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

Initial Analysis: Start with complete component inventory
Identify Issues: Find components that need attention
Get Recommendations: Request actionable split/consolidation suggestions
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:

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

Phase 2: Calculate Size Metrics

For each component:

Count statements
- Parse source files in component directory
- Count executable statements (not comments, blank lines, or declarations alone)
- Sum across all files in component
Count files
- Total source files (.js, .ts, .java, .py, etc.)
- Exclude test files, config files, documentation

Calculate percentage

component_percent = (component_statements / total_statements) * 100

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

```markdown
## 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:

Apply Gather Common Domain Components Pattern - Identify duplicate functionality
Apply Flatten Components Pattern - Remove orphaned classes from root namespaces
Apply Determine Component Dependencies Pattern - Analyze coupling between components
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

component-identification-sizing