Rule-Based Code Review Assistant

An intelligent, rule-based code review automation tool that enhances code quality through customizable analysis patterns.

Table of Contents

• Overview
• Architecture
• Features
• Installation
• Usage
• Configuration
• Rule Engine
• API Reference
• Testing
• Contributing
• Performance
• Roadmap
• License

Overview

The Rule-Based Code Review Assistant is a sophisticated automation tool designed to streamline the code review process through intelligent pattern recognition and customizable rule sets. It analyzes codebases against predefined quality standards, security patterns, and best practices to provide comprehensive feedback.

This tool helps development teams maintain consistent coding standards and catch common problems before they reach production, significantly reducing manual review time while improving code quality.

Architecture

The system follows a modular architecture with the following core components:

• Code Parser: Analyzes source code structure and syntax
• Rule Engine: Executes customizable rules and patterns
• Pattern Matcher: Detects code patterns and anti-patterns
• Security Scanner: Identifies potential security vulnerabilities
• Quality Analyzer: Evaluates code complexity and maintainability
• Report Generator: Creates detailed analysis reports
• GitHub Integration: Provides seamless CI/CD workflow integration

Features

Core Capabilities

• Rule-Based Analysis: Customizable rule engine for pattern detection
• Security Scanning: Built-in security vulnerability detection
• Code Quality Metrics: Complexity analysis and quality scoring
• CI/CD Integration: Seamless integration with popular CI/CD platforms
• Detailed Reporting: Comprehensive reports with actionable insights
• Real-time Processing: Fast analysis with minimal performance impact

Advanced Features

• Custom Rule Creation: Define your own analysis patterns
• Trend Analysis: Track code quality improvements over time
• GitHub Integration: Automated PR comments and reviews
• Configurable Severity Levels: Customize warning and error thresholds
• Multi-language Support: Support for Python, JavaScript, Java, and more
• Incremental Analysis: Analyze only changed files for efficiency

Installation

Prerequisites

• Python 3.8 or higher
• Git
• GitHub Token (for GitHub integration)

Standard Installation

# Clone the repository
git clone https://github.com/NoLongerHumanHQ/Rule-Based-Code-Review_Assistant.git
cd Rule-Based-Code-Review_Assistant

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run setup script
python setup.py install

Docker Installation

# Build Docker image
docker build -t code-review-assistant .

# Run container
docker run -d -p 8080:8080 \
  -e GITHUB_TOKEN=your_token \
  -e CONFIG_PATH=/app/config \
  code-review-assistant

Usage

Command Line Interface

# Analyze a single file
code-review-assistant analyze --file src/main.py

# Analyze entire project
code-review-assistant analyze --project /path/to/project

# Generate report
code-review-assistant report --format html --output ./reports/

# Run with custom rules
code-review-assistant analyze --rules custom_rules.yaml --project .

GitHub Actions Integration

# .github/workflows/code-review.yml
name: Automated Code Review

on: [pull_request]

jobs:
  code-review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run Code Review Assistant
        uses: NoLongerHumanHQ/Rule-Based-Code-Review_Assistant@v1
        with:
          github-token: ${{ secrets.GITHUB_TOKEN }}
          config-path: ./.code-review-config.yaml

Python API

from code_review_assistant import CodeReviewer, RuleEngine

# Initialize the reviewer
reviewer = CodeReviewer(
    rules_path="./rules/",
    config_path="./config.yaml"
)

# Analyze code
results = reviewer.analyze_file("src/example.py")

# Generate report
report = reviewer.generate_report(results, format="json")
print(report)

Configuration

Main Configuration File

# config.yaml
analyzer:
  languages: ["python", "javascript", "java"]
  max_complexity: 10
  min_coverage: 80

rules:
  security:
    enabled: true
    level: "strict"
  quality:
    enabled: true
    level: "standard"
  style:
    enabled: true
    level: "relaxed"

github:
  auto_comment: true
  severity_threshold: "warning"

reporting:
  format: ["html", "json"]
  include_suggestions: true
  output_path: "./reports/"

Custom Rules Definition

# custom_rules.yaml
rules:
  - name: "no_hardcoded_passwords"
    type: "security"
    pattern: "password\\s*=\\s*['\"][^'\"]+['\"]"
    severity: "critical"
    message: "Hardcoded passwords detected"

  - name: "max_function_length"
    type: "quality"
    max_lines: 50
    severity: "warning"
    message: "Function exceeds maximum length of 50 lines"

Rule Engine

Rule Categories

Category	Description	Examples
Security	Vulnerability detection	SQL injection, XSS, hardcoded secrets
Quality	Code quality metrics	Complexity, duplication, test coverage
Style	Coding standards	Naming conventions, formatting
Performance	Performance issues	Inefficient loops, memory leaks
Documentation	Documentation standards	Missing docstrings, outdated comments

Creating Custom Rules

from code_review_assistant.rules import BaseRule

class CustomSecurityRule(BaseRule):
    def __init__(self):
        super().__init__(
            name="custom_security_check",
            category="security",
            severity="high"
        )

    def analyze(self, code_fragment):
        # Your analysis logic here
        pass

API Reference

Core Classes

• CodeReviewer: Main interface for code analysis
• RuleEngine: Manages and executes rules
• ReportGenerator: Creates analysis reports
• GitHubIntegration: Handles GitHub API interactions

Sample Output

Console Output

Code Review Assistant v2.1.0
Analyzing: /project/src/
Files analyzed: 42
Warnings: 8
Errors: 2
Security issues: 1

Summary:
┌─────────────────┬───────┬─────────┬────────┐
│ Category        │ Count │ High    │ Medium │
├─────────────────┼───────┼─────────┼────────┤
│ Security        │ 1     │ 1       │ 0      │
│ Quality         │ 6     │ 0       │ 4      │
│ Style           │ 3     │ 0       │ 2      │
└─────────────────┴───────┴─────────┴────────┘

Detailed Report: ./reports/review_2024-01-15.html

JSON Output

{
  "metadata": {
    "timestamp": "2024-01-15T10:30:00Z",
    "version": "2.1.0",
    "total_files": 42,
    "total_lines": 1250
  },
  "summary": {
    "errors": 2,
    "warnings": 8,
    "info": 5,
    "security_issues": 1
  },
  "findings": [
    {
      "file": "src/auth.py",
      "line": 45,
      "column": 12,
      "rule": "hardcoded_password",
      "severity": "critical",
      "message": "Hardcoded password detected",
      "suggestion": "Use environment variables or secure key management"
    }
  ]
}

Testing

# Run all tests
python -m pytest

# Run with coverage
python -m pytest --cov=code_review_assistant

# Run specific test category
python -m pytest tests/test_rules.py -v

Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

# Fork and clone the repository
git clone https://github.com/yourusername/Rule-Based-Code-Review_Assistant.git

# Install development dependencies
pip install -r requirements-dev.txt

# Install pre-commit hooks
pre-commit install

# Run tests
make test

Performance

Metric	Value
Analysis Speed	~1000 lines/second
Memory Usage	<50MB for typical projects
Accuracy	95%+ for built-in rules
False Positive Rate	<5%

Roadmap

• v2.2 - Machine Learning integration for smart suggestions
• v2.3 - VS Code extension
• v2.4 - GitLab and Bitbucket integration
• v2.5 - Natural language rule definition
• v3.0 - AI-powered code improvement suggestions

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Inspired by industry-leading code review tools
• Built with dedication for the developer community

Star this repository if you find it helpful!

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Made by NoLongerHumanHQ