proffesor-for-testing__agentic-qe/reports/rvf-benchmark-comparison.md

RVF Integration Benchmark Comparison

Date: 2026-02-22 Baseline: 2026-02-22T20:34:28Z (pre-implementation, original) Post: 2026-02-22T21:15:32Z (post-implementation) System: linux/arm64, Node v24.13.0, 16GB RAM

Note

: baseline-benchmarks.json was inadvertently overwritten on Feb 23 with a post-integration re-run. The original pre-RVF baseline (Feb 22 20:34:28) has been restored. The Feb 23 re-run is preserved in baseline-benchmarks-feb23-rerun.json for reference.

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Summary

Metric	Baseline	Post	Delta	Verdict
HNSW Init	75.63ms	36.66ms	-51.5%	Improved
Pattern Loading	78.76ms	45.49ms	-42.3%	Improved
RSS Memory	135.56MB	116.52MB	-14.0%	Improved
Heap Total	24.32MB	22.07MB	-9.3%	Improved
MinCut TS Latency	10.83us	8.71us	-19.6%	Improved
Dream Insights	670	690	+3.0%	More learning
Dream Cycles	252	254	+0.8%	Active
Boot Time (total)	1133.37ms	1427.46ms	+25.9%	See note 1
Embedding Model Load	978.97ms	1345.29ms	+37.4%	See note 1
Routing p50	0.002ms	0.002ms	0%	Unchanged
DB Size	84.25MB	88.80MB	+5.4%	Expected growth
Pattern Count	6644	6644	0%	No loss

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Detailed Analysis

HNSW Initialization: -51.5% (75.63ms -> 36.66ms)

The unified HNSW backend (ADR-071) provides a single interface with lazy loading. The UnifiedHnswIndex defers full index construction, answering queries via brute-force cosine similarity first, then upgrading to @ruvector/gnn differentiableSearch if available. This is a 2-state conditional fallback, not the originally claimed 3-layer progressive system. The deferred loading still halved init time.

Pattern Loading: -42.3% (78.76ms -> 45.49ms)

ReasoningBank initialization benefits from the unified HNSW path. Instead of initializing 3 separate search implementations, the system now bootstraps a single HnswAdapter that manages named indexes (patterns, qe-memory, learning, coverage) through one code path.

Memory Usage: -14.0% (135.56MB -> 116.52MB RSS)

Consolidating HNSW implementations reduces duplicate data structures. The backend shares a single vector store across all named indexes via HnswAdapter, eliminating redundant copies of the same embeddings.

MinCut Latency: -19.6% (10.83us -> 8.71us)

The TypeScript MinCutCalculator (wrapped by QEMinCutService) shows improved performance, likely due to JIT warmup differences between runs. The mincut lambda computation remains sub-microsecond at 128.7ns per the ruvector benchmarks; the measured ~9us includes graph construction overhead.

Boot Time: +25.9% (NOTE: Not a regression)

Total boot time increased from 1133ms to 1427ms. This is entirely attributable to embedding model load variance (979ms -> 1345ms), which is environment-dependent (container memory pressure, model cache state). The components we changed (HNSW init, pattern loading) both improved significantly. With consistent model loading, effective boot time dropped by ~72ms.

Adjusted boot time (excluding embedding model load):

• Baseline: 1133.37 - 978.97 = 154.40ms
• Post: 1427.46 - 1345.29 = 82.17ms
• Delta: -46.8% improvement

Routing Latency: Unchanged (0.002ms p50)

The benchmark script measures the existing heuristic routing path. The MinCutRoutingService is wired as a strategy in task-router.ts but delegates to mincut-wrapper.js and requires agent topology data to activate. When topology is provided, routing uses lambda-based tier assignment. The heuristic remains as fallback and was measured here.

Database Integrity: Verified

• Pattern count: 6644 -> 6644 (zero data loss)
• Vector count: 124 -> 124 (preserved)
• KV entries: 1217 -> 1246 (+29, normal operational growth)
• Dream cycles: 252 -> 254 (+2, background dreaming continued)
• Dream insights: 670 -> 690 (+20, learning active)

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New Capabilities (Not Captured by Baseline Benchmarks)

These are new features that had no baseline equivalent. Status reflects wiring state, not just existence of code.

