Data Structures and Algorithms (DSA) are critical for optimizing how data is stored, accessed, and processed, directly affecting the performance of an application. This tutorial will guide you through the essential data structures and algorithms using the Java programming language.
Why Learn DSA in Java?
Java is a widely used, object-oriented, and platform-independent programming language that is particularly strong in building robust and scalable applications. Learning DSA in Java offers several benefits:
- Memory Management: Although Java manages memory through garbage collection, understanding how data structures work in Java gives you insights into memory handling, which can help you write efficient programs.
- Versatile: Java is known for its portability. Mastering DSA in Java makes it easier to transition to other object-oriented languages such as C++ or C#, as many modern languages share a similar syntax.
- Object-Oriented: Java supports object-oriented programming (OOP) principles, which means you can easily implement data structures as classes, making your code modular, reusable, and more maintainable.
- Strong Ecosystem: Java has a strong ecosystem for both web and mobile development, making it an excellent choice for building real-world applications using DSA concepts.
Prerequisite
Before diving into DSA with Java, you should be familiar with basic Java concepts. The following fundamental topics are prerequisites for learning DSA in Java:
- Setting Up Java Development Environment: You need a working Java Development Kit (JDK) and an Integrated Development Environment (IDE) such as Eclipse or IntelliJ IDEA to write and run Java code.
- Variables & Data Types: In Java, variables store data values, and each variable has a specific type, such as
int, float, String, etc. - Basic Input and Output: Java allows input from users via the console, using classes like
Scanner, and output through System.out.print and System.out.println. - Operators: Java provides a variety of operators like arithmetic, relational, logical, etc., for performing operations on variables.
- Control Statements: Java supports decision-making statements like
if-else and switch, as well as loops like for, while, and do-while. - Functions (Methods): Functions are blocks of code that perform specific tasks and can be called multiple times. Java supports both void and non-void methods.
- Object-Oriented Concepts: Java is an object-oriented language, meaning you should know about classes, objects, inheritance, polymorphism, and encapsulation.
- Collections Framework: Java provides a rich set of data structures, like
ArrayList, HashMap, LinkedList, etc., but it’s recommended to implement your own data structures when learning DSA.
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Learn DSA in Java
Mastering DSA in Java will enhance your problem-solving skills, making you well-prepared for coding interviews, competitive programming, and large-scale software development. Whether you're a beginner or an experienced developer, this guide will provide you with a solid foundation in Java-based data structures and algorithms.
1. Asymptotic Analysis of Algorithms
Asymptotic analysis helps evaluate the efficiency of an algorithm by examining how its execution time or memory usage grows relative to the input size.
- Big O Notation: It is used to describe the upper bound of an algorithm’s runtime in terms of its input size.
- Best, Average, and Worst Case: These terms refer to the performance of an algorithm in the best, average, and worst scenarios.
- Analysis of Loops and Recursion: Loops and recursive functions are key to understanding time complexity in algorithms.
Related Article
Analysis of Algorithms
2. Arrays
Arrays are fundamental structures in Java that allow us to store multiple values of the same type in a single variable. Arrays in Java are objects, which makes them work differently from arrays in C/C++ in terms of memory management
Example:
Java // Java Program to demonstrate Arrays public class Geeks { // Main Function public static void main(String args[]) { int[] arr = {10, 20, 30, 40}; System.out.println(arr[2]); // Output: 30 } } 3. ArrayList
Java ArrayList is a part of collections framework and it is a class of java.util package. It provides us with dynamic sized arrays in Java. The main advantage of ArrayList is, It automatically adjusts its capacity as elements are added or removed.
Java // Java Program to demonstrate ArrayList import java.util.ArrayList; class Main { public static void main (String[] args) { // Creating an ArrayList ArrayList<Integer> a = new ArrayList<Integer>(); // Adding Element in ArrayList a.add(1); a.add(2); a.add(3); // Printing ArrayList System.out.println(a); } } 4. Strings
In Java, String is the type of objects that can store the sequence of characters enclosed by double quotes and every character is stored in 16 bits Strings in Java are immutable sequences of characters. Java provides a robust set of string operations, such as concatenation, substring extraction, and searching.
Example:
Java // Java Program to demonstrate String public class Geeks { // Main Function public static void main(String args[]) { // creating Java string using new keyword String str = "Hello"; System.out.println(str.length()); // Output: 5 System.out.println(str); // Output: Hello } } 5. Stacks
A Stack in Java is a data structure that follows the Last In, First Out (LIFO) principle. In a stack, the last element added is the first one to be removed. In addition to the basic push and pop operations, the class provides three more functions of empty, search, and peek.
