/mock.rs).
• Lost-wakeup hardening without busy spin: parking uses permit-style semantics, and queue/capacity rechecks close races between waiter registration and wakeups (src/runtime/scheduler/worker.rs, src/runtime/scheduler/three_lane.rs, src/transport/sink.rs).
• Allocation pressure reduction: hot paths moved away from per-dispatch temporary Vec usage toward SmallVec and pre-sized structures (src/runtime/scheduler/three_lane.rs, src/transport/router.rs, src/transport/aggregator.rs).
• Intrusive queue hot paths: local ready/cancel queues store links directly in TaskRecord with queue-tag membership checks, so owner pop and thief steal stay O(1) without per-operation node allocation (src/runtime/scheduler/intrusive.rs, src/runtime/scheduler/local_queue.rs).
• Lower mutex overhead across the stack: runtime, scheduler, I/O, lab, networking, and transport internals were migrated to parking_lot primitives where it improves lock-path cost (src/runtime/*, src/transport/*, src/lab/*).
• Atomic and counter-path tuning: the global injector increments timed counters before heap insert, uses saturating decrements on pop, and keeps a cached earliest-deadline fast path so workers can usually skip timed-lane mutex acquisition (src/runtime/scheduler/global_injector.rs).
• Steal-path locality shortcuts: local queues track whether any pinned local tasks are present; when none are present, stealers take a no-branch non-local path, and when locals do exist they are skipped/restored with SmallVec to keep the common path allocation-free (src/runtime/scheduler/local_queue.rs, src/runtime/scheduler/intrusive.rs).
• Backpressure without silent drops: global ready-queue limits emit capacity warnings while still scheduling work, preserving structured-concurrency guarantees instead of dropping tasks (src/runtime/scheduler/three_lane.rs, src/runtime/config.rs).
• Reactor fast paths: I/O registration rearm paths cache waker state, and stale token/fd cleanup is explicit, which keeps event loops moving under churn (src/runtime/io_driver.rs, src/runtime/reactor/*).
• Timer wheel tuned for real cancellation workloads: timer cancel is generation-based O(1), long deadlines spill into overflow and are promoted back in range, and coalescing windows can batch nearby wakeups with minimum-group gating (src/time/wheel.rs, src/time/driver.rs).
• Panic containment on worker threads: task polling is guarded so panics are converted into terminal Outcome::Panicked, dependents/finalizers are still driven, and one bad task does not take down a worker lane (src/runtime/scheduler/three_lane.rs, src/runtime/builder.rs).
• Timer behavior measured where it matters: the timer benchmark corpus includes direct wheel-vs-BTreeMap/BinaryHeap comparisons, and the documented 10K corpus records a 2.67x cancel-path advantage over BTreeMap (benches/timer_wheel.rs).
• Stable memory handles with deterministic reuse: region-heap generation indices prevent ABA-style stale-handle reuse while preserving deterministic allocation/reuse patterns (src/runtime/region_heap.rs).
• Continuous measurement: the repository carries dedicated benchmark surfaces for scheduler, reactor, timer wheel, cancel/drain, and tracing overhead (benches/scheduler_benchmark.rs, benches/reactor_benchmark.rs, benches/timer_wheel.rs, benches/cancel_drain_bench.rs, benches/tracing_overhead.rs).

---

Networking & Protocol Stack

Asupersync ships a cancel-safe networking stack from raw sockets through application protocols. Every layer participates in structured concurrency: reads and writes respect region budgets, cancellation drains connections cleanly, and the lab runtime can substitute virtual TCP for deterministic network testing.

Reactor and I/O paths are also hardened for long-lived production behavior:

• Registrations are RAII-backed and deregistration treats NotFound as already-cleaned state, so cancellation/drop races do not leak bookkeeping (src/runtime/io_driver.rs, src/runtime/reactor/registration.rs).
• Token slabs are generation-tagged, which blocks stale-token wakeups after slot reuse (src/runtime/reactor/token.rs).
• The I/O driver records unknown_tokens instead of panicking when stale/backend events appear, so diagnostics stay available under fault conditions (src/runtime/io_driver.rs).
• epoll interest mapping supports edge-triggered and edge-oneshot modes plus explicit PRIORITY/HUP/ERROR propagation, so readiness semantics are carried with fewer implicit assumptions (src/runtime/reactor/epoll.rs).
• epoll paths explicitly clean stale fd/token mappings on ENOENT/closed-fd conditions, including fd-reuse edge cases (src/runtime/reactor/epoll.rs).
• io_uring poll handles timeout expiry (ETIME) as a timeout condition, not an operational failure, and ignores stale completions for deregistered tokens (src/runtime/reactor/io_uring.rs).

TCP

src/net/tcp/ provides TcpStream, TcpListener, and split reader/writer halves. Connections are registered with the I/O reactor (epoll or io_uring) and use oneshot waker semantics: the reactor disarms interest after each readiness event, and the stream re-arms explicitly. This avoids spurious wakes at the cost of a set_interest call per poll cycle, which benchmarks show is negligible compared to syscall overhead.

A VirtualTcp implementation (src/net/tcp/virtual_tcp.rs) provides a fully in-memory TCP abstraction for lab-runtime tests. Same API surface, deterministic behavior, no kernel sockets.

