programming

name	programming
description	Provides recipes for programming tasks. Use when executing programming tasks like creating code, creating tests, reactoring code, reviewing code.
metadata	{"scope":"implementation","version":"1.0.0"}

Programming Recipes

This skill provides a collection of recipes to solve common programming tasks, focusing on refactoring, optimization, and best practices.

Available Recipes

1. Decouple Business Logic from UI

• Goal: Separate business logic from UI components to improve maintainability, reusability, and testability.
• Technique: Extract business logic into services, state management solutions (e.g., Redux), or hooks.
• Example: Refactoring a React Counter component by moving state management to Redux, separating actions, reducers, and the store from the component's view.

2. Fix Lint Errors

• Goal: Improve code quality, catch bugs early, and ensure consistency by addressing linter warnings.
• Common Fixes:
  • Managing imports (adding missing, removing unused).
  • Adhering to style guidelines (naming conventions, spacing, indentation).
  • Removing unused variables and unreachable code.
  • Adding docstrings and replacing print statements with proper logging.

3. Handle Cross-Cutting Concerns

• Goal: Centralize logic for concerns that affect multiple parts of an application (e.g., logging, security, validation).
• Technique: Use Aspect-Oriented Programming (AOP), decorators, or middleware to avoid code duplication.
• Example: Refactoring a Python application to use aspectlib to handle logging for multiple service methods, keeping the logging logic in one place.

4. Improve Code Readability and Maintainability

• Goal: Make code easier to understand, maintain, and extend.
• Techniques:
  • Use Descriptive Variable Names: Replace abstract names (a, b) with meaningful ones (name, age).
  • Avoid Sequential Conditionals: Replace long if/else chains with dictionaries or switch statements.
  • Reduce Nested Logic: Use guard clauses to flatten deeply nested if statements.
  • Split Large Methods: Break down long methods into smaller, single-responsibility functions.

5. Refactor Data Access Layers

• Goal: Abstract database interactions to make the application more modular, scalable, and secure.
• Technique: Implement a repository pattern to separate data access logic from business logic.
• Example: Refactoring a Python function with a hardcoded, insecure SQL query into a UserRepository with a Database class that uses parameterized queries and a context manager.

6. Implement Design Patterns

• Goal: Solve common software design problems using established, reusable patterns.
• Technique: Identify areas where patterns like Singleton, Factory, or Module can improve code structure.
• Example: Refactoring JavaScript code to use the Module Pattern to encapsulate related functions and data, preventing global namespace pollution.

7. Optimize for Performance

• Goal: Identify and resolve performance bottlenecks in inefficient code.
• Techniques:
  • Optimize algorithms and data structures (e.g., using a sieve for prime generation instead of trial division).
  • Reduce redundant computations and memory allocation.
  • Introduce caching or parallelize operations where appropriate.

8. Refactor for Environmental Sustainability

• Goal: Reduce the energy consumption and environmental impact of software.
• Technique: Identify and refactor resource-intensive operations to be more efficient in terms of CPU and memory usage.
• Example: Improving a Python script that counts lines in a large file by reading it line-by-line instead of loading the entire file into memory.

9. Translate Between Programming Languages

• Goal: Port code from one language to another to leverage different features, improve performance, or standardize a codebase.
• Process: Translate the logic, syntax, and standard library calls from the source language to the target language, ensuring functional equivalence.
• Example: Converting a Perl script for file analysis into a modern TypeScript equivalent using Node.js modules.