Data Structures in Java

Here’s a quick overview of basic data structures that form the foundation of computer science and programming:

1. Array

• Definition: A collection of elements stored in contiguous memory locations.

• Key Points:

  • Fixed size.

  • Index-based access (fast lookup).

  • Insertion/deletion can be costly.

• Example (Java):

  int[] arr = {10, 20, 30, 40};
  System.out.println(arr[2]); // Output: 30
  

2. Linked List

• Definition: A collection of nodes, where each node contains data and a pointer to the next node.

• Types: Singly Linked List, Doubly Linked List, Circular Linked List.

• Key Points:

  • Dynamic size.

  • Easy insertion/deletion.

  • Sequential access (slower lookup than arrays).

• Example (Node Structure in Java):

  class Node {
      int data;
      Node next;
      Node(int d) { data = d; next = null; }
  }
  

3. Stack

• Definition: A linear data structure that follows LIFO (Last In First Out).

• Key Operations:

  • push() → add element

  • pop() → remove element

  • peek() → view top element

• Use Cases: Undo operations, expression evaluation, function call stack.

• Example:

  Stack<Integer> stack = new Stack<>();
  stack.push(10);
  stack.push(20);
  System.out.println(stack.pop()); // Output: 20
  

4. Queue

• Definition: A linear data structure that follows FIFO (First In First Out).

• Key Operations:

  • enqueue() → add element

  • dequeue() → remove element

• Types: Simple Queue, Circular Queue, Priority Queue, Deque.

• Use Cases: Scheduling, buffering.

• Example:

  Queue<Integer> queue = new LinkedList<>();
  queue.add(1);
  queue.add(2);
  System.out.println(queue.remove()); // Output: 1
  

5. Hash Table / Hash Map

• Definition: Stores key-value pairs using hashing for fast access.

• Key Points:

  • Average O(1) lookup and insertion.

  • Collisions handled by chaining or open addressing.

• Example:

  HashMap<String, Integer> map = new HashMap<>();
  map.put("A", 1);
  map.put("B", 2);
  System.out.println(map.get("A")); // Output: 1
  

6. Tree

• Definition: Hierarchical structure with nodes; top node is root.

• Types: Binary Tree, Binary Search Tree (BST), AVL Tree, Heap.

• Use Cases: Hierarchical data, searching, sorting, parsing expressions.

• Example (Binary Tree Node in Java):

  class TreeNode {
      int val;
      TreeNode left, right;
      TreeNode(int x) { val = x; }
  }
  

7. Graph

• Definition: A collection of nodes (vertices) connected by edges.

• Types: Directed/Undirected, Weighted/Unweighted, Cyclic/Acyclic.

• Use Cases: Networking, maps, social networks.

• Example (Adjacency List):

  Map<Integer, List<Integer>> graph = new HashMap<>();
  graph.put(1, Arrays.asList(2,3));
  graph.put(2, Arrays.asList(1,4));