Programming
Programming¶
A comprehensive guide to fundamental programming concepts, principles, and methodologies that transcend any single programming language. This topic covers essential knowledge for becoming a well-rounded software developer, from computational thinking and paradigms to clean code practices, testing strategies, concurrency patterns, and software architecture.
What You'll Learn¶
This topic provides language-independent coverage of: - Core Concepts: Computational thinking, abstraction, algorithms, and data structures - Paradigms: Imperative, object-oriented, functional, and declarative programming approaches - Code Quality: Clean code principles, design patterns, SOLID principles, and refactoring - Professional Practices: Testing, debugging, performance optimization, API design, and version control workflows - Software Architecture: Monoliths, microservices, layered architecture, and architectural patterns - Ethics & Career: Developer practices, open source, software ethics, and continuous learning
Lessons¶
| # | Title | Description |
|---|---|---|
| 01 | What Is Programming | Computational thinking, abstraction, problem solving, algorithms |
| 02 | Programming Paradigms | Imperative, OOP, functional, declarative approaches |
| 03 | Data Structures Fundamentals | Arrays, lists, stacks, queues, trees, graphs, hash tables |
| 04 | Algorithms Fundamentals | Complexity analysis, searching, sorting, recursion |
| 05 | Clean Code Principles | Naming, functions, comments, formatting, error handling |
| 06 | Design Patterns | Creational, structural, behavioral patterns; Gang of Four |
| 07 | SOLID Principles | Single Responsibility, Open/Closed, Liskov, Interface Segregation, Dependency Inversion |
| 08 | Testing Fundamentals | Unit, integration, E2E testing; TDD, BDD; test doubles |
| 09 | Debugging Techniques | Debugging strategies, tools, logging, profiling |
| 10 | Refactoring | Code smells, refactoring techniques, when and how to refactor |
| 11 | Concurrency and Parallelism | Threads, processes, async, race conditions, synchronization |
| 12 | Performance Optimization | Profiling, algorithmic optimization, caching, memory management |
| 13 | API Design | REST, RPC, GraphQL; versioning, documentation, best practices |
| 14 | Version Control Workflows | Git workflows, branching strategies, code review, CI/CD |
| 15 | Software Architecture | Monoliths, microservices, layered/hexagonal/clean architecture |
| 16 | Developer Practices | Technical debt, documentation, open source, ethics, career growth |
Prerequisites¶
- Basic programming knowledge: Familiarity with at least one programming language (Python, JavaScript, Java, C++, or similar)
- Fundamental syntax understanding: Variables, control flow, functions, basic data structures
- Problem-solving mindset: Willingness to think critically about code and design
No specific language expertise is required. Examples are provided in multiple languages to demonstrate language-independent concepts.
Example Code¶
Practical examples demonstrating concepts across multiple programming languages are available in examples/Programming/. These examples help illustrate that fundamental programming principles transcend any single language.
Learning Path¶
This topic is structured to build progressively:
- Foundations (Lessons 1-4): Core concepts, paradigms, data structures, and algorithms
- Code Quality (Lessons 5-7): Clean code, design patterns, and SOLID principles
- Development Practices (Lessons 8-10): Testing, debugging, and refactoring
- Advanced Topics (Lessons 11-12): Concurrency and performance optimization
- Professional Skills (Lessons 13-16): API design, version control, architecture, and ethics
You can follow the lessons sequentially or jump to specific topics based on your needs.
Recommended Resources¶
- Books: "Clean Code" (Martin), "Design Patterns" (Gang of Four), "The Pragmatic Programmer" (Hunt & Thomas)
- Practice: LeetCode, HackerRank, Project Euler for algorithm practice
- Communities: Stack Overflow, Reddit r/programming, GitHub discussions
Related Topics¶
- Language-Specific Topics: Python, C_Programming, CPP (C++)
- Advanced Topics: Algorithm, Machine_Learning, System_Design
- Tools: Git, Docker, Linux
License: Content licensed under CC BY-NC 4.0