component-identification-sizing（组件识别尺寸）

Component Identification and Sizing

This skill identifies architectural components (logical building blocks) in a codebase and calculates size metrics to assess decomposition feasibility and identify oversized components.

How to Use

Quick Start

Request analysis of your codebase:

• "Identify and size all components in this codebase"
• "Find oversized components that need splitting"
• "Create a component inventory for decomposition planning"
• "Analyze component size distribution"

Usage Examples

Example 1: Complete Analysis

User: "Identify and size all components in this codebase"

The skill will:
1. Map directory/namespace structures
2. Identify all components (leaf nodes)
3. Calculate size metrics (statements, files, percentages)
4. Generate component inventory table
5. Flag oversized/undersized components
6. Provide recommendations

Example 2: Find Oversized Components

User: "Which components are too large?"

The skill will:
1. Calculate mean and standard deviation
2. Identify components >2 std dev or >10% threshold
3. Analyze functional areas within large components
4. Suggest specific splits with estimated sizes

Example 3: Component Size Analysis

User: "Analyze component sizes and distribution"

The skill will:
1. Calculate all size metrics
2. Generate size distribution summary
3. Identify outliers
4. Provide statistics and recommendations

Step-by-Step Process

1. Initial Analysis: Start with complete component inventory
2. Identify Issues: Find components that need attention
3. Get Recommendations: Request actionable split/consolidation suggestions
4. Monitor Progress: Track component growth over time

When to Use

Apply this skill when:

• Starting a monolithic decomposition effort
• Assessing codebase structure and organization
• Identifying components that are too large or too small
• Creating component inventory for migration planning
• Analyzing code distribution across components
• Preparing for component-based decomposition patterns

Core Concepts

Component Definition

A component is an architectural building block that:

• Has a well-defined role and responsibility
• Is identified by a namespace, package structure, or directory path
• Contains source code files (classes, functions, modules) grouped together
• Performs specific business or infrastructure functionality

Key Rule: Components are identified by leaf nodes in directory/namespace structures. If a namespace is extended (e.g., services/billing extended to services/billing/payment), the parent becomes a subdomain, not a component.

Size Metrics

Statements (not lines of code):

• Count executable statements terminated by semicolons or newlines
• More accurate than lines of code for size comparison
• Accounts for code complexity, not formatting

Component Size Indicators:

• Percent of codebase: Component statements / Total statements
• File count: Number of source files in component
• Standard deviation: Distance from mean component size

Analysis Process

Phase 1: Identify Components

Scan the codebase directory structure:

1. Map directory/namespace structure

- For Node.js: services/, routes/, models/, utils/ - For Java: Package structure (e.g., com.company.domain.service) - For Python: Module paths (e.g., app/billing/payment)

1. Identify leaf nodes

- Components are the deepest directories containing source files - Example: services/BillingService/ is a component - Example: services/BillingService/payment/ extends it, making BillingService a subdomain

1. Create component inventory

- List each component with its namespace/path - Note any parent namespaces (subdomains)

Phase 2: Calculate Size Metrics

For each component:

1. Count statements

- Parse source files in component directory - Count executable statements (not comments, blank lines, or declarations alone) - Sum across all files in component

1. Count files

- Total source files (.js, .ts, .java, .py, etc.) - Exclude test files, config files, documentation

1. Calculate percentage component_percent = (component_statements / total_statements) * 100
2. Calculate statistics

- Mean component size: total_statements / number_of_components - Standard deviation: sqrt(sum((size - mean)^2) / (n - 1)) - Component's deviation: (component_size - mean) / std_dev

Phase 3: Identify Size Issues

Oversized Components (candidates for splitting):

• Exceeds 30% of total codebase (for small apps with <10 components)
• Exceeds 10% of total codebase (for large apps with >20 components)
• More than 2 standard deviations above mean
• Contains multiple distinct functional areas

Undersized Components (candidates for consolidation):

• Less than 1% of codebase (may be too granular)
• Less than 1 standard deviation below mean
• Contains only a few files with minimal functionality

Well-Sized Components:

• Between 1-2 standard deviations from mean
• Represents a single, cohesive functional area
• Appropriate percentage for application size

Output Format

Component Inventory Table

## Component Inventory

| Component Name  | Namespace/Path               | Statements | Files | Percent | Status       |
| --------------- | ---------------------------- | ---------- | ----- | ------- | ------------ |
| Billing Payment | services/BillingService      | 4,312      | 23    | 5%      | ✅ OK        |
| Reporting       | services/ReportingService    | 27,765     | 162   | 33%     | ⚠️ Too Large |
| Notification    | services/NotificationService | 1,433      | 7     | 2%      | ✅ OK        |

Status Legend:

• ✅ OK: Well-sized (within 1-2 std dev from mean)
• ⚠️ Too Large: Exceeds size threshold or >2 std dev above mean
• 🔍 Too Small: <1% of codebase or <1 std dev below mean

Size Analysis Summary

## Size Analysis Summary

**Total Components**: 18
**Total Statements**: 82,931
**Mean Component Size**: 4,607 statements
**Standard Deviation**: 5,234 statements

**Oversized Components** (>2 std dev or >10%):

- Reporting (33% - 27,765 statements) - Consider splitting into:
  - Ticket Reports
  - Expert Reports
  - Financial Reports

**Well-Sized Components** (within 1-2 std dev):

- Billing Payment (5%)
- Customer Profile (5%)
- Ticket Assignment (9%)

**Undersized Components** (<1 std dev):

- Login (2% - 1,865 statements) - Consider consolidating with Authentication

Component Size Distribution

## Component Size Distribution

Component Size Distribution (by percent of codebase)

[Visual representation or histogram if possible]

Largest: ████████████████████████████████████ 33% (Reporting) ████████ 9% (Ticket Assign) ██████ 8% (Ticket) ██████ 6% (Expert Profile) █████ 5% (Billing Payment) ████ 4% (Billing History)...

