1. What’s a Data Structure?

A data structure is a way to store and organize data so it can be accessed and modified efficiently. Choosing the right data structure can make programs faster and easier to manage.

Why data structures matter:

They help organize data efficiently.
They improve problem-solving and algorithm implementation.
They form the backbone of programming logic and software design.

Some real-life analogies:

Stack: A stack of plates — the last plate added is the first one removed.
Queue: A line of people waiting for tickets — the first person in line is the first to be served.
List: A shopping list — items can be added or removed anywhere.

2. What’s an Abstract Data Type (ADT)?

An Abstract Data Type (ADT) defines the behavior of a data structure rather than its implementation. It describes what operations can be performed and what each operation does.

Example — Stack ADT:

Operations: push(item), pop(), peek()
Implementation could be an array, a linked list, or Java’s built-in Stack class.

Key idea: ADTs define what is done, not how it is done. This allows different implementations while keeping the behavior consistent.

3. Common ADTs

Stack

Principle: LIFO (Last In, First Out)
Operations: push, pop, peek

Java Example:

import java.util.Stack;

public class StackExample {
    public static void main(String[] args) {
        Stack<Integer> stack = new Stack<>();
        stack.push(10);
        stack.push(20);
        stack.push(30);

        System.out.println("Top element: " + stack.peek()); // 30
        stack.pop();
        System.out.println("Stack after pop: " + stack); // [10, 20]
    }
}

Queue

Principle: FIFO (First In, First Out)
Operations: add() / offer(), remove() / poll(), peek()

Java Example:

import java.util.LinkedList;
import java.util.Queue;

public class QueueExample {
    public static void main(String[] args) {
        Queue<Integer> queue = new LinkedList<>();
        queue.add(10);
        queue.add(20);
        queue.add(30);

        System.out.println("Front element: " + queue.peek()); // 10
        queue.remove();
        System.out.println("Queue after remove: " + queue); // [20, 30]
    }
}

List

Definition: An ordered collection of elements
Can be array-based (ArrayList) or linked (LinkedList)
Supports insertion, deletion, and traversal

Java Example:

import java.util.ArrayList;

public class ListExample {
    public static void main(String[] args) {
        ArrayList<String> list = new ArrayList<>();
        list.add("Apple");
        list.add("Banana");
        list.add("Cherry");

        System.out.println("List elements: " + list); // [Apple, Banana, Cherry]
        list.remove("Banana");
        System.out.println("After removal: " + list); // [Apple, Cherry]
    }
}

4. Why ADTs and Data Structures Matter

They are building blocks of algorithms.
Using the right structure can make code faster and more efficient.
They are essential for problem-solving, exams, and coding interviews.
Understanding these concepts makes algorithms less intimidating — once the tools are clear, applying them is easier.

5. Next Steps

In the next post, the focus will be on Algorithm Efficiency and Big O Notation. Together, we’ll learn how to measure the performance of our code, so that when arrays, stacks, and queues are implemented, it’s easier to understand their efficiency.