code-metrics-analysis

name	code-metrics-analysis
description	Analyze code complexity, cyclomatic complexity, maintainability index, and code churn using metrics tools. Use when assessing code quality, identifying refactoring candidates, or monitoring technical debt.

Code Metrics Analysis

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Measure and analyze code quality metrics to identify complexity, maintainability issues, and areas for improvement.

When to Use

• Code quality assessment
• Identifying refactoring candidates
• Technical debt monitoring
• Code review automation
• CI/CD quality gates
• Team performance tracking
• Legacy code analysis

Quick Start

Minimal working example:

import * as ts from "typescript";
import * as fs from "fs";

interface ComplexityMetrics {
  cyclomaticComplexity: number;
  cognitiveComplexity: number;
  linesOfCode: number;
  functionCount: number;
  classCount: number;
  maxNestingDepth: number;
}

class CodeMetricsAnalyzer {
  analyzeFile(filePath: string): ComplexityMetrics {
    const sourceCode = fs.readFileSync(filePath, "utf-8");
    const sourceFile = ts.createSourceFile(
      filePath,
      sourceCode,
      ts.ScriptTarget.Latest,
      true,
    );

    const metrics: ComplexityMetrics = {
      cyclomaticComplexity: 0,
      cognitiveComplexity: 0,
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide	Contents
TypeScript Complexity Analyzer	TypeScript Complexity Analyzer
Python Code Metrics (using radon)	Python Code Metrics (using radon)
ESLint Plugin for Complexity	ESLint Plugin for Complexity
CI/CD Quality Gates	CI/CD Quality Gates

Best Practices

✅ DO

• Monitor metrics over time
• Set reasonable thresholds
• Focus on trends, not absolute numbers
• Automate metric collection
• Use metrics to guide refactoring
• Combine multiple metrics
• Include metrics in code reviews

❌ DON'T

• Use metrics as sole quality indicator
• Set unrealistic thresholds
• Ignore context and domain
• Punish developers for metrics
• Focus only on one metric
• Skip documentation