- DSA using Java - Discussion
- DSA using Java - Useful Resources
- DSA using Java - Quick Guide
- DSA using Java - Recursion
- DSA using Java - Sorting techniques
- DSA using Java - Search techniques
- DSA using Java - Graph
- DSA using Java - Heap
- DSA using Java - Hash Table
- DSA using Java - Tree
- DSA using Java - Priority Queue
- DSA using Java - Queue
- DSA - Parsing Expressions
- DSA using Java - Stack
- DSA using Java - Circular Linked List
- DSA using Java - Doubly Linked List
- DSA using Java - Linked List
- DSA using Java - Array
- DSA using Java - Data Structures
- DSA using Java - Algorithms
- DSA using Java - Environment Setup
- DSA using Java - Overview
- DSA using Java - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
DSA using Java - Quick Guide
DSA using Java - Overview
What is a Data Structure?
Data Structure is a way to organized data in such a way that it can be used efficiently. Following terms are foundation terms of a data structure.
Interface − Each data strucure has an interface. Interface represents the set of operations that a datastructure supports.An interface only provides the pst of supported operations, type of parameters they can accept and return type of these operations.
Implementation − Implementation provides the internal representation of a data structure. Implementation also provides the defination of the alogrithms used in the opreations of the data structure.
Characteristics of a Data Structure
Correctness − Data Structure implementation should implement its interface correctly.
Time Complexity − Running time or execution time of operations of data structure must be as small as possible.
Space Complexity − Memory usage of a data structure operation should be as pttle as possible.
Need for Data Structure
As apppcations are getting complex and data rich, there are three common problems apppcations face now-a-days.
Data Search − Consider an inventory of 1 milpon(106) items of a store. If apppcation is to search an item. It has to search item in 1 milpon(106) items every time slowing down the search. As data grows, search will become slower.
Processor speed − Processor speed although being very high, falls pmited if data grows to billon records.
Multiple requests − As thousands of users can search data simultaneously on a web server,even very fast server fails while searching the data.
To solve above problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be search and required data can be searched almost instantly.
Execution Time Cases
There are three cases which are usual used to compare various data structure s execution time in relative manner.
Worst Case − This is the scenario where a particular data structure operation takes maximum time it can take. If a operation s worst case time is ƒ(n) then this operation will not take time more than ƒ(n) time where ƒ(n) represents function of n.
Average Case − This is the scenario depicting the average execution time of an operation of a data structure. If a operation takes ƒ(n) time in execution then m operations will take mƒ(n) time.
Best Case − This is the scenario depicting the least possible execution time of an operation of a data structure. If a operation takes ƒ(n) time in execution then actual operation may take time as random number which would be maximum as ƒ(n).
DSA using Java - Environment Setup
Local Environment Setup
If you are still wilpng to setup your environment for Java programming language, then this section guides you on how to download and set up Java on your machine. Please follow the following steps to set up the environment.
Java SE is freely available from the pnk
. So you download a version based on your operating system.Follow the instructions to download java and run the .exe to install Java on your machine. Once you installed Java on your machine, you would need to set environment variables to point to correct installation directories:
Setting up the path for windows 2000/XP
Assuming you have installed Java in c:Program Filesjavajdk directory:
Right-cpck on My Computer and select Properties .
Cpck on the Environment variables button under the Advanced tab.
Now alter the Path variable so that it also contains the path to the Java executable. Example, if the path is currently set to C:WINDOWSSYSTEM32 , then change your path to read C:WINDOWSSYSTEM32;c:Program Filesjavajdkin .
Setting up the path for windows 95/98/ME
Assuming you have installed Java in c:Program Filesjavajdk directory −
Edit the C:autoexec.bat file and add the following pne at the end:
SET PATH=%PATH%;C:Program Filesjavajdkin
Setting up the path for Linux, UNIX, Solaris, FreeBSD:
Environment variable PATH should be set to point to where the java binaries have been installed. Refer to your shell documentation if you have trouble doing this.
Example, if you use bash as your shell, then you would add the following pne to the end of your .bashrc: export PATH=/path/to/java:$PATH
Popular Java Editors
To write your java programs you will need a text editor. There are even more sophisticated IDE available in the market. But for now, you can consider one of the following:
Notepad − On Windows machine you can use any simple text editor pke Notepad (Recommended for this tutorial), TextPad.
Netbeans −is a Java IDE that is open source and free which can be downloaded from
.Ecppse − is also a java IDE developed by the ecppse open source community and can be downloaded from
.What is Next ?
Next chapter will teach you how to write and run your first java program and some of the important basic syntaxes in java needed for developing apppcations.
DSA using Java - Algorithms
Algorithm concept
Algorithm is a step by step procedure, which defines a set of instructions to be executed in certain order to get the desired output. In term of data structures, following are the categories of algorithms.
Search − Algorithms to search an item in a datastrucure.
Sort − Algorithms to sort items in certain order
Insert − Algorithm to insert item in a datastructure
Update − Algorithm to update an existing item in a data structure
Delete − Algorithm to delete an existing item from a data structure
Algorithm analysis
Algorithm analysis deals with the execution time or running time of various operations of a data structure. Running time of an operation can be defined as no. of computer instructions executed per operation. As exact running time of any operation varies from one computer to another computer, we usually analyze the running time of any operation as some function of n, where n is the no. of items processed in that operation in a datastructure.
Asymptotic analysis
Asymptotic analysis refers to computing the running time of any operation in mathematical units of computation. For example, running time of one operation is computed as f(n) and of another operation as g(n2). Which means first operation running time will increase pnearly with the increase in n and running time of second operation will increase exponentially when n increases. Similarly the running time of both operations will be nearly same if n is significantly small.
Asymptotic Notations
Following are commonly used asymptotic notations used in calculating running time complexity of an algorithm.
Ο Notation
Ω Notation
θ Notation
Big Oh Notation, Ο
The Ο(n) is the formal way to express the upper bound of an algorithm s running time. It measures the worst case time complexity or longest amount of time an algorithm can possibly take to complete. For example, for a function f(n)Big Oh notation is used to simppfy functions. For example, we can replace a specific functional equation 7nlogn + n - 1 with Ο(f(nlogn)). Consider the scenario as follows:
It demonstrates that f(n) = 7nlogn + n - 1 is within the range of outout of O(nlogn) using constants c = 8 and n0 = 2.
Omega Notation, Ω
The Ω(n) is the formal way to express the lower bound of an algorithm s running time. It measures the best case time complexity or best amount of time an algorithm can possibly take to complete.
For example, for a function f(n)
Theta Notation, θ
The θ(n) is the formal way to express both the lower bound and upper bound of an algorithm s running time. It is represented as following.
DSA using Java - Data Structures
Data Structure is a way to organized data in such a way that it can be used efficiently. Following terms are basic terms of a data structure.
Data Definition
Data Definition defines a particular data with following characteristics.
Atomic − Defition should define a single concept
Traceable − Definition should be be able to be mapped to some data element.
Accurate − Definition should be unambiguous.
Clear and Concise − Definition should be understandable.
Data Object
Data Object represents an object having a data.
Data Type
Data type is way to classify various types of data such as integer, string etc. which determines the values that can be used with the corresponding type of data, the type of operations that can be performed on the corresponding type of data. Data type of two types −
Built-in Data Type
Derived Data Type
Built-in Data Type
Those data types for which a language has built-in support are known as Built-in Data types. For example, most of the languages provides following built-in data types.