HTTP/1.1 and HTTP/2

src/http/h1/ implements HTTP/1.1 with chunked transfer encoding, connection keep-alive, and streaming request/response bodies. src/http/h2/ implements HTTP/2 frame parsing, HPACK header compression, flow control, and stream multiplexing over a single connection.

Both layers integrate with connection pooling (src/http/pool.rs) and optional response compression (src/http/compress.rs).

WebSocket

src/net/websocket/ implements RFC 6455: handshake, binary/text frames, ping/pong, and close frames with status codes. The split reader/writer model allows concurrent send and receive within the same region.

TLS

src/tls/ wraps rustls for TLS 1.2/1.3 with three feature flags:

Flag	Root Certs
tls	Bring your own
tls-native-roots	OS trust store
tls-webpki-roots	Mozilla's WebPKI bundle

DNS and UDP

src/net/dns/ provides async DNS resolution with address-family selection. src/net/udp.rs provides async UDP sockets with send/receive and cancellation safety.

Transport Routing and Multipath Delivery

src/transport/ covers runtime-level delivery behavior above raw sockets and below protocol clients:

• router.rs tracks endpoint health and routing state with atomics (EndpointState, connection counters, failure counters) and uses RAII guards for active connection/dispatch accounting, including cancel/panic paths.
• aggregator.rs handles multipath symbol intake with dedup windows, reorder handling, and per-path statistics for loss/duplicate tracking.
• sink.rs and stream.rs use queued waiters with atomic flags and explicit wakeup bookkeeping to avoid lost-wakeup edge cases in bounded channel transport.
• sink.rs deduplicates waiter updates with Waker::will_wake checks and re-checks capacity after waiter registration, which closes the capacity-check/registration lost-wakeup race (src/transport/sink.rs).
• Shared channel close paths wake both send and receive waiters, so shutdown does not strand pending channel operations (src/transport/mod.rs).

---

Database Integration

Asupersync includes async clients for three databases, each respecting structured concurrency and cancellation.

Database	Location	Wire Protocol	Auth
SQLite	src/database/sqlite.rs	Blocking pool bridge	N/A
PostgreSQL	src/database/postgres.rs	Binary protocol v3	SCRAM-SHA-256
MySQL	src/database/mysql.rs	MySQL wire protocol	Native + caching_sha2

All three support prepared statements, transactions, and connection reuse. SQLite operations run on the blocking thread pool (since rusqlite is synchronous) with cancel-safe wrappers that respect region deadlines. PostgreSQL and MySQL implement their wire protocols directly over TcpStream, avoiding external driver dependencies.

Blocking Pool Safety Semantics

src/runtime/blocking_pool.rs enforces several invariants that matter under cancellation and panic-heavy workloads:

• Thread expansion only happens when pending work exists and all active workers are busy.
• Idle retirement uses an atomic claim step that cannot retire below min_threads.
• Panicking blocking tasks are wrapped so completion signaling and busy-thread counters are still balanced.
• Failed thread spawns roll back active-thread accounting immediately.

---

Remote Runtime and Distributed Coordination

Asupersync's distributed runtime primitives are designed around the same invariants as local execution: explicit ownership, explicit cancellation, and deterministic state transitions.

Primitive	Location	Runtime Behavior
Named remote spawn	src/remote.rs	spawn_remote executes named computations (no closure shipping) under RemoteCap
Lease obligations	src/remote.rs	Leases are obligation-backed and participate in region close/quiescence
Idempotency store	src/remote.rs	Deduplicates spawn retries with TTL-bounded records and conflict detection
Session-typed protocol	src/remote.rs	Origin/remote state machines validate legal spawn/ack/cancel/result/renewal transitions
Logical-time envelopes	src/remote.rs	Protocol messages carry logical clock metadata for causal correlation
Saga compensations	src/remote.rs	Forward steps and compensations are tracked as a structured rollback flow

The transport surface is deliberately separated from protocol state machines, so message semantics can be tested independently of network backend details.

---

Channels and Synchronization Primitives

Channels

Channel	Location	Pattern	Cancel-Safe
MPSC	src/channel/mpsc.rs	Multi-producer, single-consumer	Two-phase send (reserve/commit)
Oneshot	src/channel/oneshot.rs	Single send, single receive	Two-phase send
Broadcast	src/channel/broadcast.rs	Fan-out to subscribers	Waiter cleanup on drop
Watch	src/channel/watch.rs	Last-value multicast	Always-current read
Session	src/channel/session.rs	Typed RPC with reply obligation	Reply is a linear resource

The two-phase pattern (reserve a permit, then commit the send) is central to cancel-correctness. A reserved-but-uncommitted permit aborts cleanly on cancellation. A committed send is guaranteed delivered. No half-sent messages.

Synchronization

Primitive	Location	Notes
Mutex	src/sync/mutex.rs	Fair, cancel-safe, tracks contention
RwLock	src/sync/rwlock.rs	Writer preference with reader batching
Semaphore	src/sync/semaphore.rs	Counting, with permit-as-obligation model
Barrier	src/sync/barrier.rs	N-way synchronization point
Notify	src/sync/notify.rs	One-time or multi-waiter notification
OnceLock	src/sync/once_cell.rs	Async one-time initialization
ContendedMutex	src/sync/contended_mutex.rs	Mutex with contention metrics
Pool	src/sync/pool.rs	Object pool with per-thread caches

All primitives are deterministic under the lab runtime and participate in futurelock detection.

