Introduction to Coding and Programming Languages

• Coding is the process of writing instructions for computers using programming languages, which tell the computer what actions to perform.

Programming Languages

• Programming languages are formal languages comprised of a set of instructions used to produce various kinds of output.
• High-level languages are designed to be human-readable, examples include Python, Java, and C++.
• Low-level languages are closer to machine code, such as Assembly.
• Compilers translate high-level code into machine code all at once.
• Interpreters execute high-level code line by line.

Basic Programming Concepts

• Variables are used to store data values that can be changed during program execution.
• Data types specify the type of data a variable can hold, such as integer, float, string, and boolean.
• Operators perform operations on variables and values and include arithmetic, comparison, and logical operators.
• Control structures determine the flow of execution in a program.
• Conditional statements, such as if, else if, and else, execute different blocks of code based on conditions.
• Loops, such as for and while, repeat a block of code multiple times.
• Functions are reusable blocks of code that perform a specific task.
• Input and output (I/O) operations allow programs to receive input from users and display output.
• Comments are used to explain code and are ignored by the compiler or interpreter.

Data Structures

• Data structures are ways of organizing and storing data in a computer so that it can be used efficiently.
• They provide a means to manage large amounts of data for uses such as large databases and internet indexing services.

Arrays

• Arrays are collections of elements of the same data type stored in contiguous memory locations.
• Elements are accessed using an index, starting from 0.
• Arrays can be one-dimensional or multi-dimensional.
• Arrays offer fast access to elements given the index.
• Arrays have a fixed size, defined at the time of declaration.

Linked Lists

• Linked lists are collections of elements, called nodes, where each node contains data and a pointer to the next node.
• The last node points to null.
• Linked lists can be singly linked (one pointer) or doubly linked (two pointers: one to the next node and one to the previous node).
• Linked lists allow dynamic memory allocation.
• Insertion and deletion operations are efficient.
• Accessing an element requires traversing the list from the head.

Stacks

• Stacks are linear data structures that follow the Last-In-First-Out (LIFO) principle.
• Elements are added (pushed) and removed (popped) from the top of the stack.
• Common operations include push, pop, peek (view the top element), and isEmpty.
• Stacks are used in function call management, expression evaluation, and backtracking algorithms.

Queues

• Queues are linear data structures that follow the First-In-First-Out (FIFO) principle.
• Elements are added (enqueued) at the rear and removed (dequeued) from the front.
• Common operations include enqueue, dequeue, peek (view the front element), and isEmpty.
• Queues are used in task scheduling, breadth-first search (BFS), and handling requests in web servers.

Hash Tables

• Hash tables are data structures that implement an associative array abstract data type, a structure that can map keys to values.
• A hash function is used to compute an index (hash code) for each key.
• Collisions occur when different keys produce the same hash code; these are handled using techniques like chaining or open addressing.
• Hash tables offer fast average-case performance for insertion, deletion, and search operations.

Trees

• Trees are hierarchical data structures consisting of nodes connected by edges.
• A tree has a root node, and each node can have child nodes.
• Binary trees are trees in which each node has at most two children, referred to as the left child and the right child.
• Binary search trees (BSTs) are binary trees where the value of each node is greater than or equal to the values in its left subtree and less than or equal to the values in its right subtree.
• Tree traversal methods include Pre-order (root, left, right), In-order (left, root, right), and Post-order (left, right, root).

Graphs

• Graphs are data structures consisting of nodes (vertices) and edges that connect pairs of nodes.
• Graphs can be directed (edges have a direction) or undirected (edges are bidirectional).
• Graphs can be represented using adjacency matrices or adjacency lists.
• Graph traversal methods include Depth-first search (DFS) and Breadth-first search (BFS).
• Graphs are used to model networks, social connections, and dependencies.

Common Operations on Data Structures

• Insertion: Adding a new element to the data structure.
• Deletion: Removing an existing element from the data structure.
• Search: Finding a specific element in the data structure.
• Traversal: Visiting each element in the data structure in a specific order.
• Sorting: Arranging elements in a specific order (e.g., ascending or descending).