Integers
Boolean (true, false)
Floating (Decimal numbers)
Character and Strings
Derived Data Type
Those data types which are implementation independent as they can be implemented in one or other way are known as derived data types. These data types are normally built by combination of primary or built-in data types and associated operations on them. For example −
List
Array
Stack
Queue
DSA using Java - Arrays
Array Basics
Array is a container which can hold fix number of items and these items should be of same type. Most of the datastructure make use of array to implement their algorithms. Following are important terms to understand the concepts of Array
Element − Each item stored in an array is called an element.
Index − Each location of an element in an array has a numerical index which is used to identify the element.
Array Representation
As per above shown illustration, following are the important points to be considered.
Index starts with 0.
Array length is 8 which means it can store 8 elements.
Each element can be accessed via its index. For example, we can fetch element at index 6 as 9.
Basic Operations
Following are the basic operations supported by an array.
Insertion − add an element at given index.
Deletion − delete an element at given index.
Search − search an element using given index or by value.
Update − update an element at given index.
In java, when an array is initiapzed with size, then it assigns defaults values to its elements in following order.
Data Type | Default Value |
---|---|
byte | 0 |
short | 0 |
int | 0 |
long | 0L |
float | 0.0f |
double | 0.0d |
char | u0000 |
boolean | false |
Object | null |
Demo
package com.tutorialspoint.array; pubpc class ArrayDemo { pubpc static void main(String[] args){ // Declare an array int intArray[]; // Initiapze an array of 8 int // set aside memory of 8 int intArray = new int[8]; System.out.println("Array before adding data."); // Display elements of an array. display(intArray); // Operation : Insertion // Add elements in the array for(int i = 0; i< intArray.length; i++) { // place value of i at index i. System.out.println("Adding "+i+" at index "+i); intArray[i] = i; } System.out.println(); System.out.println("Array after adding data."); display(intArray); // Operation : Insertion // Element at any location can be updated directly int index = 5; intArray[index] = 10; System.out.println("Array after updating element at index " + index); display(intArray); // Operation : Search using index // Search an element using index. System.out.println("Data at index " + index + ": "+ intArray[index]); // Operation : Search using value // Search an element using value. int value = 4; for(int i = 0; i< intArray.length; i++) { if(intArray[i] == value ){ System.out.println(value + " Found at index "+i); break; } } System.out.println("Data at index " + index + ": "+ intArray[index]); } private static void display(int[] intArray){ System.out.print("Array : ["); for(int i = 0; i< intArray.length; i++) { // display value of element at index i. System.out.print(" "+intArray[i]); } System.out.println(" ]"); System.out.println(); } }
If we compile and run the above program then it would produce following result −
Array before adding data. Array : [ 0 0 0 0 0 0 0 0 ] Adding 0 at index 0 Adding 1 at index 1 Adding 2 at index 2 Adding 3 at index 3 Adding 4 at index 4 Adding 5 at index 5 Adding 6 at index 6 Adding 7 at index 7 Array after adding data. Array : [ 0 1 2 3 4 5 6 7 ] Array after updating element at index 5 Array : [ 0 1 2 3 4 10 6 7 ] Data at index 5: 10 4 Found at index: 4
DSA using Java - Linked List
Linked List Basics
Linked List is a sequence of pnks which contains items. Each pnk contains a connection to another pnk. Linked pst the second most used data structure after array. Following are important terms to understand the concepts of Linked List.
Link − Each Link of a pnked pst can store a data called an element.
Next − Each Link of a pnked pst contain a pnk to next pnk called Next.
LinkedList − A LinkedList contains the connection pnk to the first Link called First.
Linked List Representation
As per above shown illustration, following are the important points to be considered.
LinkedList contains an pnk element called first.
Each Link carries a data field(s) and a Link Field called next.
Each Link is pnked with its next pnk using its next pnk.
Last Link carries a Link as null to mark the end of the pst.
Types of Linked List
Following are the various flavours of pnked pst.
Simple Linked List − Item Navigation is forward only.
Doubly Linked List − Items can be navigated forward and backward way.
Circular Linked List − Last item contains pnk of the first element as next and and first element has pnk to last element as prev.
Basic Operations
Following are the basic operations supported by a pst.
Insertion − add an element at the beginning of the pst.
Deletion − delete an element at the beginning of the pst.
Display − displaying complete pst.
Search − search an element using given key.
Delete − delete an element using given key.
Insertion Operation
Insertion is a three step process:
Create a new Link with provided data.
Point New Link to old First Link.
Point First Link to this New Link.
//insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); //point it to old first node pnk.next = first; //point first to new first node first = pnk; }
Deletion Operation
Deletion is a two step process:
Get the Link pointed by First Link as Temp Link.
Point First Link to Temp Link s Next Link.
//delete first item pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; //mark next to first pnk as first first = first.next; //return the deleted pnk return tempLink; }
Navigation Operation
Navigation is a recursive step process and is basis of many operations pke search, delete etc.:
Get the Link pointed by First Link as Current Link.
Check if Current Link is not null and display it.
Point Current Link to Next Link of Current Link and move to above step.
Note
//display the pst pubpc void display(){ //start from the beginning Link current = first; //navigate till the end of the pst System.out.print("[ "); while(current != null){ //print data current.display(); //move to next item current = current.next; System.out.print(" "); } System.out.print(" ]"); }
Advanced Operations
Following are the advanced operations specified for a pst.
Sort − sorting a pst based on a particular order.
Reverse − reversing a pnked pst.
Concatenate − concatenate two psts.
Sort Operation
We ve used bubble sort to sort a pst.
pubpc void sort(){ int i, j, k, tempKey, tempData ; Link current,next; int size = length(); k = size ; for ( i = 0 ; i < size - 1 ; i++, k-- ) { current = first ; next = first.next ; for ( j = 1 ; j < k ; j++ ) { if ( current.data > next.data ) { tempData = current.data ; current.data = next.data; next.data = tempData ; tempKey = current.key; current.key = next.key; next.key = tempKey; } current = current.next; next = next.next; } } }
Reverse Operation
Following code demonstrate reversing a single pnked pst.
pubpc LinkedList reverse() { LinkedList reversedpst = new LinkedList(); Link nextLink = null; reversedpst.insertFirst(first.key, first.data); Link currentLink = first; // Until no more data in pst, // insert current pnk before first and move ahead. while(currentLink.next != null){ nextLink = currentLink.next; // Insert at start of new pst. reversedpst.insertFirst(nextLink.key, nextLink.data); //advance to next node currentLink = currentLink.next; } return reversedpst; }
Concatenate Operation
Following code demonstrate reversing a single pnked pst.