---

Concurrency Combinators

Beyond join, race, and timeout, the combinator library includes patterns for distributed systems and resilience:

Combinator	Location	Purpose
quorum	src/combinator/quorum.rs	M-of-N completion for consensus patterns
hedge	src/combinator/hedge.rs	Start backup after delay, first response wins
first_ok	src/combinator/first_ok.rs	Try operations sequentially until one succeeds
pipeline	src/combinator/pipeline.rs	Staged transformations with backpressure
map_reduce	src/combinator/map_reduce.rs	Parallel map + monoid reduction
circuit_breaker	src/combinator/circuit_breaker.rs	Failure detection, open/half-open/closed states
bulkhead	src/combinator/bulkhead.rs	Concurrency isolation (bounded parallelism)
rate_limit	src/combinator/rate_limit.rs	Token bucket throughput control
bracket	src/combinator/bracket.rs	Acquire/use/release with guaranteed cleanup
retry	src/combinator/retry.rs	Exponential backoff, budget-aware

Every combinator is cancel-safe. Losers drain after races. Outcomes aggregate via the severity lattice. An explicit law sheet (src/combinator/laws.rs) documents algebraic properties (associativity, commutativity, distributivity) and a rewrite engine (src/plan/rewrite.rs) can optimize combinator DAGs while preserving cancel/drain/quiescence invariants.

---

RaptorQ Fountain Coding

src/raptorq/ implements RFC 6330 systematic RaptorQ codes, a fountain code where any K-of-N encoded symbols suffice to recover the original K source symbols. This underpins Asupersync's distributed snapshot distribution: region state is encoded, symbols are assigned to replicas via consistent hashing, and recovery requires collecting a quorum of symbols from surviving nodes.

Module	Purpose
rfc6330.rs	Standard-compliant parameter computation
systematic.rs	Systematic encoder/decoder
gf256.rs	GF(2^8) arithmetic (addition, multiplication, inversion)
linalg.rs	Matrix operations over GF(256)
pipeline.rs	Full sender/receiver pipelines with symbol authentication
proof.rs	Decode proof system for verifiable recovery

The implementation is deterministic (no randomness in lab mode) and integrates with the security layer (src/security/) for per-symbol authentication tags, preventing Byzantine symbol injection.

On the decode side, the runtime uses a policy-driven deterministic planner instead of a single fixed elimination strategy:

• Runtime policy selection can choose conservative baseline, high-support-first, or block-Schur low-rank hard-regime plans based on extracted matrix features (src/raptorq/decoder.rs).
• Hard-regime transitions and conservative fallbacks are recorded with explicit reason labels for replay/debug analysis (src/raptorq/decoder.rs, src/raptorq/proof.rs, src/raptorq/test_log_schema.rs).
• Dense-factor artifacts are cached with bounded capacity and explicit hit/miss/eviction telemetry in decode stats (src/raptorq/decoder.rs).
• GF(256) kernels are selected deterministically per process, with policy snapshots for dual-lane fused operations and optional SIMD acceleration behind simd-intrinsics (src/raptorq/gf256.rs).

One-Command RaptorQ Validation

Use the deterministic E2E wrapper with --bundle to run staged unit/perf-smoke gates plus scenario coverage with a single command:

# Fast smoke (unit sentinel + perf smoke + fast scenario profile)
NO_PREFLIGHT=1 ./scripts/run_raptorq_e2e.sh --profile fast --bundle
# Full profile
NO_PREFLIGHT=1 ./scripts/run_raptorq_e2e.sh --profile full --bundle
# Forensics profile (includes additional repair_campaign perf smoke)
NO_PREFLIGHT=1 ./scripts/run_raptorq_e2e.sh --profile forensics --bundle

Operational notes:

• The wrapper auto-uses rch when available for cargo-heavy stages (cargo test, cargo bench, scenario tests).
• --profile supports fast|full|forensics; --scenario <ID> can target one deterministic scenario.
• Artifact outputs include summary.json, scenarios.ndjson, and (when bundled) validation_stages.ndjson.
• Increase VALIDATION_TIMEOUT or E2E_TIMEOUT if your environment is slower than expected.

---

Stream Combinators

src/stream/ provides a composable stream library with the standard functional operators: map, filter, take, skip, chunks, chain, merge, zip, fold, for_each, inspect, enumerate, any_all, count, fuse, buffered, and try_stream. Streams integrate with channels (broadcast_stream, receiver_stream) and participate in cancellation; a dropped stream cleanly aborts any pending I/O.

Lab Runtime Failure Forensics

The lab runtime includes dedicated failure detectors and recovery artifacts, so concurrency failures carry structured evidence instead of vague timeouts.

