Architecture Assessment

Architecture Assessment

Systematic evaluation of codebase architecture including pattern recognition, anti-pattern detection, coupling/​cohesion analysis, scalability review, and technical debt identification.

Quick Start

Full architecture assessment:

Perform a comprehensive architecture assessment of this codebase, identifying patterns, anti-patterns, and improvement opportunities.

Pattern identification:

Identify the architectural patterns used in this project and evaluate how well they're implemented.

Technical debt analysis:

Analyze this codebase for technical debt and prioritize items for remediation.

Capabilities

1. Architecture Evaluation

Assess overall codebase architecture through structured analysis.

Evaluation Framework

1. STRUCTURE ANALYSIS
   - Directory organization
   - Module boundaries
   - Dependency flow
   - Layer separation

2. DESIGN PRINCIPLES
   - SOLID adherence
   - DRY compliance
   - Separation of concerns
   - Single responsibility

3. QUALITY ATTRIBUTES
   - Maintainability
   - Testability
   - Extensibility
   - Reliability

4. RISK ASSESSMENT
   - Complexity hotspots
   - Coupling issues
   - Change propagation
   - Failure domains

Architecture Health Score

Scoring rubric:

• 90-100: Excellent - Minor improvements only
• 70-89: Good - Some areas need attention
• 50-69: Fair - Significant improvements needed
• Below 50: Poor - Major refactoring required

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2. Pattern Recognition

Identify and evaluate architectural patterns in the codebase.

Pattern Detection Matrix

Pattern Evaluation Criteria

For each identified pattern, assess:

## Pattern: {Name}

### Implementation Quality
- [ ] Pattern applied consistently across codebase
- [ ] Clear boundaries between pattern components
- [ ] Dependencies flow in correct direction
- [ ] Abstractions used appropriately

### Deviations
- List specific violations or inconsistencies
- Note areas where pattern is partially implemented
- Identify technical debt from pattern drift

### Recommendations
- Specific actions to improve implementation
- Priority (High/​Medium/​Low)
- Estimated effort

See references/​architecture-patterns.md for detailed pattern analysis.

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3. Anti-Pattern Detection

Identify architectural anti-patterns that harm maintainability and scalability.

Critical Anti-Patterns

Detection Commands

# Circular dependency detection
npx madge --circular src/
pydeps --show-cycles src/

# God class detection (files > 500 lines)
find src -name "*.ts" -exec wc -l {} \; | awk '$1 > 500'

# Coupling analysis
npx dependency-cruiser --output-type dot src | dot -T svg > deps.svg

See references/​anti-patterns.md for comprehensive anti-pattern catalog.

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4. Coupling Analysis

Measure and evaluate coupling between modules.

Coupling Types (Worst to Best)

1. Content Coupling - Module modifies internal data of another
2. Common Coupling - Shared global state
3. Control Coupling - One module controls flow of another via flags
4. Stamp Coupling - Shared data structures with unused fields
5. Data Coupling - Only necessary data passed (ideal)
6. Message Coupling - Loosest, communication via messages only

Coupling Metrics

## Module Coupling Report

### Afferent Coupling (Ca) - Who depends on me?
| Module | Dependents | Risk Level |
|--------|------------|------------|
| core/​utils | 45 | HIGH - Changes break many |
| auth/​jwt | 12 | MEDIUM |
| ui/​Button | 8 | LOW |

### Efferent Coupling (Ce) - Who do I depend on?
| Module | Dependencies | Risk Level |
|--------|--------------|------------|
| pages/​Dashboard | 23 | HIGH - Fragile |
| services/​order | 8 | MEDIUM |
| utils/​format | 2 | LOW |

### Instability Index
I = Ce / (Ca + Ce)
- 0.0 = Maximally stable (many dependents, few dependencies)
- 1.0 = Maximally unstable (few dependents, many dependencies)

Coupling Reduction Strategies

See references/​metrics.md for coupling metric calculations.

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5. Cohesion Assessment

Evaluate how well modules focus on single responsibilities.

Cohesion Types (Best to Worst)

1. Functional - All elements contribute to single task (ideal)
2. Sequential - Output of one element is input to next
3. Communicational - Elements operate on same data
4. Procedural - Elements related by execution order
5. Temporal - Elements execute at same time
6. Logical - Elements related by category, not function
7. Coincidental - No meaningful relationship (worst)

LCOM4 Metric

Lack of Cohesion of Methods:

• LCOM = 0: Perfect cohesion
• LCOM = 1: Acceptable
• LCOM > 1: Low cohesion, consider splitting

Calculation:

LCOM4 = Number of connected components in method-field graph
- Each method is a node
- Edge exists if two methods share a field
- LCOM4 = number of disconnected subgraphs

Cohesion Assessment Template

## Cohesion Analysis: {ModuleName}

### Responsibility Inventory
1. {Responsibility 1}
2. {Responsibility 2}
...

### Cohesion Evaluation
- **Type**: {Functional|Sequential|etc.}
- **LCOM Score**: {0-N}
- **Field Usage Matrix**: Show which methods use which fields

### Recommendations
- [ ] Extract {Responsibility X} to new module
- [ ] Merge related methods
- [ ] Remove unrelated functionality

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6. Scalability Review

Assess architecture for horizontal and vertical scaling capability.

