wheels analyze

Base command for code analysis and quality checks.

Synopsis

wheels analyze [subcommand] [options]

Description

The wheels analyze command provides comprehensive code analysis tools for Wheels applications. It helps identify code quality issues, performance bottlenecks, security vulnerabilities, and provides actionable insights for improvement.

Subcommands

Command	Description
code	Analyze code quality and patterns
performance	Analyze performance characteristics
security	Security vulnerability analysis (deprecated)

Options

Option	Description
--help	Show help information
--version	Show version information

Direct Usage

When called without subcommands, runs all analyses:

wheels analyze

This executes:

1. Code quality analysis

2. Performance analysis

3. Security scanning (if not deprecated)

Examples

Run all analyses

wheels analyze

Quick analysis with summary

wheels analyze --summary

Analyze specific directory

wheels analyze --path=./models

Generate analysis report

wheels analyze --report=html --output=./analysis-report

Analysis Overview

The analyze command examines:

Code Quality

• Coding standards compliance

• Code complexity metrics

• Duplication detection

• Best practices adherence

Performance

• N+1 query detection

• Slow query identification

• Memory usage patterns

• Cache effectiveness

Security

• SQL injection risks

• XSS vulnerabilities

• Insecure configurations

• Outdated dependencies

Output Example

Wheels Code Analysis Report
==========================

Code Quality
------------
✓ Files analyzed: 234
✓ Total lines: 12,456
⚠ Issues found: 23
  - High priority: 3
  - Medium priority: 12
  - Low priority: 8

Performance
-----------
✓ Queries analyzed: 156
⚠ Potential N+1 queries: 4
⚠ Slow queries detected: 2
✓ Cache hit ratio: 87%

Security (Deprecated)
--------------------
! Security analysis has been deprecated
! Use 'wheels security scan' instead

Summary Score: B+ (82/100)

Analysis Configuration

Configure via .wheels-analysis.json:

{
  "analyze": {
    "exclude": [
      "vendor/**",
      "tests/**",
      "*.min.js"
    ],
    "rules": {
      "complexity": {
        "maxComplexity": 10,
        "maxDepth": 4
      },
      "duplication": {
        "minLines": 5,
        "threshold": 0.05
      }
    },
    "performance": {
      "slowQueryThreshold": 1000,
      "cacheTargetRatio": 0.8
    }
  }
}

Integration with CI/CD

GitHub Actions Example

- name: Run code analysis
  run: |
    wheels analyze --format=json --output=analysis.json
    wheels analyze --format=badge > analysis-badge.svg

Quality Gates

Set minimum scores:

wheels analyze --min-score=80 --fail-on-issues=high

Report Formats

HTML Report

wheels analyze --report=html

• Interactive dashboard

• Detailed issue breakdown

• Code snippets with issues

JSON Report

wheels analyze --format=json

• Machine-readable format

• CI/CD integration

• Custom processing

Markdown Report

wheels analyze --format=markdown

• Documentation-friendly

• Pull request comments

• Wiki integration

Analysis Rules

Built-in Rules

• CFScript best practices

• SQL query optimization

• Security patterns

• Memory management

Custom Rules

Create custom rules in .wheels-analysis-rules/:

module.exports = {
  name: "custom-rule",
  check: function(file, content) {
    // Rule implementation
  }
};

Baseline

Track improvement over time:

# Create baseline
wheels analyze --save-baseline

# Compare with baseline
wheels analyze --compare-baseline

Ignoring Issues

Inline Comments

// wheels-analyze-ignore-next-line
complexQuery = ormExecuteQuery(sql, params);

/* wheels-analyze-ignore-start */
// Complex code block
/* wheels-analyze-ignore-end */

Configuration File

{
  "ignore": [
    {
      "rule": "sql-injection",
      "file": "legacy/*.cfc"
    }
  ]
}

Performance Tips

1. Incremental Analysis: Analyze only changed files

2. Parallel Processing: Use multiple cores

3. Cache Results: Reuse analysis for unchanged files

4. Focused Scans: Target specific directories

Use Cases

1. Pre-commit Hooks: Catch issues before commit

2. Pull Request Checks: Automated code review

3. Technical Debt: Track and reduce over time

4. Team Standards: Enforce coding guidelines

5. Performance Monitoring: Identify bottlenecks

Best Practices

1. Run analysis regularly

2. Fix high-priority issues first

3. Set realistic quality gates

4. Track metrics over time

5. Integrate with development workflow

Troubleshooting

Analysis Takes Too Long

• Exclude vendor directories

• Use incremental mode

• Increase memory allocation

Too Many False Positives

• Tune rule sensitivity

• Add specific ignores

• Update rule definitions

Notes

• First run may take longer due to initial scanning

• Results are cached for performance

• Some rules require database connection

• Memory usage scales with codebase size

See Also

• wheels analyze code - Code quality analysis
• wheels analyze performance - Performance analysis
• wheels security scan - Security scanning
• wheels test - Run tests