• Futurelock detection tracks tasks that still hold pending obligations but stop being polled for longer than futurelock_max_idle_steps. Detection emits TraceEventKind::FuturelockDetected with task, region, and held-obligation details, and can optionally panic immediately (panic_on_futurelock) (src/lab/runtime.rs, src/lab/config.rs).
• Restorable snapshots include deterministic content hashes over full serialized runtime state (verify_integrity()), plus structural validation (validate()) that checks reference validity, region-tree acyclicity, closed-region quiescence, and timestamp consistency before restore (src/lab/snapshot_restore.rs).
• Chaos mode is deterministic and seed-bound: pre-poll and post-poll injection points can apply cancellation, delay, budget exhaustion, and wakeup storms while emitting trace events and cumulative injection stats (src/lab/chaos.rs, src/lab/config.rs, src/lab/runtime.rs).
• Failing lab runs can auto-attach deterministic crashpack linkage (stable id/path/fingerprint plus replay command metadata), and manual crashpack attachments are preserved without duplicate auto-insertions (src/lab/runtime.rs, src/trace/crashpack.rs).

---

Observability

Structured Logging

src/observability/entry.rs defines LogEntry with span IDs, task IDs, region context, and structured fields. Log levels (Trace through Error) are separate from cancellation severity. The LogCollector batches entries for export.

Metrics

src/observability/metrics.rs provides Counter, Gauge, and Histogram abstractions with a zero-allocation hot path. Optional OpenTelemetry integration (src/observability/otel.rs) exports to any OTLP-compatible backend. Multiple exporters (stdout, in-memory for tests, null for benchmarks) can compose via MultiExporter.

Task Inspector and Diagnostics

src/observability/task_inspector.rs introspects live task state: blocked reasons, obligation holdings, budget usage, and cancellation status. src/observability/diagnostics.rs produces structured explanations: CancellationExplanation traces the full cancel propagation chain, TaskBlockedExplanation identifies what a task is waiting on, and ObligationLeak pinpoints which obligation was not resolved and by whom.

For structural runtime risk, diagnostics also maintain a spectral health monitor over the live task wait graph (src/observability/spectral_health.rs, src/observability/diagnostics.rs). It tracks the Fiedler trend and classifies early-warning severity (none/watch/warning/critical) using a multi-signal ensemble: autocorrelation (critical slowing), variance growth, flicker, skewness, Kendall tau, Spearman rho, Hoeffding's D, distance correlation, split-conformal lower bounds, and an anytime-valid deterioration e-process.

---

Proc Macros

asupersync-macros/ provides proc macros for ergonomic structured concurrency:

scope!{let a = spawn!(worker_a);let b = spawn!(worker_b);
join!(a, b)}let winner = race!(task_a, task_b);

The macros expand to standard Scope/Cx calls with proper region ownership. Compile-fail tests (via trybuild) verify that incorrect usage produces clear error messages. See docs/macro-dsl.md for the full pattern catalog.

---

Conformance Suite

conformance/ is a standalone crate containing runtime-agnostic correctness tests and artifact contracts. It verifies:

• Budget enforcement: deadlines and poll quotas are respected
• Channel invariants: two-phase sends, bounded capacity, waiter cleanup
• I/O correctness: read/write under cancellation
• Outcome aggregation: severity lattice composition
• Runtime invariants: no orphans, region quiescence
• Negative tests: fault injection scenarios (obligation leaks, region hangs)
• E2E schema contracts: deterministic suite summaries, replay pointers, failure taxonomy

Test and CI entrypoints include:

• scripts/run_all_e2e.sh (orchestrated suite execution and summary checks)
• scripts/run_raptorq_e2e.sh (RaptorQ deterministic scenarios)
• scripts/run_phase6_e2e.sh (phase-6 integration surface)
• scripts/check_no_mock_policy.py (no-mock/fake/stub policy gate)
• scripts/check_coverage_ratchet.py (coverage regression ratchet)
• scripts/check_wasm_flake_governance.py (WASM flake/quarantine/forensics release gate)

Tests emit deterministic artifact bundles (event_log.txt, failed_assertions.json, repro_manifest.json) when ASUPERSYNC_TEST_ARTIFACTS_DIR is set, and E2E suites emit JSON summaries suitable for replay automation.

---

Spork (OTP Mental Model)

Spork is an OTP-style layer built on Asupersync's kernel guarantees: regions (structured concurrency), obligations (linearity), explicit cancellation, and the deterministic lab runtime.

OTP Mapping (Conceptual)

OTP Concept	Spork / Asupersync Interpretation
Process	A region-owned task/actor (cannot orphan)
Supervisor	A compiled, deterministic restart topology over regions
Link	Failure propagation rule (sibling/parent coupling; deterministic)
Monitor + DOWN	Observation without coupling: deterministic notifications
Registry	Names as lease obligations: reserve/commit or abort (no stale names)
call/cast	Request/response and mailbox protocols with bounded drain on cancel

Why Spork Is Strictly Stronger

• Determinism: the lab runtime makes OTP-style debugging reproducible (seeded schedules, trace capture/replay, schedule exploration).
• Cancel-correctness: cancellation is a protocol (request -> drain -> finalize), so OTP-style shutdown has explicit budgets and bounded cleanup.
• No silent leaks: regions cannot close with live children or unresolved obligations (permits/acks/leases), so "forgot to reply" and "stale name" become structural failures (or test-oracle failures), not production mysteries.

