component-identification-sizing

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