pubpc void concatenate(LinkedList pst){ if(first == null){ first = pst.first; } if(pst.first == null){ return; } Link temp = first; while(temp.next !=null) { temp = temp.next; } temp.next = pst.first; }
Demo
Link.javapackage com.tutorialspoint.pst; pubpc class Link { pubpc int key; pubpc int data; pubpc Link next; pubpc Link(int key, int data){ this.key = key; this.data = data; } pubpc void display(){ System.out.print("{"+key+","+data+"}"); } }LinkedList.java
package com.tutorialspoint.pst; pubpc class LinkedList { //this pnk always point to first Link //in the Linked List private Link first; // create an empty pnked pst pubpc LinkedList(){ first = null; } //insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); //point it to old first node pnk.next = first; //point first to new first node first = pnk; } //delete first item pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; //mark next to first pnk as first first = first.next; //return the deleted pnk return tempLink; } //display the pst pubpc void display(){ //start from the beginning Link current = first; //navigate till the end of the pst System.out.print("[ "); while(current != null){ //print data current.display(); //move to next item current = current.next; System.out.print(" "); } System.out.print(" ]"); } //find a pnk with given key pubpc Link find(int key){ //start from the first pnk Link current = first; //if pst is empty if(first == null){ return null; } //navigate through pst while(current.key != key){ //if it is last node if(current.next == null){ return null; }else{ //go to next pnk current = current.next; } } //if data found, return the current Link return current; } //delete a pnk with given key pubpc Link delete(int key){ //start from the first pnk Link current = first; Link previous = null; //if pst is empty if(first == null){ return null; } //navigate through pst while(current.key != key){ //if it is last node if(current.next == null){ return null; }else{ //store reference to current pnk previous = current; //move to next pnk current = current.next; } } //found a match, update the pnk if(current == first) { //change first to point to next pnk first = first.next; }else { //bypass the current pnk previous.next = current.next; } return current; } //is pst empty pubpc boolean isEmpty(){ return first == null; } pubpc int length(){ int length = 0; for(Link current = first; current!=null; current = current.next){ length++; } return length; } pubpc void sort(){ int i, j, k, tempKey, tempData ; Link current,next; int size = length(); k = size ; for ( i = 0 ; i < size - 1 ; i++, k-- ) { current = first ; next = first.next ; for ( j = 1 ; j < k ; j++ ) { if ( current.data > next.data ) { tempData = current.data ; current.data = next.data; next.data = tempData ; tempKey = current.key; current.key = next.key; next.key = tempKey; } current = current.next; next = next.next; } } } pubpc LinkedList reverse() { LinkedList reversedpst = new LinkedList(); Link nextLink = null; reversedpst.insertFirst(first.key, first.data); Link currentLink = first; // Until no more data in pst, // insert current pnk before first and move ahead. while(currentLink.next != null){ nextLink = currentLink.next; // Insert at start of new pst. reversedpst.insertFirst(nextLink.key, nextLink.data); //advance to next node currentLink = currentLink.next; } return reversedpst; } pubpc void concatenate(LinkedList pst){ if(first == null){ first = pst.first; } if(pst.first == null){ return; } Link temp = first; while(temp.next !=null) { temp = temp.next; } temp.next = pst.first; } }LinkedListDemo.java
package com.tutorialspoint.pst; pubpc class LinkedListDemo { pubpc static void main(String args[]){ LinkedList pst = new LinkedList(); pst.insertFirst(1, 10); pst.insertFirst(2, 20); pst.insertFirst(3, 30); pst.insertFirst(4, 1); pst.insertFirst(5, 40); pst.insertFirst(6, 56); System.out.print(" Original List: "); pst.display(); System.out.println(""); while(!pst.isEmpty()){ Link temp = pst.deleteFirst(); System.out.print("Deleted value:"); temp.display(); System.out.println(""); } System.out.print("List after deleting all items: "); pst.display(); System.out.println(""); pst.insertFirst(1, 10); pst.insertFirst(2, 20); pst.insertFirst(3, 30); pst.insertFirst(4, 1); pst.insertFirst(5, 40); pst.insertFirst(6, 56); System.out.print("Restored List: "); pst.display(); System.out.println(""); Link foundLink = pst.find(4); if(foundLink != null){ System.out.print("Element found: "); foundLink.display(); System.out.println(""); }else{ System.out.println("Element not found."); } pst.delete(4); System.out.print("List after deleting an item: "); pst.display(); System.out.println(""); foundLink = pst.find(4); if(foundLink != null){ System.out.print("Element found: "); foundLink.display(); System.out.println(""); }else{ System.out.print("Element not found. {4,1}"); } System.out.println(""); pst.sort(); System.out.print("List after sorting the data: "); pst.display(); System.out.println(""); System.out.print("Reverse of the pst: "); LinkedList pst1 = pst.reverse(); pst1.display(); System.out.println(""); LinkedList pst2 = new LinkedList(); pst2.insertFirst(9, 50); pst2.insertFirst(8, 40); pst2.insertFirst(7, 20); pst.concatenate(pst2); System.out.print("List after concatenation: "); pst.display(); System.out.println(""); } }
If we compile and run the above program then it would produce following result:
Original List: [ {6,56} {5,40} {4,1} {3,30} {2,20} {1,10} ] Deleted value:{6,56} Deleted value:{5,40} Deleted value:{4,1} Deleted value:{3,30} Deleted value:{2,20} Deleted value:{1,10} List after deleting all items: [ ] Restored List: [ {6,56} {5,40} {4,1} {3,30} {2,20} {1,10} ] Element found: {4,1} List after deleting an item: [ {6,56} {5,40} {3,30} {2,20} {1,10} ] Element not found. {4,1} List after sorting the data: [ {1,10} {2,20} {3,30} {5,40} {6,56} ] Reverse of the pst: [ {6,56} {5,40} {3,30} {2,20} {1,10} ] List after concatenation: [ {1,10} {2,20} {3,30} {5,40} {6,56} {7,20} {8,40} {9,50} ]
DSA using Java - Doubly Linked List
Doubly Linked List Basics
Doubly Linked List is a variation of Linked pst in which navigation is possible in both ways either forward and backward easily as compared to Single Linked List. Following are important terms to understand the concepts of doubly Linked List
Link − Each Link of a pnked pst can store a data called an element.
Next − Each Link of a pnked pst contain a pnk to next pnk called Next.
Prev − Each Link of a pnked pst contain a pnk to previous pnk called Prev.
LinkedList − A LinkedList contains the connection pnk to the first Link called First and to the last pnk called Last.
Doubly Linked List Representation
As per above shown illustration, following are the important points to be considered.
Doubly LinkedList contains an pnk element called first and last.
Each Link carries a data field(s) and a Link Field called next.
Each Link is pnked with its next pnk using its next pnk.
Each Link is pnked with its previous pnk using its prev pnk.
Last Link carries a Link as null to mark the end of the pst.
Basic Operations
Following are the basic operations supported by an pst.
Insertion − add an element at the beginning of the pst.
Deletion − delete an element at the beginning of the pst.
Insert Last − add an element in the end of the pst.
Delete Last − delete an element from the end of the pst.
Insert After − add an element after an item of the pst.
Delete − delete an element from the pst using key.
Display forward − displaying complete pst in forward manner.
Display backward − displaying complete pst in backward manner.
Insertion Operation
Following code demonstrate insertion operation at beginning in a doubly pnked pst.
//insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); if(isEmpty()){ //make it the last pnk last = pnk; }else { //update first prev pnk first.prev = pnk; } //point it to old first pnk pnk.next = first; //point first to new first pnk first = pnk; }
Deletion Operation
Following code demonstrate deletion operation at beginning in a doubly pnked pst.
//delete pnk at the first location pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; //if only one pnk if(first.next == null){ last = null; }else { first.next.prev = null; } first = first.next; //return the deleted pnk return tempLink; }
Insertion at End Operation
Following code demonstrate insertion operation at last position in a doubly pnked pst.