Where To Look In The Repo

• Supervisor compilation/runtime: src/supervision.rs
• Name leases + registry plumbing: src/cx/registry.rs
• Minimal supervised Spork app walkthrough: examples/spork_minimal_supervised_app.rs
• Deterministic ordering contracts (Spork): docs/spork_deterministic_ordering.md
• Spork glossary + invariants: docs/spork_glossary_invariants.md
• Crash artifacts + canonical traces: src/trace/crashpack.rs

Mathematical Foundations

Asupersync has formal semantics backing its engineering.

Concept	Math	Payoff
Outcomes	Severity lattice: Ok < Err < Cancelled < Panicked	Monotone aggregation, no "recovery" from worse states
Concurrency	Near-semiring: join (⊗) and race (⊕) with laws	Lawful rewrites, DAG optimization
Budgets	Tropical semiring: (ℝ∪{∞}, min, +)	Critical path computation, budget propagation
Obligations	Linear logic: resources used exactly once	No leaks, static checking possible
Traces	Mazurkiewicz equivalence (partial orders)	Optimal DPOR, stable replay
Cancellation	Two-player game with budgets	Completeness theorem: sufficient budgets guarantee termination
Adaptive scheduling	EXP3/Hedge no-regret online learning	Dynamic preemption control without fairness blind spots
Drain certificates	Martingales + Freedman/Azuma concentration	Quantified confidence that cancellation drain reaches quiescence
Structural diagnostics	Spectral graph theory + conformal + e-processes	Early warning on wait-graph fragmentation with calibrated alarms

See asupersync_v4_formal_semantics.md for the complete operational semantics.

---

"Alien Artifact" Quality Algorithms

Asupersync is intentionally "math-forward": it uses advanced math and theory-grade CS where it buys real guarantees (determinism, cancel-correctness, bounded cleanup, and reproducible concurrency debugging). This is not aspirational; the mechanisms below are implemented in the codebase today.

Online Control of Cancel Preemption (EXP3/Hedge)

src/runtime/scheduler/three_lane.rs includes a deterministic EXP3/Hedge controller that selects cancel-streak limits per epoch from observed reward (progress + fairness + deadline components). This is the scheduler's online-control layer: it adapts to workload regime shifts while preserving deterministic replay and explicit fairness bounds.

Martingale Drain Certificates (Freedman + Azuma + Phase Labels)

src/cancel/progress_certificate.rs models cancellation drain as a stochastic progress process with auditable evidence, variance estimation, and concentration bounds. Freedman provides a tighter variance-aware bound; Azuma remains as conservative reference. Verdicts include phase classification (warmup, rapid_drain, slow_tail, stalled, quiescent) for operational clarity.

Spectral Bifurcation Warnings on the Wait Graph

src/observability/spectral_health.rs computes Laplacian-spectrum diagnostics and an early-warning severity model (none/watch/warning/critical) over the live wait graph. It combines spectral trend analysis, nonparametric dependence tests, split-conformal next-step bounds, and an anytime-valid e-process, so structural degradation can be detected with calibrated confidence before hard failures.

Mazurkiewicz Trace Monoid + Foata Normal Form (DPOR Equivalence Classes)

Instead of treating traces as opaque linear logs, Asupersync factors out pure commutations of independent events via trace theory. Two traces that differ only by swapping adjacent independent events are considered equivalent, and canonicalized to a unique representative (Foata normal form). See src/trace/canonicalize.rs.

$$ M(\Sigma, I) = \Sigma^* / \equiv_I $$

Payoff: canonical fingerprints for schedule exploration and stable replay across "same behavior, different interleaving" runs.

Geodesic Schedule Normalization (A* / Beam Search Over Linear Extensions)

Given a dependency DAG (trace poset), Asupersync constructs a valid linear extension that minimizes "owner switches" (a proxy for context-switch entropy) using deterministic heuristics and an exact bounded A* solver. See src/trace/geodesic.rs and src/trace/event_structure.rs.

Payoff: smaller, more canonical traces that are easier to diff, replay, and minimize.

DPOR Race Detection + Happens-Before (Vector Clocks)

Asupersync includes DPOR-style race detection and backtracking point extraction, using a minimal happens-before relation (vector clocks per task) plus resource-footprint conflicts. See src/trace/dpor.rs and src/trace/independence.rs.

Payoff: systematic interleaving exploration that targets truly different behaviors instead of brute-force schedule fuzzing.

Persistent Homology of Trace Commutation Complexes (GF(2) Boundary Reduction)

Schedule exploration is prioritized using topological signals from a square cell complex built out of commuting diamonds: edges are causality edges, squares represent valid commutations, and Betti numbers/persistence quantify "non-trivial scheduling freedom". The implementation uses deterministic GF(2) bitset linear algebra and boundary-matrix reduction. See src/trace/boundary.rs, src/trace/gf2.rs, and src/trace/scoring.rs.

Payoff: an evidence-ledger, structure-aware notion of "interesting schedules" that tends to surface rare concurrency behaviors earlier.

Sheaf-Theoretic Consistency Checks for Distributed Sagas

In distributed obligation tracking, pairwise lattice merges can hide global inconsistency (phantom commits). Asupersync models this as a sheaf-style gluing problem and detects obstructions where no global assignment explains all local observations. See src/trace/distributed/sheaf.rs.

