Lesson 1

Object-Oriented Programming (OOP) remains the dominant paradigm for building maintainable, scalable, and reusable software systems. Unlike traditional procedural programming, which organizes code as a sequence of instructions—OOP focuses on objects that model real-world entities with state and behavior. In this module, you will learn to:

1. Compare traditional program design with object-oriented design
2. Identify initial classes in a system
3. Evaluate the qualities of a “good class”
4. Apply OOP constructs in C++ to build modular applications

At its core, OOP represents software concepts as objects, which are instances of classes. A class acts as a blueprint, defining the attributes (data) and behaviors (methods) that its objects share. In C++, the key constructs of OOP include:

1. Classes: Blueprints that encapsulate attributes and methods.
2. Objects: Instances of classes that represent real-world entities.
3. Encapsulation: Bundling data and methods while controlling access with specifiers (private, protected, public).
4. Inheritance: Mechanism for reusing and extending functionality through base and derived classes.
5. Polymorphism: The ability for objects to take on multiple forms, supported by function overloading, operator overloading, and virtual functions.
6. Abstraction: Hiding complex implementation details and exposing only essential functionality, often achieved with abstract classes or interfaces.

These principles work together to simplify complex systems, encourage reuse, and improve maintainability across large projects.

Choosing between paradigms depends on the task, project requirements, and environment. Imperative programming is well-suited for:

• Small, simple scripts (data processing, automation)
• Performance-critical code where direct control over memory is essential
• Procedural algorithms like sorting or searching
• Low-level programming such as drivers or embedded systems

Object-Oriented Programming is better for:

• Complex, large-scale applications (enterprise systems, simulations, GUIs)
• Systems requiring code reuse, modularity, and maintainability
• Domains where inheritance, polymorphism, and abstraction naturally model the problem space

Summary:

• Use imperative programming for straightforward tasks, performance-focused code, or low-level system development.
• Use object-oriented programming when scalability, reusability, and abstraction are critical.

Modern development often combines both paradigms: procedural techniques for small utilities and OOP principles for system design.