Data structures are fundamental concepts in computer science and programming that organize and store data efficiently. Different data structures have varied characteristics and are suitable for different kinds of applications. Below are some basic data structures along with their key properties and uses:

1. Arrays

• Definition: A collection of elements identified by index or key, where all elements are of the same data type.
• Characteristics:
  • Fixed size (static arrays) or dynamic size (dynamic arrays).
  • Elements are stored in contiguous memory locations.
• Use Cases: Storing a list of items, performing searches using indexed access.

2. Linked Lists

• Definition: A sequential collection of elements, called nodes, each containing a data part and a reference (or link) to the next node.
• Types:
  • Singly Linked List: Each node links to the next node.
  • Doubly Linked List: Each node links to both the next and the previous node.
  • Circular Linked List: The last node links back to the first node.
• Characteristics:
  • Dynamic size (can grow and shrink).
  • Efficient insertions and deletions.
• Use Cases: Implementing stacks, queues, and other dynamic data applications.

3. Stacks

• Definition: A linear data structure that follows the Last In, First Out (LIFO) principle. The last element added is the first to be removed.
• Operations:
  • push: Add an element to the top.
  • pop: Remove the top element.
  • peek: View the top element without removing it.
• Use Cases: Expression parsing, backtracking algorithms, and function call management.

4. Queues

• Definition: A linear data structure that follows the First In, First Out (FIFO) principle. The first element added is the first to be removed.
• Operations:
  • enqueue: Add an element to the back.
  • dequeue: Remove the front element.
  • peek: View the front element without removing it.
• Types:
  • Simple Queue: Non-circular, traditional queue.
  • Circular Queue: The last position is connected back to the first position.
  • Priority Queue: Elements have priorities; higher priority elements are dequeued before lower ones.
• Use Cases: Scheduling tasks, managing requests in service systems, and buffering.