Payoff: catches split-brain-style saga states that evade purely pairwise conflict checks.

Anytime-Valid Invariant Monitoring (E-Processes, Ville's Inequality)

The lab runtime can continuously monitor invariants (task leaks, obligation leaks, region quiescence) using e-processes: a supermartingale-based, anytime-valid testing framework that supports optional stopping without "peeking penalties". See src/lab/oracle/eprocess.rs and src/obligation/eprocess.rs.

Payoff: turn long-running exploration into statistically sound monitoring, with deterministic, explainable rejection thresholds.

Distribution-Free Conformal Calibration for Oracle Metrics

Oracle anomaly thresholds are calibrated using split conformal prediction, giving finite-sample, distribution-free coverage guarantees under exchangeability assumptions across deterministic schedule seeds. See src/lab/conformal.rs.

Payoff: stable false-alarm behavior under workload drift, without hand-tuned magic constants.

Algebraic Law Sheets + Rewrite Engines With Side-Condition Lattices

Asupersync's concurrency combinators come with an explicit law sheet (severity lattices, budget semirings, race/join laws, etc.) and a rewrite engine guarded by conservative static analyses (obligation-safety and cancel-safety lattices; deadline min-plus reasoning). See src/combinator/laws.rs, src/plan/rewrite.rs, and src/plan/analysis.rs.

Payoff: principled plan optimization without silently breaking cancel/drain/quiescence invariants.

TLA+ Export for Model Checking

Traces can be exported as TLA+ behaviors with spec skeletons for bounded TLC model checking of core invariants (no orphans, obligation linearity, quiescence). See src/trace/tla_export.rs.

Payoff: bridge from deterministic runtime traces to model-checking workflows when you need "prove it", not "it passed tests".

---

Using Asupersync as a Dependency

Cargo.toml

[dependencies]
# crates.ioasupersync = "0.2.5"# or git# asupersync = { git = "https://github.com/Dicklesworthstone/asupersync", version = "0.2.5" }

Feature Flags

Asupersync is feature-light by default; the lab runtime is available without flags.

Feature	Description	Default
test-internals	Expose test-only helpers (not for production)	Yes
metrics	OpenTelemetry metrics provider	No
tracing-integration	Tracing spans/logging integration	No
proc-macros	scope!, spawn!, join!, race! proc macros	No
tower	Tower Service adapter support	No
trace-compression	LZ4 compression for trace files	No
debug-server	Debug HTTP server for runtime inspection	No
config-file	TOML config file loading for RuntimeBuilder	No
lock-metrics	Contended mutex wait/hold metrics	No
io-uring	Linux io_uring reactor (kernel 5.1+)	No
tls	TLS support via rustls	No
tls-native-roots	TLS with native root certs	No
tls-webpki-roots	TLS with webpki root certs	No
sqlite	SQLite async wrapper with blocking pool bridge	No
postgres	PostgreSQL async wire-protocol client	No
mysql	MySQL async wire-protocol client	No
kafka	Kafka integration via rdkafka	No
simd-intrinsics	AVX2/NEON GF(256) kernels for RaptorQ	No
loom-tests	Loom scheduler/concurrency verification surface	No
cli	CLI tools (trace inspection)	No

Minimum Supported Rust Version

Rust nightly (Edition 2024, pinned by rust-toolchain.toml).

Semver Policy

• 0.x.y: Breaking changes may ship in 0.(x+1).0
• 1.x.y: Breaking changes only in (1+1).0.0

See docs/api_audit.md for the current public API audit and stability notes.

Core Exports

use asupersync::{// Capability contextCx,Scope,// Outcome types (four-valued result)Outcome,OutcomeError,PanicPayload,Severity, join_outcomes,// CancellationCancelKind,CancelReason,// Resource managementBudget,Time,// Error handlingError,ErrorKind,Recoverability,// IdentifiersRegionId,TaskId,ObligationId,// TestingLabConfig,LabRuntime,// PolicyPolicy,};

Wrapping Cx for Frameworks

Framework authors (e.g., HTTP servers) should wrap Cx:

/// Framework-specific request contextpubstructRequestContext<'a>{cx:&'aCx,request_id:u64,}impl<'a>RequestContext<'a>{pubfnis_cancelled(&self) -> bool{self.cx.is_cancel_requested()}pubfnbudget(&self) -> Budget{self.cx.budget()}pubfncheckpoint(&self) -> Result<(), asupersync::Error>{self.cx.checkpoint()}}

HTTP Status Mapping

// Recommended HTTP status mapping:// - Outcome::Ok(_) → 200 OK// - Outcome::Err(_) → 4xx/5xx based on error type// - Outcome::Cancelled(_) → 499 Client Closed Request// - Outcome::Panicked(_) → 500 Internal Server Error

---

Configuration

Lab Runtime Configuration

let config = LabConfig::default()// Seed for deterministic scheduling (same seed = same execution).seed(42)// Maximum steps before timeout (prevents infinite loops).max_steps(100_000)// Enable futurelock detection (tasks holding obligations without progress).futurelock_max_idle_steps(1000)// Enable trace capture for replay.capture_trace(true);let lab = LabRuntime::new(config);

Futurelock detection is tied to held obligations and poll progress, not just elapsed time. The detector compares current step against each task's last_polled_step, and can either emit violations or panic based on panic_on_futurelock (src/lab/runtime.rs, src/lab/config.rs).

