Object-Oriented Programming (OOP)

• Computer programming is the process of designing, writing, testing, and maintaining the source code of computer programs
• It involves creating instructions that tell a computer what to do
• Programming languages are used to write these instructions

Object-Oriented Programming (OOP)

• OOP is a programming paradigm based on the concept of "objects", which contain data in the form of fields (attributes) and code in the form of procedures (methods)
• OOP focuses on creating reusable and modular code through concepts like encapsulation, inheritance, and polymorphism
• Encapsulation: Bundling data and methods that operate on the data within a class, hiding internal implementation details from the outside
• Inheritance: Allows new classes (subclasses or derived classes) to inherit properties and behaviors from existing classes (base classes or parent classes), promoting code reuse and creating hierarchical relationships
• Polymorphism: Enables objects of different classes to respond to the same method call in their own way, providing flexibility and extensibility

Functional Programming

• Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing state and mutable data
• Key principles include immutability, pure functions, and higher-order functions
• Immutability: Data cannot be modified after creation, promoting predictable and thread-safe code
• Pure functions: Functions that always produce the same output for the same input and have no side effects, making code easier to test and reason about
• Higher-order functions: Functions that can take other functions as arguments or return them as results, enabling powerful abstractions and code composition

Data Structures

• Data structures are ways of organizing and storing data in a computer so that it can be used efficiently
• Common data structures include:
  • Arrays: Contiguous blocks of memory that store elements of the same data type
  • Linked Lists: Collections of nodes, each containing data and a pointer to the next node
  • Stacks: LIFO (Last-In, First-Out) data structure
  • Queues: FIFO (First-In, First-Out) data structure
  • Trees: Hierarchical data structures consisting of nodes connected by edges
  • Graphs: Collections of nodes (vertices) connected by edges
  • Hash Tables: Data structures that use a hash function to map keys to their corresponding values

Algorithms

• Algorithms are step-by-step procedures or sets of rules designed to solve a specific problem
• Algorithm design involves analyzing the problem, devising a solution, and expressing it in a way that a computer can execute
• Important algorithm design techniques:
  • Divide and Conquer: Break down a problem into smaller subproblems, solve them recursively, and combine their solutions
  • Dynamic Programming: Solve overlapping subproblems by storing their solutions to avoid recomputation
  • Greedy Algorithms: Make locally optimal choices at each step with the hope of finding a global optimum
• Algorithm analysis involves assessing the efficiency and correctness of an algorithm based on factors such as time complexity and space complexity

Software Development Methodologies

• Software development methodologies are frameworks or approaches used to structure, plan, and control the process of developing software
• Common methodologies:
  • Waterfall: Sequential, linear approach with distinct phases (requirements, design, implementation, testing, deployment, maintenance)
  • Agile: Iterative and incremental approach that emphasizes flexibility, collaboration, and customer feedback
  • Scrum: Agile framework that uses short development cycles called sprints and daily meetings to track progress
  • Kanban: Agile methodology that focuses on visualizing workflow, limiting work in progress, and continuously improving processes
  • DevOps: Emphasizes collaboration and automation between development and operations teams to streamline the software delivery process

Python

• Python is a high-level, interpreted, general-purpose programming language
• Known for its readability and clear syntax
• Supports multiple programming paradigms, including object-oriented, imperative, and functional programming
• Dynamically typed
• Features a large standard library

def greet(name):
    print(f"Hello, {name}!")

greet("World")

Java

• Java is a high-level, class-based, object-oriented programming language
• Designed to be platform-independent (write once, run anywhere) through the use of the Java Virtual Machine (JVM)
• Statically typed
• Known for its robustness, security, and scalability

public class Main {
    public static void main(String[] args) {
        System.out.println("Hello, World!");
    }
}