Object-Oriented Programming
OOP (Object Oriented Programming) is a programming paradigm that utilizes objects to organize data and functions into modules for reuse and modularity purposes as well as to foster strong separation of concerns.
C++ classes serve as templates or blueprints for creating objects, which represent real-world entities. An object contains both data and its associated logical sequences – commonly referred to as methods – that manipulate it, so a class may contain multiple instances with identical properties and behaviors.
OOP allows classes to inherit properties and behaviors of other classes through inheritance, similar to how traits can be passed along between parent and offspring. For example, if the Car class can run and drift, its Sports Car offspring will automatically inherit this ability. Polymorphism is another key aspect of OOP that should not be overlooked.
Inheritance
Inheritance is a mechanism through which classes can inherit properties and behavior from another class, commonly referred to as the base class name followed by a colon symbol. A new class, known as a derived class, must then be created using this approach and may either utilize data and Functions from its parent class or override them altogether.
Inheritance provides code reusability, which is crucial to maintaining the quality of your work. Unfortunately, inheritence can present issues when your classes become complex – leading to duplicate code or unnecessary member functions which could cause memory leaks or other errors.
Students writing C++ assignments often struggle with its stringent syntax. Even the slightest mistake could have serious repercussions.
Polymorphism
Polymorphism is a core feature of object-oriented programming that enables one function or operator to take different approaches in different scenarios, increasing Code reusability while decreasing maintenance costs and speeding up program execution time.
Compile-time polymorphism involves having the compiler determine which function or operation to call depending on the number and type of arguments provided to it, also known as static polymorphism. This form of polymorphism is utilized through function overloading and virtual functions.
Run time polymorphism occurs when the compiler resolves an object at runtime to determine which function to call. This is achieved using virtual functions and inheritance. For instance, Animal class has a virtual function called makeSound() that can be overridden in other classes such as Dog; at run time the correct implementation for makeSound() function will be chosen depending on which object type has been identified as relevant by run time polymorphism.
Data Structures
Data structures are logical arrangements of data that store and retrieve information efficiently, enabling complex Algorithms to run efficiently. Common types include elements, iterators and storage containers – choosing an ineffective data structure can lead to slow or nonresponsive code.
There are two primary data structures: linear and non-linear. Linear data structures store elements in sequential memory locations like arrays. Their contents can be accessed sequentially from a certain starting point; examples of this kind of linear data structure include stacks and queues.
Non-linear data structures use graphs and trees as the foundation. They consist of numerous nodes connected by parent-child relationships. Access is via keys instead of indexes. Non-linear structures are ideal for data management, scheduling, message handling systems. Unfortunately, their complexity makes them harder to comprehend.
Threading
Threading is a Programming technique that enables a program to run multiple threads at the same time, each sharing memory space with the main program and handling different tasks simultaneously – increasing its efficiency and responsiveness.
Threads can be created by passing either a lambda expression or object with operator() overloaded to the std::thread constructor, while static member functions can also be launched using this technique.
An independent thread can be joined to a main thread by calling the pthread_join() function, which ensures proper synchronization and resource cleanup. Alternately, detached threads may run independently (called worker threads ), with system automatically reclaiming resources when finished executing independently.