### Recommendations

Recommendations

High Priority: Split Large Components

Reporting Component (33% of codebase):

• Current: Single component with 27,765 statements
• Issue: Too large, contains multiple functional areas
• Recommendation: Split into:

1. Reporting Shared (common utilities) 2. Ticket Reports (ticket-related reports) 3. Expert Reports (expert-related reports) 4. Financial Reports (financial reports)

• Expected Result: Each component ~7-9% of codebase

Medium Priority: Review Small Components

Login Component (2% of codebase):

• Current: 1,865 statements, 3 files
• Consideration: May be too granular if related to broader authentication
• Recommendation: Evaluate if should be consolidated with Authentication/User components

Low Priority: Monitor Well-Sized Components

Most components are appropriately sized. Continue monitoring during decomposition.

## Analysis Checklist

**Component Identification**:

- Mapped all directory/namespace structures
- Identified leaf nodes (components) vs parent nodes (subdomains)
- Created complete component inventory
- Documented namespace/path for each component

**Size Calculation**:

- Counted statements (not lines) for each component
- Counted source files (excluding tests/configs)
- Calculated percentage of total codebase
- Calculated mean and standard deviation

**Size Assessment**:

- Identified oversized components (>threshold or >2 std dev)
- Identified undersized components (<1% or <1 std dev)
- Flagged components for splitting or consolidation
- Documented size distribution

**Recommendations**:

- Suggested splits for oversized components
- Suggested consolidations for undersized components
- Prioritized recommendations by impact
- Created architecture stories for refactoring

## Implementation Notes

### For Node.js/Express Applications

Components typically found in:

- `services/` - Business logic components
- `routes/` - API endpoint components
- `models/` - Data model components
- `utils/` - Utility components
- `middleware/` - Middleware components

**Example Component Identification**:

services/ ├── BillingService/ ← Component (leaf node) │ ├── index.js │ └── BillingService.js ├── CustomerService/ ← Component (leaf node) │ └── CustomerService.js └── NotificationService/ ← Component (leaf node) └── NotificationService.js

### For Java Applications

Components identified by package structure:

- `com.company.domain.service` - Service components
- `com.company.domain.model` - Model components
- `com.company.domain.repository` - Repository components

**Example Component Identification**:

com.company.billing.payment ← Component (leaf package) com.company.billing.history ← Component (leaf package) com.company.billing ← Subdomain (parent of payment/history)

### Statement Counting

**JavaScript/TypeScript**:

- Count statements terminated by `;` or newline
- Include: assignments, function calls, returns, conditionals, loops
- Exclude: comments, blank lines, declarations without assignment

**Java**:

- Count statements terminated by `;`
- Include: method calls, assignments, returns, conditionals
- Exclude: class/interface declarations, comments, blank lines

**Python**:

- Count executable statements (not comments or blank lines)
- Include: assignments, function calls, returns, conditionals
- Exclude: docstrings, comments, blank lines

## Fitness Functions

After identifying and sizing components, create automated checks:

### Component Size Threshold

// Alert if any component exceeds 10% of codebase function checkComponentSize(components, threshold = 0.1) { const totalStatements = components.reduce((sum, c) => sum + c.statements, 0) return components .filter((c) => c.statements / totalStatements > threshold) .map((c) => ({ component: c.name, percent: ((c.statements / totalStatements) * 100).toFixed(1), issue: 'Exceeds size threshold', })) }

### Standard Deviation Check

// Alert if component is >2 standard deviations from mean function checkStandardDeviation(components) { const sizes = components.map((c) => c.statements) const mean = sizes.reduce((a, b) => a + b, 0) / sizes.length const stdDev = Math.sqrt(sizes.reduce((sum, size) => sum + Math.pow(size - mean, 2), 0) / (sizes.length - 1))

return components .filter((c) => Math.abs(c.statements - mean) > 2 * stdDev) .map((c) => ({ component: c.name, deviation: ((c.statements - mean) / stdDev).toFixed(2), issue: 'More than 2 standard deviations from mean', })) }

## Best Practices

### Do's ✅

- Use statements, not lines of code
- Identify components as leaf nodes only
- Calculate both percentage and standard deviation
- Consider application size when setting thresholds
- Document namespace/path for each component
- Create visual size distribution if possible

### Don'ts ❌

- Don't count test files in component size
- Don't treat parent directories as components
- Don't use fixed thresholds without considering app size
- Don't ignore small components (may need consolidation)
- Don't skip standard deviation calculation
- Don't mix infrastructure and domain components in same analysis

## Next Steps

After completing component identification and sizing:

1. **Apply Gather Common Domain Components Pattern** - Identify duplicate functionality
2. **Apply Flatten Components Pattern** - Remove orphaned classes from root namespaces
3. **Apply Determine Component Dependencies Pattern** - Analyze coupling between components
4. **Create Component Domains** - Group components into logical domains

## Notes

- Component size thresholds vary by application size
- Small apps (<10 components): 30% threshold may be appropriate
- Large apps (>20 components): 10% threshold is more appropriate
- Standard deviation is more reliable than fixed percentages
- Well-sized components are 1-2 standard deviations from mean
- Oversized components often contain multiple functional areas that can be split