Capability	Status	Tests	Description
MinCut Routing	Wired	47 passing	Wrapper delegating to mincut-wrapper.js; production-active in task-router.ts (ADR-068)
RVCOW Dream Branching	Wired	26 passing	SQLite savepoints are real and functional; RVF fork is a cosmetic side-effect writing to /tmp (ADR-069)
Witness Chain	Wired	21 passing	Genuinely correct SHA-256 hash chain, production-active (ADR-070)
HNSW Unification	Wired	39 passing	Single IHnswIndexProvider interface; 2-state fallback (try @ruvector/gnn, else brute-force cosine), not 3-layer progressive as originally claimed (ADR-071)
Speculative Dreaming	Wired	included above	Runs on SQLite savepoints, not RVF RVCOW as the name implies
Structural Health Monitor	Internal	included above	Used within mincut subsystem only, not exposed as an endpoint

Total new tests: 133

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Modules Not Yet Wired Into Production

The following modules exist and have passing tests, but are not imported or invoked by any production code path:

Module	File	Status
RVF Native Adapter	rvf-native-adapter.ts	Exists, tested, but not imported by any production code
RVF Dual-Writer	rvf-dual-writer.ts	Exists, tested, not wired into QEReasoningBank
Brain Exporter	brain-exporter.ts	CLI functions exist but not registered in CommandRegistry
MinCut Test Optimizer	mincut-test-optimizer.ts	Exists, tested, zero imports in codebase

These modules represent completed work that needs integration wiring to become production-active. Until wired, they are dead code with test coverage.

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HNSW Implementation Status

Implementation	Baseline	Post	Notes
InMemoryHNSWIndex	Active	Deprecated	Replaced by UnifiedHnswIndex (ADR-071 Phase B)
RuvectorFlatIndex	Active	Deprecated	Replaced by unified backend
QEGNNEmbeddingIndex	Active	Active	Migration pending (coverage domain)
UnifiedHnswIndex	N/A	NEW	Single entry point via HnswAdapter
ProgressiveHnswBackend	N/A	NEW	2-state conditional fallback (try @ruvector/gnn, else brute-force cosine)

Effective HNSW implementations: 3 -> 1 primary + 2 deprecated (kept as fallback per risk mitigation plan)

Correction: The original report described the ProgressiveHnswBackend as "3-layer progressive loading." The actual implementation is a 2-state conditional: it attempts @ruvector/gnn and falls back to brute-force cosine similarity. There is no intermediate layer.

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Audit Trail Coverage

Area	Baseline	Post
Quality gate decisions	0%	100% (QUALITY_GATE_PASS/FAIL recorded)
Pattern mutations	0%	100% (CREATE, UPDATE, PROMOTE recorded)
Dream merge/discard	0%	100% (DREAM_MERGE, DREAM_DISCARD recorded)
Routing decisions	0%	Wired (ROUTING_DECISION type available)

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Targets vs Actuals

Metric	Master Plan Target	Actual	Hit?
HNSW init	Faster	36.66ms (-51.5%)	Yes
Pattern load	Faster	45.49ms (-42.3%)	Yes
Memory RSS	Lower	116.52MB (-14.0%)	Yes
Search implementations	1	1 primary + 2 deprecated	Partial
Audit trail	100% of gates + mutations	100%	Yes
Data loss	Zero	Zero (6644/6644 patterns)	Yes
Dream branching	Safe isolation	SQLite savepoints (real); RVF fork (cosmetic)	Partial
MinCut routing	Lambda-based	Wired via wrapper with fallback	Partial

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Recommendations

1. Wire dead modules into production — The RVF Native Adapter, RVF Dual-Writer, Brain Exporter, and MinCut Test Optimizer all exist with tests but have zero production imports. Either wire them into the appropriate code paths or remove them to reduce maintenance burden.
2. Register Brain Exporter commands in CommandRegistry so the CLI functions are actually callable.
3. Wire RVF Dual-Writer into QEReasoningBank if dual-write capability is still desired; otherwise delete it.
4. Remove deprecated HNSW implementations once UnifiedHnswIndex has been validated in production for 1+ week.
5. Migrate coverage domain (QEGNNEmbeddingIndex) to use HnswAdapter.create('coverage') to complete unification.
6. Update benchmark script to exercise new code paths (mincut routing with topology, unified HNSW search, witness chain verification).
7. Run integration tests (Step 2 from master plan) to validate cross-workstream behavior.
8. Monitor embedding model load variance — consider pre-warming or caching the model to stabilize boot time.
9. Evaluate whether "RVCOW" naming is misleading — The actual dream branching uses SQLite savepoints, which work well. The RVF/RVCOW layer on top writes to /tmp as a side effect. Consider renaming to reflect what actually happens.