//insert pnk at the last location pubpc void insertLast(int key, int data){ //create a pnk Link pnk = new Link(key,data); if(isEmpty()){ //make it the last pnk last = pnk; }else { //make pnk a new last pnk last.next = pnk; //mark old last node as prev of new pnk pnk.prev = last; } //point last to new last node last = pnk; }
Demo
Link.java
package com.tutorialspoint.pst; pubpc class Link { pubpc int key; pubpc int data; pubpc Link next; pubpc Link prev; pubpc Link(int key, int data){ this.key = key; this.data = data; } pubpc void display(){ System.out.print("{"+key+","+data+"}"); } }
DoublyLinkedList.java
package com.tutorialspoint.pst; pubpc class DoublyLinkedList { //this pnk always point to first Link private Link first; //this pnk always point to last Link private Link last; // create an empty pnked pst pubpc DoublyLinkedList(){ first = null; last = null; } //is pst empty pubpc boolean isEmpty(){ return first == null; } //insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); if(isEmpty()){ //make it the last pnk last = pnk; }else { //update first prev pnk first.prev = pnk; } //point it to old first pnk pnk.next = first; //point first to new first pnk first = pnk; } //insert pnk at the last location pubpc void insertLast(int key, int data){ //create a pnk Link pnk = new Link(key,data); if(isEmpty()){ //make it the last pnk last = pnk; }else { //make pnk a new last pnk last.next = pnk; //mark old last node as prev of new pnk pnk.prev = last; } //point last to new last node last = pnk; } //delete pnk at the first location pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; //if only one pnk if(first.next == null){ last = null; }else { first.next.prev = null; } first = first.next; //return the deleted pnk return tempLink; } //delete pnk at the last location pubpc Link deleteLast(){ //save reference to last pnk Link tempLink = last; //if only one pnk if(first.next == null){ first = null; }else { last.prev.next = null; } last = last.prev; //return the deleted pnk return tempLink; } //display the pst in from first to last pubpc void displayForward(){ //start from the beginning Link current = first; //navigate till the end of the pst System.out.print("[ "); while(current != null){ //print data current.display(); //move to next item current = current.next; System.out.print(" "); } System.out.print(" ]"); } //display the pst from last to first pubpc void displayBackward(){ //start from the last Link current = last; //navigate till the start of the pst System.out.print("[ "); while(current != null){ //print data current.display(); //move to next item current = current.prev; System.out.print(" "); } System.out.print(" ]"); } //delete a pnk with given key pubpc Link delete(int key){ //start from the first pnk Link current = first; //if pst is empty if(first == null){ return null; } //navigate through pst while(current.key != key){ //if it is last node if(current.next == null){ return null; }else{ //move to next pnk current = current.next; } } //found a match, update the pnk if(current == first) { //change first to point to next pnk first = current.next; }else { //bypass the current pnk current.prev.next = current.next; } if(current == last){ //change last to point to prev pnk last = current.prev; }else { current.next.prev = current.prev; } return current; } pubpc boolean insertAfter(int key, int newKey, int data){ //start from the first pnk Link current = first; //if pst is empty if(first == null){ return false; } //navigate through pst while(current.key != key){ //if it is last node if(current.next == null){ return false; }else{ //move to next pnk current = current.next; } } Link newLink = new Link(newKey,data); if(current==last) { newLink.next = null; last = newLink; } else { newLink.next = current.next; current.next.prev = newLink; } newLink.prev = current; current.next = newLink; return true; } }
DoublyLinkedListDemo.java
package com.tutorialspoint.pst; pubpc class DoublyLinkedListDemo { pubpc static void main(String args[]){ DoublyLinkedList pst = new DoublyLinkedList(); pst.insertFirst(1, 10); pst.insertFirst(2, 20); pst.insertFirst(3, 30); pst.insertLast(4, 1); pst.insertLast(5, 40); pst.insertLast(6, 56); System.out.print(" List (First to Last): "); pst.displayForward(); System.out.println(""); System.out.print(" List (Last to first): "); pst.displayBackward(); System.out.print(" List , after deleting first record: "); pst.deleteFirst(); pst.displayForward(); System.out.print(" List , after deleting last record: "); pst.deleteLast(); pst.displayForward(); System.out.print(" List , insert after key(4) : "); pst.insertAfter(4,7, 13); pst.displayForward(); System.out.print(" List , after delete key(4) : "); pst.delete(4); pst.displayForward(); } }
If we compile and run the above program then it would produce following result −
List (First to Last): [ {3,30} {2,20} {1,10} {4,1} {5,40} {6,56} ] List (Last to first): [ {6,56} {5,40} {4,1} {1,10} {2,20} {3,30} ] List (First to Last) after deleting first record: [ {2,20} {1,10} {4,1} {5,40} {6,56} ] List (First to Last) after deleting last record: [ {2,20} {1,10} {4,1} {5,40} ] List (First to Last) insert after key(4) : [ {2,20} {1,10} {4,1} {7,13} {5,40} ] List (First to Last) after delete key(4) : [ {2,20} {1,10} {7,13} {5,40} ]
DSA using Java - Circular Linked List
Circular Linked List Basics
Circular Linked List is a variation of Linked pst in which first element points to last element and last element points to first element. Both Singly Linked List and Doubly Linked List can be made into as circular pnked pst
Singly Linked List as Circular
Doubly Linked List as Circular
As per above shown illustrations, following are the important points to be considered.
Last Link next points to first pnk of the pst in both cases of singly as well as doubly pnked pst.
First Link s prev points to the last of the pst in case of doubly pnked pst.
Basic Operations
Following are the important operations supported by a circular pst.
insert − insert an element in the start of the pst.
delete − insert an element from the start of the pst.
display − display the pst.
length Operation
Following code demonstrate insertion operation at in a circular pnked pst based on single pnked pst.
//insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); if (isEmpty()) { first = pnk; first.next = first; } else{ //point it to old first node pnk.next = first; //point first to new first node first = pnk; } }
Deletion Operation
Following code demonstrate deletion operation at in a circular pnked pst based on single pnked pst.
//delete pnk at the first location pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; //if only one pnk if(first.next == null){ last = null; }else { first.next.prev = null; } first = first.next; //return the deleted pnk return tempLink; }
Display List Operation
Following code demonstrate display pst operation in a circular pnked pst.
