Naming Conventions:
Use descriptive and meaningful names for variables, functions, and classes.
Follow camelCase for variable and function names (e.g.,
sensorData,calculatePath()).Use PascalCase for class names (e.g.,
PerceptionModule,LocalizationSystem).Avoid single-letter variable names except for loop counters or well-known conventions (e.g.,
i,j).
Indentation and Formatting:
Use a consistent indentation of 4 spaces.
Encourage clear and concise code with proper line breaks and white spaces.
Limit line length to 80-100 characters to ensure code readability.
Comments:
Include comments to explain complex logic or algorithms.
Add comments to clarify the purpose of classes, functions, and important code blocks.
Avoid unnecessary comments that only restate obvious code.
Error Handling:
Use proper error handling mechanisms, like exceptions or error codes, to handle unexpected situations.
Log errors with relevant context information to aid debugging and diagnostics.
Modularity and Reusability:
Encourage writing modular and reusable code.
Design classes and functions with a single responsibility.
Avoid duplication of code; prefer writing utility functions or libraries.
Code Reviews:
Conduct regular code reviews to maintain code quality and adherence to the coding standards.
Encourage constructive feedback and discussions during code reviews.
Version Control:
Utilize version control systems (e.g., Git) for code collaboration and tracking changes.
Follow a branching strategy to manage code changes effectively.
Unit Testing:
Encourage writing unit tests for critical components and algorithms.
Aim for high test coverage to catch potential bugs early in development.
Security Considerations:
Follow secure coding practices to prevent common vulnerabilities, such as SQL injection or cross-site scripting.
Sanitize user inputs and validate data to avoid security breaches.
Documentation:
Maintain up-to-date and comprehensive documentation for code and APIs.
Provide usage examples and explanations of complex algorithms or functions.
Performance Optimization:
Optimize code for performance when necessary, but prioritize readability and maintainability.
Use profiling tools to identify performance bottlenecks before applying optimizations.