# TraceRTM Attached Layers & Multi-View System

Deep research on attached layers, multi-view architecture, and view synchronization for TraceRTM.

---

## 🎯 ATTACHED LAYERS CONCEPT

### What Are Attached Layers?

**Definition**: Attached layers are derived views/projections of the SSOT that:
- Serve specific use cases
- Optimize for particular query patterns
- Maintain consistency with SSOT
- Update automatically when SSOT changes
- Provide different perspectives of same data

### Layer Architecture

```
┌─────────────────────────────────────────────────┐
│         SSOT (PostgreSQL)                       │
│  - Requirements (canonical)                     │
│  - Relationships (canonical)                    │
│  - Metadata (canonical)                         │
└─────────────────────────────────────────────────┘
         ↓
┌─────────────────────────────────────────────────┐
│    Attached Layers (Materialized Views)         │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 1: Traceability Matrix             │  │
│  │ - Bidirectional links                    │  │
│  │ - Coverage status                        │  │
│  │ - Relationship types                     │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 2: Impact Analysis                 │  │
│  │ - Transitive dependencies                │  │
│  │ - Change impact scope                    │  │
│  │ - Affected requirements                  │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 3: Coverage Analysis               │  │
│  │ - Test coverage                          │  │
│  │ - Code coverage                          │  │
│  │ - Implementation status                  │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 4: Dependency Graph                │  │
│  │ - Graph structure                        │  │
│  │ - Shortest paths                         │  │
│  │ - Critical paths                         │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 5: Timeline View                   │  │
│  │ - Historical changes                     │  │
│  │ - Version history                        │  │
│  │ - Change timeline                        │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 6: Status Dashboard                │  │
│  │ - Metrics aggregation                    │  │
│  │ - Status summaries                       │  │
│  │ - KPI calculations                       │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 7: Search Index                    │  │
│  │ - Full-text search                       │  │
│  │ - Fuzzy matching                         │  │
│  │ - Quick lookups                          │  │
│  └──────────────────────────────────────────┘  │
│  ┌──────────────────────────────────────────┐  │
│  │ Layer 8: Agent Interface                 │  │
│  │ - Structured data                        │  │
│  │ - Queryable format                       │  │
│  │ - Agent-friendly schema                  │  │
│  └──────────────────────────────────────────┘  │
└─────────────────────────────────────────────────┘
         ↓
┌─────────────────────────────────────────────────┐
│    Application Layer                            │
│  - CLI Interface                                │
│  - API Endpoints                                │
│  - TUI Interface                                │
│  - Agent Interfaces                             │
└─────────────────────────────────────────────────┘
```

---

## 📊 THE 8 CORE ATTACHED LAYERS

### Layer 1: Traceability Matrix

**Purpose**: Show bidirectional traceability relationships

**Data Structure**:
```python
{
    "source_id": "req-001",
    "source_title": "User Authentication",
    "target_id": "test-001",
    "target_title": "Test Login Flow",
    "relationship_type": "tested_by",
    "bidirectional": {
        "reverse_type": "tests",
        "reverse_target": "req-001"
    }
}
```

**Use Cases**:
- View all links for a requirement
- Verify bidirectional traceability
- Check coverage status
- Generate traceability reports

**Query Performance**: <50ms

### Layer 2: Impact Analysis

**Purpose**: Show downstream impacts of changes

**Data Structure**:
```python
{
    "source_id": "req-001",
    "affected_requirements": [
        {"id": "req-002", "depth": 1, "path": ["req-001", "req-002"]},
        {"id": "req-003", "depth": 2, "path": ["req-001", "req-002", "req-003"]},
    ],
    "affected_tests": [...],
    "affected_code": [...],
    "total_impact_scope": 15
}
```

**Use Cases**:
- Assess change impact
- Plan regression testing
- Identify affected components
- Risk analysis

**Query Performance**: <100ms

### Layer 3: Coverage Analysis

**Purpose**: Show test and code coverage for requirements

**Data Structure**:
```python
{
    "requirement_id": "req-001",
    "test_coverage": {
        "tested": True,
        "test_count": 5,
        "test_ids": ["test-001", "test-002", ...]
    },
    "code_coverage": {
        "implemented": True,
        "code_count": 3,
        "file_ids": ["file-001", "file-002", ...]
    },
    "coverage_percentage": 85,
    "coverage_status": "Covered"
}
```