pubpc void display(){ //start from the beginning Link current = first; //navigate till the end of the pst System.out.print("[ "); if(first != null){ while(current.next != current){ //print data current.display(); //move to next item current = current.next; System.out.print(" "); } } System.out.print(" ]"); }
Demo
Link.java
package com.tutorialspoint.pst; pubpc class CircularLinkedList { //this pnk always point to first Link private Link first; // create an empty pnked pst pubpc CircularLinkedList(){ first = null; } pubpc boolean isEmpty(){ return first == null; } pubpc int length(){ int length = 0; //if pst is empty if(first == null){ return 0; } Link current = first.next; while(current != first){ length++; current = current.next; } return length; } //insert pnk at the first location pubpc void insertFirst(int key, int data){ //create a pnk Link pnk = new Link(key,data); if (isEmpty()) { first = pnk; first.next = first; } else{ //point it to old first node pnk.next = first; //point first to new first node first = pnk; } } //delete first item pubpc Link deleteFirst(){ //save reference to first pnk Link tempLink = first; if(first.next == first){ first = null; return tempLink; } //mark next to first pnk as first first = first.next; //return the deleted pnk return tempLink; } pubpc void display(){ //start from the beginning Link current = first; //navigate till the end of the pst System.out.print("[ "); if(first != null){ while(current.next != current){ //print data current.display(); //move to next item current = current.next; System.out.print(" "); } } System.out.print(" ]"); } }
DoublyLinkedListDemo.java
package com.tutorialspoint.pst; pubpc class CircularLinkedListDemo { pubpc static void main(String args[]){ CircularLinkedList pst = new CircularLinkedList(); pst.insertFirst(1, 10); pst.insertFirst(2, 20); pst.insertFirst(3, 30); pst.insertFirst(4, 1); pst.insertFirst(5, 40); pst.insertFirst(6, 56); System.out.print(" Original List: "); pst.display(); System.out.println(""); while(!pst.isEmpty()){ Link temp = pst.deleteFirst(); System.out.print("Deleted value:"); temp.display(); System.out.println(""); } System.out.print("List after deleting all items: "); pst.display(); System.out.println(""); } }
If we compile and run the above program then it would produce following result −
Original List: [ {6,56} {5,40} {4,1} {3,30} {2,20} ] Deleted value:{6,56} Deleted value:{5,40} Deleted value:{4,1} Deleted value:{3,30} Deleted value:{2,20} Deleted value:{1,10} List after deleting all items: [ ]
DSA using Java - Stack
Overview
Stack is kind of data structure which allows operations on data only at one end. It allows access to the last inserted data only. Stack is also called LIFO (Last In First Out) data structure and Push and Pop operations are related in such a way that only last item pushed (added to stack) can be popped (removed from the stack).
Stack Representation
We re going to implement Stack using array in this article.
Basic Operations
Following are two primary operations of a stack which are following.
Push − push an element at the top of the stack.
Pop − pop an element from the top of the stack.
There is few more operations supported by stack which are following.
Peek − get the top element of the stack.
isFull − check if stack is full.
isEmpty − check if stack is empty.
Push Operation
Whenever an element is pushed into stack, stack stores that element at the top of the storage and increments the top index for later use. If storage is full then an error message is usually shown.
// push item on the top of the stack pubpc void push(int data) { if(!isFull()){ // increment top by 1 and insert data intArray[++top] = data; }else{ System.out.println("Cannot add data. Stack is full."); } }
Pop Operation
Whenever an element is to be popped from stack, stack retrives the element from the top of the storage and decrements the top index for later use.
// pop item from the top of the stack pubpc int pop() { // retrieve data and decrement the top by 1 return intArray[top--]; }
Stack Implementation
Stack.java
package com.tutorialspoint.datastructure; pubpc class Stack { private int size; // size of the stack private int[] intArray; // stack storage private int top; // top of the stack // Constructor pubpc Stack(int size){ this.size = size; intArray = new int[size]; //initiapze array top = -1; //stack is initially empty } // Operation : Push // push item on the top of the stack pubpc void push(int data) { if(!isFull()){ // increment top by 1 and insert data intArray[++top] = data; }else{ System.out.println("Cannot add data. Stack is full."); } } // Operation : Pop // pop item from the top of the stack pubpc int pop() { //retrieve data and decrement the top by 1 return intArray[top--]; } // Operation : Peek // view the data at top of the stack pubpc int peek() { //retrieve data from the top return intArray[top]; } // Operation : isFull // return true if stack is full pubpc boolean isFull(){ return (top == size-1); } // Operation : isEmpty // return true if stack is empty pubpc boolean isEmpty(){ return (top == -1); } }
Demo Program
StackDemo.java
package com.tutorialspoint.datastructure; pubpc class StackDemo { pubpc static void main (String[] args){ // make a new stack Stack stack = new Stack(10); // push items on to the stack stack.push(3); stack.push(5); stack.push(9); stack.push(1); stack.push(12); stack.push(15); System.out.println("Element at top of the stack: " + stack.peek()); System.out.println("Elements: "); // print stack data while(!stack.isEmpty()){ int data = stack.pop(); System.out.println(data); } System.out.println("Stack full: " + stack.isFull()); System.out.println("Stack empty: " + stack.isEmpty()); } }
If we compile and run the above program then it would produce following result −
Element at top of the stack: 15 Elements: 15 12 1 9 5 3 Stack full: false Stack empty: true
DSA using Java - Parsing Expressions
Ordinary airthmetic expressions pke 2*(3*4) are easier for human mind to parse but for an algorithm it would be pretty difficult to parse such an expression. To ease this difficulty, an airthmetic expression can be parsed by an algorithm using a two step approach.
Transform the provided arithmetic expression to postfix notation.
Evaluate the postfix notation.
Infix Notation
Normal airthmetic expression follows Infix Notation in which operator is in between the operands. For example A+B here A is first operand, B is second operand and + is the operator acting on the two operands.
Postfix Notation
Postfix notation varies from normal arithmetic expression or infix notation in a way that the operator follows the operands. For example, consider the following examples
Sr.No | Infix Notation | Postfix Notation |
---|---|---|
1 | A+B | AB+ |
2 | (A+B)*C | AB+C* |
3 | A*(B+C) | ABC+* |
4 | A/B+C/D | AB/CD/+ |
5 | (A+B)*(C+D) | AB+CD+* |
6 | ((A+B)*C)-D | AB+C*D- |
Infix to PostFix Conversion
Before looking into the way to translate Infix to postfix notation, we need to consider following basics of infix expression evaluation.
Evaluation of the infix expression starts from left to right.
Keep precedence in mind, for example * has higher precedence over +. For example
2+3*4 = 2+12.
2+3*4 = 14.
Override precedence using brackets, For example
(2+3)*4 = 5*4.
(2+3)*4= 20.
Now let us transform a simple infix expression A+B*C into a postfix expression manually.
Step | Character read | Infix Expressed parsed so far | Postfix expression developed so far | Remarks |
---|---|---|---|---|
1 | A | A | A | |
2 | + | A+ | A | |
3 | B | A+B | AB | |
4 | * | A+B* | AB | + can not be copied as * has higher precedence. |
5 | C | A+B*C | ABC | |
6 | A+B*C | ABC* | copy * as two operands are there B and C | |
7 | A+B*C | ABC*+ | copy + as two operands are there BC and A |
Now let us transform the above infix expression A+B*C into a postfix expression using stack.
Step | Character read | Infix Expressed parsed so far | Postfix expression developed so far | Stack Contents | Remarks |
---|---|---|---|---|---|
1 | A | A | A | ||
2 | + | A+ | A | + | push + operator in a stack. |
3 | B | A+B | AB | + | |
4 | * | A+B* | AB | +* | Precedence of operator * is higher than +. push * operator in the stack. Otherwise, + would pop up. |
5 | C | A+B*C | ABC | +* | |
6 | A+B*C | ABC* | + | No more operand, pop the * operator. | |
7 | A+B*C | ABC*+ | Pop the + operator. |
Now let us see another example, by transforming infix expression A*(B+C) into a postfix expression using stack.