Scalability Dimensions

Scalability Anti-Patterns

Scalability Checklist

See checklists/​scalability-checklist.md for detailed assessment.

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7. Technical Debt Identification

Find, categorize, and prioritize technical debt.

Debt Categories

Debt Prioritization Matrix

              Impact
         Low    |    High
        +-------+--------+
High    | PLAN  | DO NOW |
Effort  +-------+--------+
Low     | DEFER | DO SOON|
        +-------+--------+

Debt Inventory Template

## Technical Debt Inventory

### Critical (Fix within 2 weeks)
| ID | Description | Category | Impact | Effort | Owner |
|----|-------------|----------|--------|--------|-------|
| TD-001 | Security vulnerabilities in auth | Security | Critical | 2d | @dev |

### High (Fix within quarter)
| ID | Description | Category | Impact | Effort | Owner |
|----|-------------|----------|--------|--------|-------|
| TD-002 | Circular dependency in core | Architecture | High | 1w | @team |

### Medium (Track and address opportunistically)
...

### Low (Accept or defer)
...

See checklists/​debt-assessment-checklist.md for systematic debt discovery.

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Assessment Workflows

Full Architecture Assessment

1. DISCOVERY (1-2 hours)
   [ ] Clone/​access repository
   [ ] Review documentation (README, ADRs, wiki)
   [ ] Interview stakeholders on pain points
   [ ] Identify key business domains

2. STATIC ANALYSIS (2-4 hours)
   [ ] Run complexity analysis (lizard, escomplex)
   [ ] Run dependency analysis (madge, pydeps)
   [ ] Check test coverage
   [ ] Audit dependencies

3. PATTERN ANALYSIS (1-2 hours)
   [ ] Identify primary architecture pattern
   [ ] Evaluate pattern adherence
   [ ] Document deviations

4. COUPLING/​COHESION (1-2 hours)
   [ ] Map module dependencies
   [ ] Calculate coupling metrics
   [ ] Assess module cohesion

5. ANTI-PATTERN SCAN (1-2 hours)
   [ ] Check for god classes
   [ ] Find circular dependencies
   [ ] Identify distributed monolith signs

6. SCALABILITY REVIEW (1-2 hours)
   [ ] Assess statelessness
   [ ] Review data access patterns
   [ ] Check async processing

7. DEBT INVENTORY (2-4 hours)
   [ ] Catalog all debt
   [ ] Prioritize by impact/​effort
   [ ] Estimate remediation costs

8. REPORT & RECOMMENDATIONS (2-4 hours)
   [ ] Compile findings
   [ ] Prioritize recommendations
   [ ] Create roadmap

Quick Health Check (30 min)

1. Structure scan - directory layout, layers
2. Complexity hotspots - top 5 complex files
3. Dependency health - vulnerabilities, outdated
4. Test coverage - overall percentage
5. Quick recommendations - top 3 issues

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Output Templates

Architecture Assessment Report

# Architecture Assessment: {Project Name}

## Executive Summary
- **Overall Health Score**: {X}/​100
- **Primary Pattern**: {Pattern Name}
- **Critical Issues**: {Count}
- **Recommended Actions**: {Top 3}

## Assessment Details

### 1. Architecture Overview
- Pattern: {Identified pattern}
- Layers: {Layer breakdown}
- Key Components: {List}

### 2. Strengths
- {Strength 1}
- {Strength 2}

### 3. Concerns
| Priority | Issue | Impact | Recommendation |
|----------|-------|--------|----------------|
| Critical | ... | ... | ... |
| High | ... | ... | ... |

### 4. Metrics Summary
| Metric | Current | Target | Status |
|--------|---------|--------|--------|
| Avg Cyclomatic Complexity | 12 | <10 | WARN |
| Test Coverage | 65% | >80% | WARN |
| Dependency Health | 3 vulns | 0 | FAIL |

### 5. Recommendations Roadmap
#### Immediate (0-2 weeks)
1. ...

#### Short-term (1-3 months)
1. ...

#### Long-term (3-12 months)
1. ...

### 6. Technical Debt Summary
- Total Items: {count}
- Estimated Remediation: {time}
- Priority Distribution: {Critical: X, High: Y, Medium: Z}

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Tool Integration

Static Analysis Commands

# JavaScript/​TypeScript
npx escomplex src/ --format json > complexity.json
npx madge --circular --extensions ts src/
npx dependency-cruiser --output-type json src/ > deps.json

# Python
radon cc src/ -a -j > complexity.json
radon mi src/ -j > maintainability.json
pydeps src/ --cluster --max-bacon 2

# Go
gocyclo -over 10 ./​...
gocognit -over 15 ./​...

# Multi-language
lizard src/ -l python -l javascript --CCN 15

# Dependency health
npm audit --json
pip-audit --format=json

Visualization

# Dependency graphs
npx madge --image deps.png src/
npx dependency-cruiser --output-type dot src | dot -T svg > deps.svg

# Architecture diagrams
npx arkit -o architecture.svg

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Reference Files

• references/​architecture-patterns.md - Detailed pattern catalog and evaluation criteria
• references/​anti-patterns.md - Anti-pattern detection and remediation
• references/​metrics.md - Coupling, cohesion, and complexity metrics
• checklists/​scalability-checklist.md - Scalability assessment checklist
• checklists/​debt-assessment-checklist.md - Technical debt discovery checklist