# Automated Code Review with TRUST 5 Validation

> Module: AI-powered automated code review with TRUST 5 validation framework and comprehensive quality analysis
> Complexity: Advanced
> Time: 35+ minutes
> Dependencies: Python 3.8+, Context7 MCP, ast, pylint, flake8, bandit, mypy

## Quick Reference

### Core Capabilities

The automated code review system provides comprehensive code quality analysis across multiple dimensions:

TRUST 5 Framework:
- Truthfulness: Code correctness and logic accuracy validation
- Relevance: Requirements fulfillment and purpose alignment checking
- Usability: Maintainability and understandability assessment
- Safety: Security vulnerability and error handling detection
- Timeliness: Performance standards and modern practices verification

Static Analysis Integration:
- pylint: Code quality and style checking
- flake8: Style guide enforcement
- bandit: Security vulnerability scanning
- mypy: Type checking and validation

Context7-Enhanced Analysis:
- Up-to-date security patterns from OWASP and Semgrep
- Performance anti-patterns from profiling best practices
- Code quality patterns from SonarQube standards
- TRUST 5 validation framework patterns

### Key Components

```python
from moai_workflow_testing.automated_code_review import (
    AutomatedCodeReviewer,
    CodeReviewReport,
    TrustCategory,
    Severity,
    IssueType
)

# Initialize automated code reviewer
reviewer = AutomatedCodeReviewer(context7_client=context7)

# Review entire codebase
report = await reviewer.review_codebase(
    project_path="/path/to/project",
    include_patterns=["/*.py"],
    exclude_patterns=["/tests/", "/__pycache__/"]
)

print(f"Overall TRUST Score: {report.overall_trust_score:.2f}")
print(f"Files Reviewed: {report.summary_metrics['files_reviewed']}")
print(f"Total Issues: {report.summary_metrics['total_issues']}")
print(f"Critical Issues: {report.summary_metrics['critical_issues']}")
```

### TRUST 5 Scores

The review system calculates scores for each TRUST category:

```python
for category, score in report.overall_category_scores.items():
    print(f"{category.value}: {score:.2f}")
```

Category Score Calculation:
- Scores range from 0.0 to 1.0
- Penalties applied based on issue severity and confidence
- Weighted average for overall score
- Category weights: Truthfulness (25%), Relevance (20%), Usability (25%), Safety (20%), Timeliness (10%)

### Issue Severity Levels

Critical: Security vulnerabilities, syntax errors, data loss risks
High: Complex logic issues, major performance problems, significant safety concerns
Medium: Code smells, maintainability issues, moderate performance problems
Low: Style violations, minor documentation issues, small optimizations
Info: Suggestions and best practice recommendations

---

## Implementation Guide

### Basic Code Review Workflow

Step 1: Initialize the automated code reviewer with optional Context7 client for enhanced pattern detection

Step 2: Review the codebase by specifying:
- Project path to analyze
- Include patterns for files to review (default: ["/*.py"])
- Exclude patterns for directories to skip (default: ["/__pycache__/", "/venv/", "/tests/"])

Step 3: Analyze the generated report which includes:
- Overall TRUST score across all categories
- Per-file review results with individual issues
- Summary metrics with issue counts by severity and category
- Critical issues requiring immediate attention
- Actionable recommendations prioritized by impact

### Single File Review

For reviewing individual files:

```python
file_result = await reviewer.review_single_file("/path/to/file.py")
print(f"File Trust Score: {file_result.trust_score:.2f}")
print(f"Issues found: {len(file_result.issues)}")
print(f"Lines of code: {file_result.lines_of_code}")
```

### Understanding Code Issues

Each issue detected includes:

```python
for issue in file_result.issues:
    print(f"Category: {issue.category.value}")
    print(f"Severity: {issue.severity.value}")
    print(f"Type: {issue.issue_type.value}")
    print(f"Title: {issue.title}")
    print(f"Description: {issue.description}")
    print(f"Location: {issue.file_path}:{issue.line_number}")
    print(f"Code snippet: {issue.code_snippet}")
    print(f"Suggested fix: {issue.suggested_fix}")
    print(f"Confidence: {issue.confidence:.2f}")
    if issue.rule_violated:
        print(f"Rule violated: {issue.rule_violated}")
    if issue.external_reference:
        print(f"Reference: {issue.external_reference}")
```

