Core Data Structures
What are Core Data Structures?
Core data structures are the basic ways of organizing and storing data so that it can be used efficiently.
They are the building blocks of all programs — from a simple calculator app to large-scale social media platforms.
Why Learn Core Data Structures?
- Efficiency: Choosing the right data structure can make programs run much faster.
- Problem Solving: Many real-world problems map directly to these structures.
- Foundation for Advanced DSA: You can’t master algorithms without knowing how data is stored and accessed.
- Interview Readiness: Core data structures are a favorite topic in technical interviews.
📖 What You Will Learn in This Chapter
This chapter introduces you to the most commonly used data structures, their uses, advantages, disadvantages, and Java implementations.
1. Array
- What is an Array and how it works.
- How to store and access elements using indexes.
- Limitations of arrays.
- Real-life example: Managing a list of student marks.
2. Strings
- How strings store sequences of characters.
- String manipulation in Java.
- Common operations like concatenation, searching, and substring extraction.
- Real-life example: Checking if a password contains a special character.
3. Linked Lists
- How nodes are connected using references.
- Singly vs Doubly linked lists.
- Adding, deleting, and traversing nodes.
- Real-life example: Music playlist navigation.
4. Stacks
- Last In, First Out (LIFO) principle.
- Push, Pop, Peek operations.
- Real-life example: Undo/Redo feature in editors.
5. Queues
- First In, First Out (FIFO) principle.
- Enqueue and Dequeue operations.
- Variations like Circular Queue and Priority Queue.
- Real-life example: Ticket booking system.
6. Hashing
- Storing and retrieving data using key–value pairs.
- Hash functions and hash tables.
- Handling collisions.
- Real-life example: Fast dictionary lookup.
7. Trees
- Hierarchical data representation.
- Types of trees: Binary, Binary Search Tree (BST), etc.
- Traversal methods (Inorder, Preorder, Postorder).
- Real-life example: Folder structure in your computer.
8. Graphs
- Nodes (vertices) and connections (edges).
- Directed vs Undirected graphs.
- Representations: Adjacency Matrix and Adjacency List.
- Real-life example: Social network connections.
🛠 How We Will Learn
For each data structure, we will cover:
- Definition – What it is.
- Why – Advantages and limitations.
- Where to Use – Real-life scenarios.
- Java Implementation – With step-by-step explanations.
- Complexity Analysis – Understanding performance.
Key Takeaway
By the end of this chapter, you will be able to:
- Identify the right data structure for a problem.
- Implement it in Java.
- Analyze its performance.
- Use it in real-world applications.