* ci(bench): wire v2 criterion benches into CI as a compile-verify regression gate
Sub-deliverable 8.3 of the benchmark/optimization milestone (needs ADR slot 174).
The v2/ workspace ships 26 criterion benches across 18 crates, but benches are
not part of `cargo test`, so nothing in CI compiled them and they silently rot
when a public API they call changes.
Add `.github/workflows/bench-regression.yml`:
- bench-compile (HARD GATE): `cargo bench --workspace --no-default-features
--no-run` compiles + links every default-feature bench (no measurement) plus
the cir-gated cir_bench — a real, deterministic regression guard against
bench bit-rot.
- bench-fast-run (INFORMATIONAL, continue-on-error, never gates): runs a
curated pure-CPU subset (nvsim, ruvector sketch/fusion) in criterion
quick-mode and uploads logs as an artifact.
No timing-regression gate, by design: wall-clock on shared GitHub runners varies
2-3x run-to-run, so a hard threshold or cross-runner `criterion --baseline`
compare would manufacture false failures. The honest scope is compile-verify +
informational-run; the workflow header documents the self-hosted-runner
condition under which true timing-gating becomes honest. The crv-gated crv_bench
is excluded because its crates.io dep ruvector-crv 0.1.1 fails to build upstream.
Running the gate immediately caught one already-bit-rotted bench:
wifi-densepose-mat/detection_bench failed to compile (E0063: missing field
last_rssi in SensorPosition). Fixed (last_rssi: None) and re-verified.
Validation (MEASURED): mat detection_bench + cir_bench + nvsim + ruvector +
vitals + swarm benches compile under --no-default-features; fast subset runs;
`cargo test -p wifi-densepose-mat --no-default-features` 174 passed / 0 failed;
Python proof PASS, hash f8e76f21...46f7a unchanged.
Co-Authored-By: claude-flow <ruv@ruv.net>
* docs(adr): ADR-174 — CI bench-regression compile-verify gate
Records sub-deliverable 8.3 (bench-regression.yml, committed
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| .. | ||
| benches | ||
| src | ||
| tests | ||
| Cargo.toml | ||
| README.md | ||
README.md
wifi-densepose-mat
Mass Casualty Assessment Tool for WiFi-based disaster survivor detection and localization.
Overview
wifi-densepose-mat uses WiFi Channel State Information (CSI) to detect and locate survivors
trapped in rubble, debris, or collapsed structures. The crate follows Domain-Driven Design (DDD)
with event sourcing, organized into three bounded contexts -- detection, localization, and
alerting -- plus a machine learning layer for debris penetration modeling and vital signs
classification.
Use cases include earthquake search and rescue, building collapse response, avalanche victim location, flood rescue operations, and mine collapse detection.
Features
- Vital signs detection -- Breathing patterns, heartbeat signatures, and movement classification with ensemble classifier combining all three modalities.
- Survivor localization -- 3D position estimation through debris via triangulation, depth estimation, and position fusion.
- Triage classification -- Automatic START protocol-compatible triage with priority-based alert generation and dispatch.
- Event sourcing -- All state changes emitted as domain events (
DetectionEvent,AlertEvent,ZoneEvent) stored in a pluggableEventStore. - ML debris model -- Debris material classification, signal attenuation prediction, and uncertainty-aware vital signs classification.
- REST + WebSocket API --
axum-based HTTP API for real-time monitoring dashboards. - ruvector integration --
ruvector-solverfor triangulation math,ruvector-temporal-tensorfor compressed CSI buffering.
Feature flags
| Flag | Default | Description |
|---|---|---|
std |
yes | Standard library support |
api |
yes | REST + WebSocket API (enables serde for all types) |
ruvector |
yes | ruvector-solver and ruvector-temporal-tensor |
serde |
no | Serialization (also enabled by api) |
portable |
no | Low-power mode for field-deployable devices |
distributed |
no | Multi-node distributed scanning |
drone |
no | Drone-mounted scanning (implies distributed) |
Quick Start
use wifi_densepose_mat::{
DisasterResponse, DisasterConfig, DisasterType,
ScanZone, ZoneBounds,
};
#[tokio::main]
async fn main() -> anyhow::Result<()> {
let config = DisasterConfig::builder()
.disaster_type(DisasterType::Earthquake)
.sensitivity(0.8)
.build();
let mut response = DisasterResponse::new(config);
// Define scan zone
let zone = ScanZone::new(
"Building A - North Wing",
ZoneBounds::rectangle(0.0, 0.0, 50.0, 30.0),
);
response.add_zone(zone)?;
// Start scanning
response.start_scanning().await?;
Ok(())
}
Architecture
wifi-densepose-mat/src/
lib.rs -- DisasterResponse coordinator, config builder, MatError
domain/
survivor.rs -- Survivor aggregate root
disaster_event.rs -- DisasterEvent, DisasterType
scan_zone.rs -- ScanZone, ZoneBounds
alert.rs -- Alert, Priority
vital_signs.rs -- VitalSignsReading, BreathingPattern, HeartbeatSignature
triage.rs -- TriageStatus, TriageCalculator (START protocol)
coordinates.rs -- Coordinates3D, LocationUncertainty
events.rs -- DomainEvent, EventStore, InMemoryEventStore
detection/ -- BreathingDetector, HeartbeatDetector, MovementClassifier, EnsembleClassifier
localization/ -- Triangulator, DepthEstimator, PositionFuser
alerting/ -- AlertGenerator, AlertDispatcher, TriageService
ml/ -- DebrisPenetrationModel, VitalSignsClassifier, UncertaintyEstimate
api/ -- axum REST + WebSocket router
integration/ -- SignalAdapter, NeuralAdapter, HardwareAdapter
Related Crates
| Crate | Role |
|---|---|
wifi-densepose-core |
Foundation types and traits |
wifi-densepose-signal |
CSI preprocessing for detection pipeline |
wifi-densepose-nn |
Neural inference for ML models |
wifi-densepose-hardware |
Hardware sensor data ingestion |
ruvector-solver |
Triangulation and position math |
ruvector-temporal-tensor |
Compressed CSI buffering |
License
MIT OR Apache-2.0