tasq/node_modules/@claude-flow/neural/__tests__/README.md

Neural Module Test Suite

Comprehensive test coverage for the V3 neural module with 106 tests across 3 test files.

Test Files

1. sona.test.ts (23 tests)

Tests for SONA Learning Engine integration with @ruvector/sona:

Initialization (5 tests)

• Balanced mode initialization
• Real-time mode initialization
• Research mode initialization
• Edge mode initialization
• Batch mode initialization

Learning from Trajectories (5 tests)

• Learning from complete trajectory
• Performance target validation (<0.05ms)
• Handling empty trajectories
• Multi-step trajectory learning
• Learning time tracking

Adaptation (6 tests)

• Behavior adaptation based on context
• Performance target validation (<0.1ms)
• Finding similar patterns
• Route inference from patterns
• Handling no patterns found
• Adaptation time tracking

Mode Switching (2 tests)

• Switching between modes
• Resetting learning state

Statistics and Monitoring (3 tests)

• Engine statistics retrieval
• Learning time tracking
• Adaptation time tracking

Engine Control (2 tests)

• Enable/disable engine
• Force learning and background ticking
• Pattern finding by embedding

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2. algorithms.test.ts (44 tests)

Tests for reinforcement learning algorithms:

Q-Learning (8 tests)

• Initialization
• Q-value updates from trajectory
• Performance target (<1ms)
• Exploration rate decay
• Epsilon-greedy action selection
• Q-value retrieval
• Eligibility traces support
• Q-table pruning
• Reset functionality

SARSA (8 tests)

• Initialization
• SARSA rule updates
• Expected SARSA variant
• Action probability distribution
• Epsilon-greedy policy
• Eligibility traces (SARSA-lambda)
• Short trajectory handling
• Reset functionality

DQN (9 tests)

• Initialization
• Experience replay buffer
• DQN update mechanism
• Performance target (<10ms)
• Double DQN support
• Epsilon-greedy action selection
• Q-value retrieval
• Target network updates
• Circular buffer handling

PPO (7 tests)

• Initialization
• Experience collection
• PPO update with clipping
• Performance target (<10ms for small batches)
• GAE advantage computation
• Policy action sampling
• Multiple training epochs
• Buffer clearing after update

Decision Transformer (12 tests)

• Initialization
• Trajectory buffer management
• Incomplete trajectory handling
• Training on buffered trajectories
• Performance target (<10ms per batch)
• Return-conditioned action generation
• Causal attention masking
• Bounded trajectory buffer
• Varying trajectory lengths
• Returns-to-go computation

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3. patterns.test.ts (39 tests)

Tests for pattern learning and ReasoningBank:

Pattern Extraction (9 tests)

• Initialization
• Trajectory storage
• Trajectory retrieval
• Successful trajectory judgment
• Failed trajectory judgment
• Strength identification
• Weakness identification
• Improvement suggestion generation
• Incomplete trajectory error handling

Memory Distillation (8 tests)

• Successful trajectory distillation
• Low-quality trajectory filtering
• Automatic judgment before distillation
• Strategy extraction
• Key learnings extraction
• Aggregate embedding computation
• Distillation performance tracking
• Memory-trajectory linking

Retrieval with MMR (6 tests)

• Top-k similar memory retrieval
• MMR diversity application
• Retrieval result structure
• Retrieval performance tracking
• Empty bank handling
• K parameter respect

Consolidation (6 tests)

• Memory deduplication
• Contradiction detection
• Pattern merging
• Old pattern pruning
• Consolidation result structure
• Consolidation event emission

Pattern Management (7 tests)

• Memory to pattern conversion
• Pattern evolution with new experience
• Pattern usage tracking
• Success rate updates
• Quality history maintenance (max 100)
• Pattern evolution events
• Getting all patterns

Event System (3 tests)

• Adding/removing event listeners
• Consolidation event emission
• Pattern evolution event emission

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Performance Targets

All tests validate against these performance targets:

Operation	Target	Test Coverage
SONA learn()	<0.05ms	✓
SONA adapt()	<0.1ms	✓
Q-Learning update	<1ms	✓
SARSA update	<1ms	✓
DQN update	<10ms	✓
PPO update	<10ms	✓
Decision Transformer train	<10ms	✓
ReasoningBank retrieval	<10ms	✓
ReasoningBank distillation	<10ms	✓

Running Tests

# Run all tests
npm run test

# Run with coverage
npm run test -- --coverage

# Run specific test file
npm run test sona.test.ts
npm run test algorithms.test.ts
npm run test patterns.test.ts

# Watch mode
npm run test -- --watch

Test Coverage Goals

• Statements: >80%
• Branches: >75%
• Functions: >80%
• Lines: >80%

Algorithm Correctness

Tests validate core algorithm implementations:

1. Q-Learning: TD error computation, Q-table updates, exploration decay
2. SARSA: On-policy updates, expected SARSA variant, eligibility traces
3. DQN: Experience replay, target networks, double DQN, dueling architecture
4. PPO: Clipped surrogate objective, GAE, value clipping, entropy bonus
5. Decision Transformer: Sequence modeling, causal attention, return conditioning

Pattern Learning Pipeline

Tests validate the 4-step ReasoningBank pipeline:

1. RETRIEVE: Top-k memory injection with MMR diversity (6 tests)
2. JUDGE: LLM-as-judge trajectory evaluation (9 tests)
3. DISTILL: Extract strategy memories from trajectories (8 tests)
4. CONSOLIDATE: Dedup, detect contradictions, prune patterns (6 tests)

Mocking Strategy

• @ruvector/sona: Mocked to isolate SONA integration tests
• All algorithms: Pure TypeScript, no mocking needed
• ReasoningBank: Pure TypeScript, no mocking needed

Notes

• Tests use Vitest for fast execution
• All tests are isolated with beforeEach setup
• Performance tests allow overhead for mocking/setup
• Helper functions generate realistic test trajectories
• Tests cover edge cases (empty trajectories, incomplete data, etc.)