### Customizing Analysis Patterns

Configure analysis patterns to match project standards:

```python
# Access analysis patterns
patterns = await reviewer.context7_analyzer.load_analysis_patterns()

# Customize quality thresholds
patterns['quality']['long_functions']['max_lines'] = 100
patterns['quality']['complex_conditionals']['max_complexity'] = 15
patterns['quality']['deep_nesting']['max_depth'] = 5

# Run review with custom patterns
reviewer.analysis_patterns = patterns
report = await reviewer.review_codebase(project_path)
```

---

## Advanced Modules

For detailed implementation and advanced features, see the specialized modules:

### TRUST 5 Validation Framework

See [trust5-validation.md](./trust5-validation.md) for:
- Complete TRUST 5 category implementations
- Custom validation rules and patterns
- Category-specific analysis methods
- Score calculation algorithms
- Penalty and weight customization

### Static Analysis Integration

See [static-analysis.md](./static-analysis.md) for:
- pylint, flake8, bandit, mypy integration details
- Tool configuration and customization
- Result parsing and normalization
- Tool-to-TRUST category mapping
- Error handling and fallback strategies

### Security Analysis

See [security-analysis.md](./security-analysis.md) for:
- Context7-enhanced security pattern detection
- OWASP Top 10 vulnerability scanning
- SQL injection, command injection, path traversal detection
- Security fix suggestions with references
- Business logic vulnerability analysis

### Quality Metrics

See [quality-metrics.md](./quality-metrics.md) for:
- Function length and complexity analysis
- Nesting depth detection
- Cyclomatic complexity calculation
- Code metrics and statistics
- Maintainability indices

### Advanced TRUST 5 Framework

See [automated-code-review/trust5-framework.md](./automated-code-review/trust5-framework.md) for:
- Deep dive into TRUST 5 methodology
- Category-specific analysis patterns
- Advanced scoring algorithms
- Custom rule creation
- Integration with external validation tools

### Context7 Integration

See [automated-code-review/context7-integration.md](./automated-code-review/context7-integration.md) for:
- Context7 MCP integration patterns
- Real-time pattern loading
- Security vulnerability databases
- Performance optimization libraries
- Code quality standards integration

### Review Workflows

See [automated-code-review/review-workflows.md](./automated-code-review/review-workflows.md) for:
- CI/CD pipeline integration
- Automated review workflows
- Report generation and formatting
- Team collaboration patterns
- Continuous quality monitoring

---

## Best Practices

1. Comprehensive Coverage: Analyze code across all TRUST 5 dimensions for complete quality assessment
2. Context Integration: Leverage Context7 for up-to-date security and quality patterns
3. Actionable Feedback: Provide specific, implementable suggestions with code examples
4. Severity Prioritization: Focus on critical and high-severity issues first for maximum impact
5. Continuous Integration: Integrate into CI/CD pipeline for automated reviews on every commit
6. Custom Thresholds: Adjust analysis thresholds to match project standards and team preferences
7. Regular Updates: Keep Context7 patterns current for latest vulnerability detection
8. Team Consistency: Use consistent review rules across entire codebase for uniform quality

---

## Related Modules

- [Smart Refactoring](./smart-refactoring.md): Automated refactoring with code quality improvements
- [Performance Optimization](./performance-optimization.md): Performance profiling and bottleneck detection
- [AI Debugging](./ai-debugging.md): AI-powered debugging and error resolution

---

## Module Structure

```
automated-code-review.md (this file)
├── trust5-validation.md (TRUST 5 framework implementation)
├── static-analysis.md (pylint, flake8, bandit, mypy integration)
├── security-analysis.md (security vulnerability detection)
├── quality-metrics.md (code quality, complexity, metrics)
└── automated-code-review/
    ├── trust5-framework.md (deep dive into TRUST 5 categories)
    ├── context7-integration.md (Context7 MCP integration)
    └── review-workflows.md (CI/CD and team workflows)
```

---

Version: 2.0.0 (Modular Structure)
Last Updated: 2026-01-06
Module: `modules/automated-code-review.md`