Lab snapshots also support structural validation and integrity checks. RestorableSnapshot computes a deterministic content hash over the full serialized snapshot, so semantic tampering is detectable before replay analysis (src/lab/snapshot_restore.rs).

Runtime leak handling is configurable via ObligationLeakResponse (Panic, Log, Silent, Recover) with optional threshold-based escalation (LeakEscalation), and zero thresholds are normalized to one to avoid invalid policy states (src/runtime/config.rs). If a leak is detected while the thread is already unwinding, a Panic response is downgraded to Log to avoid double-panic aborts; leak counting is also guarded against reentrant inflation (src/runtime/state.rs).

Budget Configuration

// Request timeout with poll budgetlet request_budget = Budget::new().with_deadline_secs(30)// 30 second timeout.with_poll_quota(10_000)// Max 10k polls.with_priority(100);// Normal priority// Cleanup budget (tighter for faster shutdown)let cleanup_budget = Budget::new().with_deadline_secs(5).with_poll_quota(500);

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Troubleshooting

"ObligationLeak detected"

Your task completed while holding an obligation (permit, ack, lease).

// Wrong: permit dropped without send/abortlet permit = tx.reserve(cx).await?;returnOutcome::ok(());// Leak!// Right: always resolve obligationslet permit = tx.reserve(cx).await?;
permit.send(message);// Resolved

"RegionCloseTimeout"

A region is stuck waiting for children that won't complete.

// Check for: infinite loops without checkpointsloop{
cx.checkpoint()?;// Add checkpoints in loops// ... work ...}

"FuturelockViolation"

A task is holding obligations but not making progress.

// Check for: awaiting something that will never resolve// while holding a permit/locklet permit = tx.reserve(cx).await?;
other_thing.await;// If this blocks forever → futurelock
permit.send(msg);

Deterministic test failures

Same seed should give same execution. If not:

// Check for: time-based operations// WRONG: uses wall-clock timelet now = std::time::Instant::now();// RIGHT: uses virtual time through Cxlet now = cx.now();

Also check for ambient randomness:

// WRONG: ambient entropy breaks determinismlet id = rand::random::<u64>();// RIGHT: use capability-based entropylet id = cx.random_u64();

To enforce deterministic collections in lab code, consider a clippy rule that disallows std::collections::HashMap/HashSet in favor of util::DetHashMap/DetHashSet.

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Limitations

Current State

Capability	Status
Single-thread deterministic kernel	✅ Complete
Parallel scheduler + work-stealing	✅ Implemented (three-lane scheduler)
I/O reactor (epoll + io_uring)	✅ Implemented
TCP, HTTP/1.1, HTTP/2, WebSocket, TLS	✅ Implemented
Database clients (SQLite, PostgreSQL, MySQL)	✅ Implemented
Actor supervision (GenServer, links, monitors)	✅ Implemented
DPOR schedule exploration	✅ Implemented
Distributed runtime (remote tasks, sagas, leases, recovery)	✅ Implemented
RaptorQ fountain coding for snapshot distribution	✅ Implemented
Formal methods (Lean coverage artifacts + TLA+ export)	✅ Implemented

What Asupersync Doesn't Do

• Cooperative cancellation only: Non-cooperative code requires explicit escalation boundaries
• Not a drop-in replacement for other runtimes: Different API, different guarantees
• No Tokio dependency compatibility by default: runtime-specific crates that assume Tokio need explicit boundary adapters

Design Trade-offs

Choice	Trade-off
Explicit checkpoints	More verbose, but cancellation is observable
Capability tokens	Extra parameter threading, but testable and auditable
Two-phase effects	More complex primitives, but no data loss
Region ownership	Can't detach tasks, but no orphans

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Roadmap

Phase	Focus	Status
Phase 0	Single-thread deterministic kernel	✅ Complete
Phase 1	Parallel scheduler + region heap	✅ Complete
Phase 2	I/O integration (epoll, io_uring, TCP, HTTP, TLS)	✅ Complete
Phase 3	Actors + supervision (GenServer, links, monitors)	✅ Complete
Phase 4	Distributed structured concurrency	✅ Complete
Phase 5	DPOR + TLA+ tooling	✅ Complete
Phase 6	Hardening, policy gates, and adapter surface expansion	✅ Continuous

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FAQ

Why "Asupersync"?

"A super sync": structured concurrency done right.

Why not just use existing runtimes with careful conventions?

Conventions don't compose. The 100th engineer on your team will spawn a detached task. The library you depend on will drop a future holding a lock. Asupersync makes incorrect code unrepresentable (or at least detectable).

How does this compare to structured concurrency in other languages?

Similar goals to Kotlin coroutines, Swift structured concurrency, and Java's Project Loom. Asupersync goes further with:

• Formal operational semantics
• Two-phase effects for cancel-safety
• Obligation tracking (linear resources)
• Deterministic lab runtime

Can I use this with existing async Rust code?