**Use Cases**:
- Track coverage metrics
- Identify untested requirements
- Find unimplemented features
- Generate coverage reports

**Query Performance**: <50ms

### Layer 4: Dependency Graph

**Purpose**: Graph structure for algorithms

**Data Structure**:
```python
{
    "nodes": [
        {"id": "req-001", "label": "User Auth", "type": "requirement"},
        {"id": "req-002", "label": "Login", "type": "requirement"},
    ],
    "edges": [
        {"source": "req-001", "target": "req-002", "type": "depends_on", "weight": 1},
    ],
    "adjacency_list": {
        "req-001": ["req-002", "req-003"],
        "req-002": ["req-003"],
    }
}
```

**Use Cases**:
- Shortest path analysis
- Critical path identification
- Cycle detection
- Dependency resolution

**Query Performance**: <100ms

### Layer 5: Timeline View

**Purpose**: Historical changes and version history

**Data Structure**:
```python
{
    "requirement_id": "req-001",
    "timeline": [
        {
            "timestamp": "2025-01-01T10:00:00Z",
            "operation": "created",
            "user": "alice",
            "changes": {"title": "User Auth"}
        },
        {
            "timestamp": "2025-01-02T14:30:00Z",
            "operation": "updated",
            "user": "bob",
            "changes": {"status": "active"}
        },
    ],
    "current_version": 2,
    "total_changes": 5
}
```

**Use Cases**:
- Audit trail
- Version history
- Change tracking
- Compliance reporting

**Query Performance**: <100ms

### Layer 6: Status Dashboard

**Purpose**: Aggregated metrics and KPIs

**Data Structure**:
```python
{
    "total_requirements": 150,
    "total_tested": 120,
    "total_implemented": 135,
    "coverage_percentage": 80,
    "test_coverage_percentage": 85,
    "implementation_coverage_percentage": 90,
    "status_breakdown": {
        "active": 100,
        "draft": 30,
        "deprecated": 20
    },
    "recent_changes": 5,
    "last_updated": "2025-01-15T10:00:00Z"
}
```

**Use Cases**:
- Executive dashboards
- Project status
- Metrics tracking
- KPI monitoring

**Query Performance**: <50ms

### Layer 7: Search Index

**Purpose**: Full-text search and fuzzy matching

**Data Structure**:
```python
{
    "requirement_id": "req-001",
    "title": "User Authentication",
    "description": "System shall authenticate users...",
    "search_text": "user authentication system authenticate users",
    "keywords": ["auth", "user", "login", "security"],
    "fuzzy_tokens": ["usr", "auth", "authn"],
    "last_indexed": "2025-01-15T10:00:00Z"
}
```

**Use Cases**:
- Quick requirement lookup
- Full-text search
- Fuzzy matching
- Autocomplete

**Query Performance**: <20ms

### Layer 8: Agent Interface

**Purpose**: Structured, queryable data for agents

**Data Structure**:
```python
{
    "requirement": {
        "id": "req-001",
        "title": "User Authentication",
        "status": "active",
        "metadata": {...}
    },
    "relationships": {
        "tests": ["test-001", "test-002"],
        "implements": ["file-001"],
        "depends_on": ["req-002"],
        "blocks": ["req-003"]
    },
    "metrics": {
        "test_coverage": 0.85,
        "code_coverage": 0.90,
        "impact_scope": 15
    },
    "queryable_fields": [
        "id", "title", "status", "created_at", "updated_at"
    ]
}
```

**Use Cases**:
- Agent queries
- Structured data access
- Programmatic interfaces
- API responses

**Query Performance**: <30ms

---

## 🔄 MULTI-VIEW SYNCHRONIZATION

### Synchronization Strategy

**Challenge**: Keep all views consistent with SSOT

**Solution**: Event-driven incremental updates

### Implementation

**1. Change Detection**:
```sql
-- Track all changes
CREATE TABLE change_events (
    id BIGSERIAL PRIMARY KEY,
    entity_type VARCHAR(50),
    entity_id UUID,
    operation VARCHAR(10),
    old_values JSONB,
    new_values JSONB,
    timestamp TIMESTAMP DEFAULT NOW()
);
```

**2. View Update Triggers**:
```python
# When requirement changes
def on_requirement_changed(req_id, changes):
    # Update all affected views
    update_traceability_matrix(req_id)
    update_impact_analysis(req_id)
    update_coverage_analysis(req_id)
    update_dependency_graph(req_id)
    update_timeline_view(req_id)
    update_status_dashboard()
    update_search_index(req_id)
    update_agent_interface(req_id)
```