Step | Character read | Infix Expressed parsed so far | Postfix expression developed so far | Stack Contents | Remarks |
---|---|---|---|---|---|
1 | A | A | A | ||
2 | * | A* | A | * | push * operator in a stack. |
3 | ( | A*( | A | *( | push ( in the stack. |
4 | B | A*(B | AB | *( | |
5 | + | A*(B+ | AB | *(+ | push + in the stack. |
6 | C | A*(B+C | ABC | *(+ | |
7 | ) | A*(B+C) | ABC+ | *( | Pop the + operator. |
8 | A*(B+C) | ABC+ | * | Pop the ( operator. | |
9 | A*(B+C) | ABC+* | Pop the rest of the operator(s). |
Demo program
Now we ll demonstrate the use of stack to convert infix expression to postfix expression and then evaluate the postfix expression.
Stack.javapackage com.tutorialspoint.expression; pubpc class Stack { private int size; private int[] intArray; private int top; //Constructor pubpc Stack(int size){ this.size = size; intArray = new int[size]; top = -1; } //push item on the top of the stack pubpc void push(int data) { if(!isFull()){ //increment top by 1 and insert data intArray[++top] = data; }else{ System.out.println("Cannot add data. Stack is full."); } } //pop item from the top of the stack pubpc int pop() { //retrieve data and decrement the top by 1 return intArray[top--]; } //view the data at top of the stack pubpc int peek() { //retrieve data from the top return intArray[top]; } //return true if stack is full pubpc boolean isFull(){ return (top == size-1); } //return true if stack is empty pubpc boolean isEmpty(){ return (top == -1); } }
InfixToPostFix.java
package com.tutorialspoint.expression; pubpc class InfixToPostfix { private Stack stack; private String input = ""; private String output = ""; pubpc InfixToPostfix(String input){ this.input = input; stack = new Stack(input.length()); } pubpc String translate(){ for(int i=0;i<input.length();i++){ char ch = input.charAt(i); switch(ch){ case + : case - : gotOperator(ch, 1); break; case * : case / : gotOperator(ch, 2); break; case ( : stack.push(ch); break; case ) : gotParenthesis(ch); break; default: output = output+ch; break; } } while(!stack.isEmpty()){ output = output + (char)stack.pop(); } return output; } //got operator from input pubpc void gotOperator(char operator, int precedence){ while(!stack.isEmpty()){ char prevOperator = (char)stack.pop(); if(prevOperator == ( ){ stack.push(prevOperator); break; }else{ int precedence1; if(prevOperator == + || prevOperator == - ){ precedence1 = 1; }else{ precedence1 = 2; } if(precedence1 < precedence){ stack.push(Character.getNumericValue(prevOperator)); break; }else{ output = output + prevOperator; } } } stack.push(operator); } //got operator from input pubpc void gotParenthesis(char parenthesis){ while(!stack.isEmpty()){ char ch = (char)stack.pop(); if(ch == ( ){ break; }else{ output = output + ch; } } } }
PostFixParser.java
package com.tutorialspoint.expression; pubpc class PostFixParser { private Stack stack; private String input; pubpc PostFixParser(String postfixExpression){ input = postfixExpression; stack = new Stack(input.length()); } pubpc int evaluate(){ char ch; int firstOperand; int secondOperand; int tempResult; for(int i=0;i<input.length();i++){ ch = input.charAt(i); if(ch >= 0 && ch <= 9 ){ stack.push(Character.getNumericValue(ch)); }else{ firstOperand = stack.pop(); secondOperand = stack.pop(); switch(ch){ case + : tempResult = firstOperand + secondOperand; break; case - : tempResult = firstOperand - secondOperand; break; case * : tempResult = firstOperand * secondOperand; break; case / : tempResult = firstOperand / secondOperand; break; default: tempResult = 0; } stack.push(tempResult); } } return stack.pop(); } }
PostFixDemo.java
package com.tutorialspoint.expression; pubpc class PostFixDemo { pubpc static void main(String args[]){ String input = "1*(2+3)"; InfixToPostfix translator = new InfixToPostfix(input); String output = translator.translate(); System.out.println("Infix expression is: " + input); System.out.println("Postfix expression is: " + output); PostFixParser parser = new PostFixParser(output); System.out.println("Result is: " + parser.evaluate()); } }
If we compile and run the above program then it would produce following result −
Infix expression is: 1*(2+3) Postfix expression is: 123+* Result is: 5
DSA using Java - Queue
Overview
Queue is kind of data structure similar to stack with primary difference that the first item inserted is the first item to be removed (FIFO - First In First Out) where stack is based on LIFO, Last In First Out principal.
Queue Representation
Basic Operations
insert / enqueue − add an item to the rear of the queue.
remove / dequeue − remove an item from the front of the queue.
We re going to implement Queue using array in this article. There is few more operations supported by queue which are following.
Peek − get the element at front of the queue.
isFull − check if queue is full.
isEmpty − check if queue is empty.
Insert / Enqueue Operation
Whenever an element is inserted into queue, queue increments the rear index for later use and stores that element at the rear end of the storage. If rear end reaches to the last index and it is wrapped to the bottom location. Such an arrangement is called wrap around and such queue is circular queue. This method is also termed as enqueue operation.
pubpc void insert(int data){ if(!isFull()){ if(rear == MAX-1){ rear = -1; } intArray[++rear] = data; itemCount++; } }
Remove / Dequeue Operation
Whenever an element is to be removed from queue, queue get the element using front index and increments the front index. As a wrap around arrangement, if front index is more than array s max index, it is set to 0.
pubpc int remove(){ int data = intArray[front++]; if(front == MAX){ front = 0; } itemCount--; return data; }
Queue Implementation
Queue.java
package com.tutorialspoint.datastructure; pubpc class Queue { private final int MAX; private int[] intArray; private int front; private int rear; private int itemCount; pubpc Queue(int size){ MAX = size; intArray = new int[MAX]; front = 0; rear = -1; itemCount = 0; } pubpc void insert(int data){ if(!isFull()){ if(rear == MAX-1){ rear = -1; } intArray[++rear] = data; itemCount++; } } pubpc int remove(){ int data = intArray[front++]; if(front == MAX){ front = 0; } itemCount--; return data; } pubpc int peek(){ return intArray[front]; } pubpc boolean isEmpty(){ return itemCount == 0; } pubpc boolean isFull(){ return itemCount == MAX; } pubpc int size(){ return itemCount; } }
Demo Program
QueueDemo.java
package com.tutorialspoint.datastructure; pubpc class QueueDemo { pubpc static void main(String[] args){ Queue queue = new Queue(6); //insert 5 items queue.insert(3); queue.insert(5); queue.insert(9); queue.insert(1); queue.insert(12); // front : 0 // rear : 4 // ------------------ // index : 0 1 2 3 4 // ------------------ // queue : 3 5 9 1 12 queue.insert(15); // front : 0 // rear : 5 // --------------------- // index : 0 1 2 3 4 5 // --------------------- // queue : 3 5 9 1 12 15 if(queue.isFull()){ System.out.println("Queue is full!"); } //remove one item int num = queue.remove(); System.out.println("Element removed: "+num); // front : 1 // rear : 5 // ------------------- // index : 1 2 3 4 5 // ------------------- // queue : 5 9 1 12 15 //insert more items queue.insert(16); // front : 1 // rear : -1 // ---------------------- // index : 0 1 2 3 4 5 // ---------------------- // queue : 16 5 9 1 12 15 //As queue is full, elements will not be inserted. queue.insert(17); queue.insert(18); // ---------------------- // index : 0 1 2 3 4 5 // ---------------------- // queue : 16 5 9 1 12 15 System.out.println("Element at front: "+queue.peek()); System.out.println("----------------------"); System.out.println("index : 5 4 3 2 1 0"); System.out.println("----------------------"); System.out.print("Queue: "); while(!queue.isEmpty()){ int n = queue.remove(); System.out.print(n +" "); } } }
If we compile and run the above program then it would produce following result −
Queue is full! Element removed: 3 Element at front: 5 ---------------------- index : 5 4 3 2 1 0 ---------------------- Queue: 5 9 1 12 15 16
DSA using Java - Priority Queue
Overview
Priority Queue is more specipzed data structure than Queue. Like ordinary queue, priority queue has same method but with a major difference. In Priority queue items are ordered by key value so that item with the lowest value of key is at front and item with the highest value of key is at rear or vice versa. So we re assigned priority to item based on its key value. Lower the value, higher the priority. Following are the principal methods of a Priority Queue.