Asupersync has its own runtime with explicit capabilities. For code that needs to interop with external async libraries, we provide boundary adapters that preserve our cancel-correctness guarantees.

Is this production-ready?

Asupersync is active development software with a fully implemented runtime surface (deterministic kernel, parallel scheduler, TCP/HTTP/TLS/WebSocket, database clients, distributed runtime primitives, actor/supervision model, and deterministic verification harnesses). It is a strong fit for internal systems where correctness guarantees and deterministic debugging are primary requirements.

How do I report bugs?

Open an issue at https://github.com/Dicklesworthstone/asupersync/issues

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Documentation

Document	Purpose
asupersync_plan_v4.md	Design Bible: Complete specification, invariants, philosophy
asupersync_v4_formal_semantics.md	Operational Semantics: Small-step rules, TLA+ sketch
asupersync_v4_api_skeleton.rs	API Skeleton: Rust types and signatures
docs/integration.md	Integration Docs: Architecture, API orientation, tutorials, Browser Edition docs IA/navigation contract
docs/wasm_quickstart_migration.md	Browser Quickstart + Migration: deterministic onboarding commands, migration anti-pattern map, deferred-surface fallback guidance
docs/wasm_canonical_examples.md	Browser Canonical Examples: vanilla/TypeScript/React/Next scenario catalog with deterministic repro commands and artifact pointers
docs/wasm_pilot_cohort_rubric.md	Pilot Cohort Rubric: deterministic intake scoring, risk tiers, exclusions, and onboarding acceptance criteria
docs/wasm_browser_scheduler_semantics.md	Browser Scheduler + Trace Contract: scheduler/event-loop law plus browser trace schema v1 taxonomy, compatibility, and redaction rules
docs/wasm_react_reference_patterns.md	React Reference Pattern Catalog: deterministic task-group, retry, bulkhead, and tracing-hook scenarios with replay commands
docs/wasm_nextjs_template_cookbook.md	Next.js Template Cookbook: deterministic App Router bootstrap/deployment scenarios, failure signatures, and replay commands
docs/wasm_flake_governance_and_forensics.md	WASM Flake Governance + Forensics: quarantine policy, release-blocking thresholds, and deterministic replay triage workflow
docs/doctor_operator_model_contract.md	Doctor Operator Contract: personas, missions, and decision-loop schema
docs/doctor_workspace_scanner_contract.md	Doctor Workspace + Screen Contract: workspace scan schema and screen-to-engine payload contracts
docs/doctor_evidence_ingestion_contract.md	Doctor Evidence Contract: deterministic artifact-ingestion schema, provenance, and compatibility policy
docs/doctor_logging_contract.md	Doctor Logging Contract: baseline event envelope, correlation primitives, and deterministic smoke-validation rules
docs/doctor_remediation_recipe_contract.md	Doctor Remediation DSL Contract: machine-readable recipe schema, confidence scoring model, risk bands, and extension policy
docs/doctor_diagnostics_report_contract.md	Doctor Core Report Contract: summary/findings/evidence/commands/provenance schema with deterministic fixture bundle
docs/doctor_cli_packaging_contract.md	Doctor CLI Packaging Contract: deterministic package payload, config templates, manifest policy, install smoke, and upgrade guidance
docs/raptorq_baseline_bench_profile.md	RaptorQ Baseline Packet: deterministic bench/profile corpus + repro commands
docs/raptorq_unit_test_matrix.md	RaptorQ Unit Matrix: unit/E2E scenario coverage and replay/log schema mapping
docs/macro-dsl.md	Macro DSL: scope!/spawn!/join!/race! usage, patterns, examples
docs/cancellation-testing.md	Cancellation Testing: deterministic injection + oracles
docs/replay-debugging.md	Replay Debugging: Record/replay for debugging async bugs
docs/security_threat_model.md	Security Review: Threat model and security invariants
formal/lean/coverage/README.md	Lean Coverage Program: ontology, artifacts, CI profiles, and proof-health contracts
formal/lean/coverage/proof_impact_closed_loop_report_v1.json	Proof Impact Ledger: reproducible correctness/reliability/performance closure evidence
TESTING.md	Testing Guide: unit, conformance, E2E, fuzzing, CI
AGENTS.md	AI Guidelines: Rules for AI coding agents

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Contributing

About Contributions: Please don't take this the wrong way, but I do not accept outside contributions for any of my projects. I simply don't have the mental bandwidth to review anything, and it's my name on the thing, so I'm responsible for any problems it causes; thus, the risk-reward is highly asymmetric from my perspective. I'd also have to worry about other "stakeholders," which seems unwise for tools I mostly make for myself for free. Feel free to submit issues, and even PRs if you want to illustrate a proposed fix, but know I won't merge them directly. Instead, I'll have Claude or Codex review submissions via gh and independently decide whether and how to address them. Bug reports in particular are welcome. Sorry if this offends, but I want to avoid wasted time and hurt feelings. I understand this isn't in sync with the prevailing open-source ethos that seeks community contributions, but it's the only way I can move at this velocity and keep my sanity.

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License

MIT License (with OpenAI/Anthropic Rider). See LICENSE.