**3. Incremental Refresh**:
```python
# Only refresh affected rows
def update_traceability_matrix(req_id):
    # Delete affected rows
    db.execute("""
        DELETE FROM traceability_matrix
        WHERE source_id = :req_id OR target_id = :req_id
    """, {"req_id": req_id})
    
    # Re-insert updated rows
    db.execute("""
        INSERT INTO traceability_matrix
        SELECT ... FROM requirements r1
        JOIN relationships rel ON r1.id = rel.source_id
        JOIN requirements r2 ON rel.target_id = r2.id
        WHERE r1.id = :req_id OR r2.id = :req_id
    """, {"req_id": req_id})
```

---

## 📈 CONSISTENCY MODELS

### Strong Consistency for SSOT

- All reads see latest writes
- ACID transactions
- Immediate consistency
- No stale data

### Eventual Consistency for Views

- Views eventually match SSOT
- Temporary staleness acceptable
- Refresh within seconds
- Configurable refresh frequency

### Hybrid Approach

```python
# Read from SSOT for critical data
def get_requirement(req_id):
    return db.query(Requirement).filter_by(id=req_id).first()

# Read from views for analytics
def get_impact_analysis(req_id):
    return db.query(ImpactAnalysisView).filter_by(source_id=req_id).all()

# Refresh views after changes
def update_requirement(req_id, **changes):
    req = db.query(Requirement).filter_by(id=req_id).first()
    for key, value in changes.items():
        setattr(req, key, value)
    db.commit()
    
    # Trigger view refresh
    refresh_views_for_requirement(req_id)
```

---

## 🎯 VIEW SELECTION STRATEGY

### When to Use Each View

**Traceability Matrix**:
- Need to see all links
- Verify bidirectional traceability
- Generate reports

**Impact Analysis**:
- Planning changes
- Risk assessment
- Regression testing

**Coverage Analysis**:
- Track metrics
- Find gaps
- Compliance reporting

**Dependency Graph**:
- Shortest path queries
- Critical path analysis
- Cycle detection

**Timeline View**:
- Audit trail
- Version history
- Change tracking

**Status Dashboard**:
- Executive reporting
- Project status
- KPI monitoring

**Search Index**:
- Quick lookups
- Full-text search
- Autocomplete

**Agent Interface**:
- Agent queries
- Programmatic access
- API responses

---

## 🚀 IMPLEMENTATION ROADMAP

### Phase 1: Core Layers (Week 1-2)
- ✅ Traceability Matrix
- ✅ Impact Analysis
- ✅ Coverage Analysis
- ✅ Dependency Graph

### Phase 2: Advanced Layers (Week 3)
- ✅ Timeline View
- ✅ Status Dashboard
- ✅ Search Index

### Phase 3: Agent Layer (Week 4)
- ✅ Agent Interface
- ✅ Structured queries
- ✅ API integration

### Phase 4: Optimization (Week 5)
- ✅ Performance tuning
- ✅ Caching strategy
- ✅ Load testing

---

## 📊 PERFORMANCE TARGETS

| Layer | Query Type | Target | Actual |
|-------|-----------|--------|--------|
| Traceability | Single req | <50ms | TBD |
| Impact | Full analysis | <100ms | TBD |
| Coverage | Single req | <50ms | TBD |
| Dependency | Graph query | <100ms | TBD |
| Timeline | Full history | <100ms | TBD |
| Dashboard | Aggregation | <50ms | TBD |
| Search | Full-text | <20ms | TBD |
| Agent | Structured | <30ms | TBD |

---

## 🎯 BENEFITS OF ATTACHED LAYERS

✅ **Performance** - Optimized queries for each use case
✅ **Flexibility** - Multiple perspectives of same data
✅ **Scalability** - Incremental updates scale
✅ **Consistency** - All views derived from SSOT
✅ **Maintainability** - Clear separation of concerns
✅ **Extensibility** - Easy to add new views
✅ **Reliability** - Automatic synchronization
✅ **Auditability** - Complete change history

---

## 🔗 NEXT STEPS

1. Design view schemas
2. Create materialized views
3. Implement change tracking
4. Set up incremental refresh
5. Optimize query performance
6. Add caching layer
7. Implement agent interface
8. Load test and optimize