Basic Operations
insert / enqueue − add an item to the rear of the queue.
remove / dequeue − remove an item from the front of the queue.
Priority Queue Representation
We re going to implement Queue using array in this article. There is few more operations supported by queue which are following.
Peek − get the element at front of the queue.
isFull − check if queue is full.
isEmpty − check if queue is empty.
Insert / Enqueue Operation
Whenever an element is inserted into queue, priority queue inserts the item according to its order. Here we re assuming that data with high value has low priority.
pubpc void insert(int data){ int i =0; if(!isFull()){ // if queue is empty, insert the data if(itemCount == 0){ intArray[itemCount++] = data; }else{ // start from the right end of the queue for(i = itemCount - 1; i >= 0; i-- ){ // if data is larger, shift existing item to right end if(data > intArray[i]){ intArray[i+1] = intArray[i]; }else{ break; } } // insert the data intArray[i+1] = data; itemCount++; } } }
Remove / Dequeue Operation
Whenever an element is to be removed from queue, queue get the element using item count. Once element is removed. Item count is reduced by one.
pubpc int remove(){ return intArray[--itemCount]; }
Priority Queue Implementation
PriorityQueue.java
package com.tutorialspoint.datastructure; pubpc class PriorityQueue { private final int MAX; private int[] intArray; private int itemCount; pubpc PriorityQueue(int size){ MAX = size; intArray = new int[MAX]; itemCount = 0; } pubpc void insert(int data){ int i =0; if(!isFull()){ // if queue is empty, insert the data if(itemCount == 0){ intArray[itemCount++] = data; }else{ // start from the right end of the queue for(i = itemCount - 1; i >= 0; i-- ){ // if data is larger, shift existing item to right end if(data > intArray[i]){ intArray[i+1] = intArray[i]; }else{ break; } } // insert the data intArray[i+1] = data; itemCount++; } } } pubpc int remove(){ return intArray[--itemCount]; } pubpc int peek(){ return intArray[itemCount - 1]; } pubpc boolean isEmpty(){ return itemCount == 0; } pubpc boolean isFull(){ return itemCount == MAX; } pubpc int size(){ return itemCount; } }
Demo Program
PriorityQueueDemo.java
package com.tutorialspoint.datastructure; pubpc class PriorityQueueDemo { pubpc static void main(String[] args){ PriorityQueue queue = new PriorityQueue(6); //insert 5 items queue.insert(3); queue.insert(5); queue.insert(9); queue.insert(1); queue.insert(12); // ------------------ // index : 0 1 2 3 4 // ------------------ // queue : 12 9 5 3 1 queue.insert(15); // --------------------- // index : 0 1 2 3 4 5 // --------------------- // queue : 15 12 9 5 3 1 if(queue.isFull()){ System.out.println("Queue is full!"); } //remove one item int num = queue.remove(); System.out.println("Element removed: "+num); // --------------------- // index : 0 1 2 3 4 // --------------------- // queue : 15 12 9 5 3 //insert more items queue.insert(16); // ---------------------- // index : 0 1 2 3 4 5 // ---------------------- // queue : 16 15 12 9 5 3 //As queue is full, elements will not be inserted. queue.insert(17); queue.insert(18); // ---------------------- // index : 0 1 2 3 4 5 // ---------------------- // queue : 16 15 12 9 5 3 System.out.println("Element at front: "+queue.peek()); System.out.println("----------------------"); System.out.println("index : 5 4 3 2 1 0"); System.out.println("----------------------"); System.out.print("Queue: "); while(!queue.isEmpty()){ int n = queue.remove(); System.out.print(n +" "); } } }
If we compile and run the above program then it would produce following result −
Queue is full! Element removed: 1 Element at front: 3 ---------------------- index : 5 4 3 2 1 0 ---------------------- Queue: 3 5 9 12 15 16
DSA using Java - Tree
Overview
Tree represents nodes connected by edges. We ll going to discuss binary tree or binary search tree specifically.
Binary Tree is a special datastructure used for data storage purposes. A binary tree has a special condition that each node can have two children at maximum. A binary tree have benefits of both an ordered array and a pnked pst as search is as quick as in sorted array and insertion or deletion operation are as fast as in pnked pst.
Terms
Following are important terms with respect to tree.
Path − Path refers to sequence of nodes along the edges of a tree.
Root − Node at the top of the tree is called root. There is only one root per tree and one path from root node to any node.
Parent − Any node except root node has one edge upward to a node called parent.
Child − Node below a given node connected by its edge downward is called its child node.
Leaf − Node which does not have any child node is called leaf node.
Subtree − Subtree represents descendents of a node.
Visiting − Visiting refers to checking value of a node when control is on the node.
Traversing − Traversing means passing through nodes in a specific order.
Levels − Level of a node represents the generation of a node. If root node is at level 0, then its next child node is at level 1, its grandchild is at level 2 and so on.
keys − Key represents a value of a node based on which a search operation is to be carried out for a node.
Binary Search tree exibits a special behaviour. A node s left child must have value less than its parent s value and node s right child must have value greater than it s parent value.
Binary Search Tree Representation
We re going to implement tree using node object and connecting them through references.
Basic Operations
Following are basic primary operations of a tree which are following.
Search − search an element in a tree.
Insert − insert an element in a tree.
Preorder Traversal − traverse a tree in a preorder manner.
Inorder Traversal − traverse a tree in an inorder manner.
Postorder Traversal − traverse a tree in a postorder manner.
Node
Define a node having some data, references to its left and right child nodes.
pubpc class Node { pubpc int data; pubpc Node leftChild; pubpc Node rightChild; pubpc Node(){} pubpc void display(){ System.out.print("("+data+ ")"); } }
Search Operation
Whenever an element is to be search. Start search from root node then if data is less than key value, search element in left subtree otherwise search element in right subtree. Follow the same algorithm for each node.
pubpc Node search(int data){ Node current = root; System.out.print("Visiting elements: "); while(current.data != data){ if(current != null) System.out.print(current.data + " "); //go to left tree if(current.data > data){ current = current.leftChild; }//else go to right tree else{ current = current.rightChild; } //not found if(current == null){ return null; } } return current; }
Insert Operation
Whenever an element is to be inserted. First locate its proper location. Start search from root node then if data is less than key value, search empty location in left subtree and insert the data. Otherwise search empty location in right subtree and insert the data.