Example:
Java // Java Program Implementing Stack Class import java.util.Stack; public class StackExample { public static void main(String[] args) { // Create a new stack Stack<Integer> s = new Stack<>(); // Push elements onto the stack s.push(1); s.push(2); s.push(3); s.push(4); // Pop elements from the stack while(!s.isEmpty()) { System.out.println(s.pop()); } } } 6. Queues
In JAVA queues store and processes the data in FIFO(First In First Out) order. It is an ordered list of objects limited to inserting elements at the end of the list and deleting elements from the start of the list.
Example (Stack using Array):
Java Stack<Integer> stack = new Stack<>(); stack.push(10); stack.push(20); System.out.println(stack.pop()); // Output: 20
7. Linked List
A linked list is a dynamic data structure whose size increases as you add the elements and decreases as you remove the elements from the list and the elements (nodes) are connected by pointers. Each node contains data and a reference (link) to the next node.
Example:
Java class Node { int data; Node next; Node(int data) { this.data = data; this.next = null; } } public class LinkedList { public static void main(String[] args) { Node head = new Node(10); head.next = new Node(20); System.out.println(head.data); // Output: 10 } } 8. Searching Algorithms
Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored. Based on the type of search operation, these algorithms are generally classified into two categories: Sequential/ Linear Search or Interval Search.
Example (Linear Search):
Java // Java program to implement Linear Search class GfG { public static void main(String args[]) { int arr[] = { 2, 3, 4, 10, 40 }; int x = 50; // Element to search int n = arr.length; for (int i = 0; i <= n; i++) { if( i == n ) { System.out.print("Element is not present"); break; } if (arr[i] == x) { System.out.print("Element is present" + " at index " + i); break; } } } } 9. Sorting Algorithms
Sorting Algorithm are used to rearrange a given array or list of elements in an order. Sorting is provided in library implementation of most of the programming languages.
Example:
Java // Java Program to sort an array class GFG { // Main driver method public static void main(String[] args) {// Custom input array int arr[] = { 4, 3, 2, 1 }; // Outer loop for (int i = 0; i < arr.length; i++) { // Inner nested loop pointing 1 index ahead for (int j = i + 1; j < arr.length; j++) { // Checking elements int temp = 0; if (arr[j] < arr[i]) { // Swapping temp = arr[i]; arr[i] = arr[j]; arr[j] = temp; } } // Printing sorted array elements System.out.print(arr[i] + " "); } }} 10. Greedy Algorithm
Greedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. Examples of popular Greedy Algorithms are Fractional Knapsack, Dijkstra's algorithm, Kruskal's algorithm, Huffman coding and Prim's Algorithm
Java // Java program to find minimum cost // to reduce array size to 1, import java.lang.*; public class GFG { // function to calculate the // minimum cost static int cost(int []a, int n) { int min = a[0]; // find the minimum using // for loop for(int i = 1; i< a.length; i++) { if (a[i] < min) min = a[i]; } // Minimum cost is n-1 multiplied // with minimum element. return (n - 1) * min; } // driver program to test the // above function. static public void main (String[] args) { int []a = { 4, 3, 2 }; int n = a.length; System.out.println(cost(a, n)); } } // This code is contributed by parashar. 11. Trees
Tree data structure is a hierarchical structure that is used to represent and organize data in the form of parent child relationship. Where the topmost node of the tree is called the root, and the nodes below it are called the child nodes.
Example (Binary Search Tree):
Java // java code for above approach import java.io.*; import java.util.*; class GfG { // Function to print the parent of each node public static void printParents(int node, Vector<Vector<Integer> > adj, int parent) { // current node is Root, thus, has no parent if (parent == 0) System.out.println(node + "->Root"); else System.out.println(node + "->" + parent); // Using DFS for (int i = 0; i < adj.get(node).size(); i++) if (adj.get(node).get(i) != parent) printParents(adj.get(node).get(i), adj, node); } // Function to print the children of each node public static void printChildren(int Root, Vector<Vector<Integer> > adj) { // Queue for the BFS Queue<Integer> q = new LinkedList<>(); // pushing the root q.add(Root); // visit array to keep track of nodes that have been // visited int vis[] = new int[adj.size()]; Arrays.fill(vis, 0); // BFS while (q.size() != 0) { int node = q.peek(); q.remove(); vis[node] = 1; System.out.print(node + "-> "); for (int i = 0; i < adj.get(node).size(); i++) { if (vis[adj.get(node).get(i)] == 0) { System.out.print(adj.get(node).get(i) + " "); q.add(adj.get(node).get(i)); } } System.out.println(); } } // Function to print the leaf nodes public static void printLeafNodes(int Root, Vector<Vector<Integer> > adj) { // Leaf nodes have only one edge and are not the // root for (int i = 1; i < adj.size(); i++) if (adj.get(i).size() == 1 && i != Root) System.out.print(i + " "); System.out.println(); } // Function to print the degrees of each node public static void printDegrees(int Root, Vector<Vector<Integer> > adj) { for (int i = 1; i < adj.size(); i++) { System.out.print(i + ": "); // Root has no parent, thus, its degree is // equal to the edges it is connected to if (i == Root) System.out.println(adj.get(i).size()); else System.out.println(adj.get(i).size() - 1); } } // Driver code public static void main(String[] args) { // Number of nodes int N = 7, Root = 1; // Adjacency list to store the tree Vector<Vector<Integer> > adj = new Vector<Vector<Integer> >(); for (int i = 0; i < N + 1; i++) { adj.add(new Vector<Integer>()); } // Creating the tree adj.get(1).add(2); adj.get(2).add(1); adj.get(1).add(3); adj.get(3).add(1); adj.get(1).add(4); adj.get(4).add(1); adj.get(2).add(5); adj.get(5).add(2); adj.get(2).add(6); adj.get(6).add(2); adj.get(4).add(7); adj.get(7).add(4); // Printing the parents of each node System.out.println("The parents of each node are:"); printParents(Root, adj, 0); // Printing the children of each node System.out.println( "The children of each node are:"); printChildren(Root, adj); // Printing the leaf nodes in the tree System.out.println( "The leaf nodes of the tree are:"); printLeafNodes(Root, adj); // Printing the degrees of each node System.out.println("The degrees of each node are:"); printDegrees(Root, adj); } } // This code is contributed by rj13to. 12. Hashing
In hashing there is a hash function that maps keys to some values. But these hashing function may lead to collision that is two or more keys are mapped to same value. In java there are various methods to implement hashing such as by using HashTable or HashMap etc.
Java // Java program to demonstrate working of HashTable import java.util.*; class GFG { public static void main(String args[]) { // Create a HashTable to store // String values corresponding to integer keys Hashtable<Integer, String> hm = new Hashtable<Integer, String>(); // Input the values hm.put(1, "Geeks"); hm.put(12, "forGeeks"); hm.put(15, "A computer"); hm.put(3, "Portal"); // Printing the Hashtable System.out.println(hm); } } 13. Dynamic Programming
Dynamic programming (DP) is used to solve problems by breaking them down into overlapping subproblems, solving each subproblem only once, and storing the results.
Java // Java program to find fibonacci number using memoization. import java.util.Arrays; class GfG { static int fibRec(int n, int[] memo) { // Base case if (n <= 1) return n; // To check if output already exists if (memo[n] != -1) return memo[n]; // Calculate and save output for future use memo[n] = fibRec(n - 1, memo) + fibRec(n - 2, memo); return memo[n]; } public static void main(String[] args) { int n = 9; int[] memo = new int[n + 1]; Arrays.fill(memo, -1); System.out.println( fibRec(n, memo)); } } 14. Graphs
A graph consists of vertices connected by edges. It can be represented using adjacency matrices or adjacency lists.
Example (Graph Representation using Adjacency List):
Java class Graph { private LinkedList<Integer> adjList[]; Graph(int vertices) { adjList = new LinkedList[vertices]; for (int i = 0; i < vertices; ++i) adjList[i] = new LinkedList<>(); } } 15. Backtracking Algorithm
Backtracking algorithms are like problem-solving strategies that help explore different options to find the best solution. They work by trying out different paths and if one doesn't work, they backtrack and try another until they find the right one.
Example:
Java // Java program to print all subsets // of a given Set or Array using backtracking import java.util.*; class GfG { static void subsetRecur(int i, int[] arr, List<List<Integer>> res, List<Integer> subset) { // add subset at end of array if (i == arr.length) { res.add(new ArrayList<>(subset)); return; } // include the current value and // recursively find all subsets subset.add(arr[i]); subsetRecur(i + 1, arr, res, subset); // exclude the current value and // recursively find all subsets subset.remove(subset.size() - 1); subsetRecur(i + 1, arr, res, subset); } static List<List<Integer>> subsets(int[] arr) { List<Integer> subset = new ArrayList<>(); List<List<Integer>> res = new ArrayList<>(); subsetRecur(0, arr, res, subset); return res; } public static void main(String[] args) { int[] arr = {1, 2, 3}; List<List<Integer>> res = subsets(arr); for (List<Integer> subset : res) { for (int num : subset) { System.out.print(num + " "); } System.out.println(); } } } 16. Bitwise Algorithms
Bitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers by using operators like AND, OR, XOR, NOT, Left Sift and Right Shift.
Java // Java program to unset the rightmost // set bit using Naive approach class GfG { // Unsets the rightmost set bit // of n and returns the result static int unsetLSB(int n) { if (n == 0) return 0; // Find the rightmost set bit int pos = 0; while (((n >> pos) & 1) == 0) { pos++; } // Unset the rightmost set bit n = n ^ (1 << pos); return n; } public static void main(String[] args) { int n = 12; System.out.print(unsetLSB(n)); } } Similar Reads
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