How to Build a Customizable Code Linter with User-Defined Rule Sets

Simple Summary

A flexible code linter with customizable rule sets, allowing developers to enforce coding standards and catch errors early in the development process.

Product Requirements Document (PRD)

Goals:

• Develop a code linter with support for custom rule sets
• Provide an intuitive interface for creating, editing, and managing linting rules
• Enable seamless integration with popular development environments and CI/CD pipelines
• Ensure high performance and scalability to handle large codebases

Target Audience:

• Software developers
• Development teams
• Quality assurance professionals

Key Features:

1. Custom rule creation interface
2. Rule set management (create, edit, delete, import, export)
3. Code analysis engine
4. Integration with popular IDEs and text editors
5. CI/CD pipeline integration
6. Performance optimization for large codebases
7. Detailed error reporting and suggestions
8. User authentication and rule sharing

User Requirements:

• Ability to create custom linting rules using a simple, expressive syntax
• Import and export rule sets for sharing and version control
• Apply different rule sets to different projects or file types
• Receive clear, actionable feedback on linting errors and warnings
• Integrate the linter into existing development workflows

User Flows

1. Rule Creation:

   • User logs in to the linter dashboard
   • Navigates to "Create New Rule" section
   • Defines rule parameters (e.g., pattern matching, severity)
   • Tests rule against sample code
   • Saves and adds rule to a rule set

2. Code Linting:

   • User selects a project or file to lint
   • Chooses applicable rule set(s)
   • Initiates linting process
   • Reviews linting results and error messages
   • Applies suggested fixes or ignores warnings as needed

3. Rule Set Management:

   • User accesses rule set management interface
   • Creates a new rule set or selects an existing one
   • Adds, removes, or modifies rules within the set
   • Exports rule set for sharing or version control
   • Applies rule set to specific projects or file types

Technical Specifications

• Frontend: React for web interface, Electron for desktop app
• Backend: Node.js with Express.js
• Database: PostgreSQL for user data and rule storage
• Authentication: JWT for secure user sessions
• Code Analysis: Custom parser using Abstract Syntax Trees (ASTs)
• API: RESTful architecture
• Testing: Jest for unit and integration tests
• CI/CD: GitHub Actions for automated testing and deployment
• Containerization: Docker for consistent development and deployment environments

API Endpoints

• POST /api/auth/register
• POST /api/auth/login
• GET /api/users/:id
• POST /api/rules
• GET /api/rules
• PUT /api/rules/:id
• DELETE /api/rules/:id
• POST /api/rulesets
• GET /api/rulesets
• PUT /api/rulesets/:id
• DELETE /api/rulesets/:id
• POST /api/lint
• GET /api/projects
• POST /api/projects

Database Schema

Users:

• id (PK)
• username
• email
• password_hash
• created_at
• updated_at

Rules:

• id (PK)
• user_id (FK to Users)
• name
• description
• pattern
• severity
• created_at
• updated_at

RuleSets:

• id (PK)
• user_id (FK to Users)
• name
• description
• created_at
• updated_at

RuleSetRules:

• id (PK)
• rule_set_id (FK to RuleSets)
• rule_id (FK to Rules)

Projects:

• id (PK)
• user_id (FK to Users)
• name
• rule_set_id (FK to RuleSets)
• created_at
• updated_at

File Structure

Implementation Plan

1. Project Setup (1 week)

   • Initialize project structure
   • Set up version control
   • Configure development environment

2. Backend Development (3 weeks)

   • Implement user authentication
   • Develop rule and rule set management APIs
   • Create code parsing and AST analysis engine

3. Frontend Development (3 weeks)

   • Build user interface components
   • Implement rule creation and management interfaces
   • Develop linting results display

4. Integration and Testing (2 weeks)

   • Integrate frontend and backend
   • Implement end-to-end linting process
   • Conduct thorough testing and bug fixing

5. Performance Optimization (1 week)

   • Optimize linting engine for large codebases
   • Implement caching and parallel processing

6. IDE and CI/CD Integration (2 weeks)

   • Develop plugins for popular IDEs
   • Create CI/CD pipeline integrations

7. Documentation and Polishing (1 week)

   • Write user and developer documentation
   • Refine UI/UX based on feedback

8. Deployment and Launch Preparation (1 week)

   • Set up production environment
   • Conduct final testing and performance tuning

Deployment Strategy

1. Containerize application using Docker
2. Deploy backend to a scalable cloud platform (e.g., AWS ECS or Google Cloud Run)
3. Host frontend on a CDN for fast global access
4. Use a managed PostgreSQL service for the database
5. Implement a CI/CD pipeline using GitHub Actions
6. Set up monitoring and logging (e.g., ELK stack or Datadog)
7. Configure auto-scaling for handling varying loads
8. Implement regular backups and disaster recovery procedures
9. Use a staged rollout strategy (dev, staging, production)

Design Rationale

• React and Node.js chosen for their robust ecosystem and developer productivity
• Custom AST parser for flexibility in handling various programming languages
• RESTful API design for ease of integration with other tools and services
• PostgreSQL selected for its reliability and support for complex queries
• Containerization with Docker ensures consistency across development and production environments
• Modular architecture allows for easy extension and maintenance of the codebase
• Focus on user-friendly interfaces to lower the barrier for creating custom linting rules