ruv 5bd0d59aa6 feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety ... P1 fixes (this sprint): - P1-6: Extract sensing-server modules (cli, types, csi, pose) from main.rs - P1-7: DDA ray march for tomography — O(max(n)) replaces O(n^3) voxel scan - P1-8: Batch neural inference — Tensor::stack/split for single GPU call - P1-10: Eliminate 112KB/frame alloc — islice replaces deque→list copy P2 fixes (this quarter): - P2-11: Python unit tests for 8 modules (rate_limit, auth, error_handler, pose_service, stream_service, hardware_service, health_check, metrics) - P2-13: MAT simulated data safety guard — blocking overlay + pulsing banner - P2-14: Wire token blacklist into auth verification + logout endpoint - P2-15: Frame budget benchmark — confirms pipeline well under 50ms budget Addresses 8 of 10 remaining issues from QE analysis (ADR-080). Co-Authored-By: claude-flow <ruv@ruv.net>		2026-04-06 17:00:27 -04:00
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test_api_throughput.py	feat: Complete Rust port of WiFi-DensePose with modular crates	2026-01-13 03:11:16 +00:00
test_frame_budget.py	feat: ADR-080 P1+P2 remediation — refactor, perf, tests, safety	2026-04-06 17:00:27 -04:00
test_inference_speed.py	feat: Complete Rust port of WiFi-DensePose with modular crates	2026-01-13 03:11:16 +00:00