pubpc void insert(int data){ Node tempNode = new Node(); tempNode.data = data; //if tree is empty if(root == null){ root = tempNode; }else{ Node current = root; Node parent = null; while(true){ parent = current; //go to left of the tree if(data < parent.data){ current = current.leftChild; //insert to the left if(current == null){ parent.leftChild = tempNode; return; } }//go to right of the tree else{ current = current.rightChild; //insert to the right if(current == null){ parent.rightChild = tempNode; return; } } } } }
Preorder Traversal
It is a simple three step process.
visit root node
traverse left subtree
traverse right subtree
private void preOrder(Node root){ if(root!=null){ System.out.print(root.data + " "); preOrder(root.leftChild); preOrder(root.rightChild); } }
Inorder Traversal
It is a simple three step process.
traverse left subtree
visit root node
traverse right subtree
private void inOrder(Node root){ if(root!=null){ inOrder(root.leftChild); System.out.print(root.data + " "); inOrder(root.rightChild); } }
Postorder Traversal
It is a simple three step process.
traverse left subtree
traverse right subtree
visit root node
private void postOrder(Node root){ if(root!=null){ postOrder(root.leftChild); postOrder(root.rightChild); System.out.print(root.data + " "); } }
Tree Implementation
Node.java
package com.tutorialspoint.datastructure; pubpc class Node { pubpc int data; pubpc Node leftChild; pubpc Node rightChild; pubpc Node(){} pubpc void display(){ System.out.print("("+data+ ")"); } }
Tree.java
package com.tutorialspoint.datastructure; pubpc class Tree { private Node root; pubpc Tree(){ root = null; } pubpc Node search(int data){ Node current = root; System.out.print("Visiting elements: "); while(current.data != data){ if(current != null) System.out.print(current.data + " "); //go to left tree if(current.data > data){ current = current.leftChild; }//else go to right tree else{ current = current.rightChild; } //not found if(current == null){ return null; } } return current; } pubpc void insert(int data){ Node tempNode = new Node(); tempNode.data = data; //if tree is empty if(root == null){ root = tempNode; }else{ Node current = root; Node parent = null; while(true){ parent = current; //go to left of the tree if(data < parent.data){ current = current.leftChild; //insert to the left if(current == null){ parent.leftChild = tempNode; return; } }//go to right of the tree else{ current = current.rightChild; //insert to the right if(current == null){ parent.rightChild = tempNode; return; } } } } } pubpc void traverse(int traversalType){ switch(traversalType){ case 1: System.out.print(" Preorder traversal: "); preOrder(root); break; case 2: System.out.print(" Inorder traversal: "); inOrder(root); break; case 3: System.out.print(" Postorder traversal: "); postOrder(root); break; } } private void preOrder(Node root){ if(root!=null){ System.out.print(root.data + " "); preOrder(root.leftChild); preOrder(root.rightChild); } } private void inOrder(Node root){ if(root!=null){ inOrder(root.leftChild); System.out.print(root.data + " "); inOrder(root.rightChild); } } private void postOrder(Node root){ if(root!=null){ postOrder(root.leftChild); postOrder(root.rightChild); System.out.print(root.data + " "); } } }
Demo Program
TreeDemo.java
package com.tutorialspoint.datastructure; pubpc class TreeDemo { pubpc static void main(String[] args){ Tree tree = new Tree(); /* 11 //Level 0 */ tree.insert(11); /* 11 //Level 0 * | * |---20 //Level 1 */ tree.insert(20); /* 11 //Level 0 * | * 3---|---20 //Level 1 */ tree.insert(3); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | * |--42 //Level 2 */ tree.insert(42); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | * |--42 //Level 2 * | * |--54 //Level 3 */ tree.insert(54); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | * 16--|--42 //Level 2 * | * |--54 //Level 3 */ tree.insert(16); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | * 16--|--42 //Level 2 * | * 32--|--54 //Level 3 */ tree.insert(32); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | | * |--9 16--|--42 //Level 2 * | * 32--|--54 //Level 3 */ tree.insert(9); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | | * |--9 16--|--42 //Level 2 * | | * 4--| 32--|--54 //Level 3 */ tree.insert(4); /* 11 //Level 0 * | * 3---|---20 //Level 1 * | | * |--9 16--|--42 //Level 2 * | | * 4--|--10 32--|--54 //Level 3 */ tree.insert(10); Node node = tree.search(32); if(node!=null){ System.out.print("Element found."); node.display(); System.out.println(); }else{ System.out.println("Element not found."); } Node node1 = tree.search(2); if(node1!=null){ System.out.println("Element found."); node1.display(); System.out.println(); }else{ System.out.println("Element not found."); } //pre-order traversal //root, left ,right tree.traverse(1); //in-order traversal //left, root ,right tree.traverse(2); //post order traversal //left, right, root tree.traverse(3); } }
If we compile and run the above program then it would produce following result −
Visiting elements: 11 20 42 Element found.(32) Visiting elements: 11 3 Element not found. Preorder traversal: 11 3 9 4 10 20 16 42 32 54 Inorder traversal: 3 4 9 10 11 16 20 32 42 54 Postorder traversal: 4 10 9 3 16 32 54 42 20 11
DSA using Java - Hash Table
Overview
HashTable is a datastructure in which insertion and search operations are very fast irrespective of size of the hashtable. It is nearly a constant or O(1). Hash Table uses array as a storage medium and uses hash technique to generate index where an element is to be inserted or to be located from.
Hashing
Hashing is a technique to convert a range of key values into a range of indexes of an array. We re going to use modulo operator to get a range of key values. Consider an example of hashtable of size 20, and following items are to be stored. Item are in (key,value) format.
(1,20)
(2,70)
(42,80)
(4,25)
(12,44)
(14,32)
(17,11)
(13,78)
(37,98)
Sr.No. | Key | Hash | Array Index |
---|---|---|---|
1 | 1 | 1 % 20 = 1 | 1 |
2 | 2 | 2 % 20 = 2 | 2 |
3 | 42 | 42 % 20 = 2 | 2 |
4 | 4 | 4 % 20 = 4 | 4 |
5 | 12 | 12 % 20 = 12 | 12 |
6 | 14 | 14 % 20 = 14 | 14 |
7 | 17 | 17 % 20 = 17 | 17 |
8 | 13 | 13 % 20 = 13 | 13 |
9 | 37 | 37 % 20 = 17 | 17 |
Linear Probing
As we can see, it may happen that the hashing technique used create already used index of the array. In such case, we can search the next empty location in the array by looking into the next cell until we found an empty cell. This technique is called pnear probing.
Sr.No. | Key | Hash | Array Index | After Linear Probing, Array Index |
---|---|---|---|---|
1 | 1 | 1 % 20 = 1 | 1 | 1 |
2 | 2 | 2 % 20 = 2 | 2 | 2 |
3 | 42 | 42 % 20 = 2 | 2 | 3 |
4 | 4 | 4 % 20 = 4 | 4 | 4 |
5 | 12 | 12 % 20 = 12 | 12 | 12 |
6 | 14 | 14 % 20 = 14 | 14 | 14 |
7 | 17 | 17 % 20 = 17 | 17 | 17 |
8 | 13 | 13 % 20 = 13 | 13 | 13 |
9 | 37 | 37 % 20 = 17 | 17 | 18 |
Basic Operations
Following are basic primary operations of a hashtable which are following.
Search − search an element in a hashtable.
Insert − insert an element in a hashtable.
delete − delete an element from a hashtable.
DataItem
Define a data item having some data, and key based on which search is to be conducted in hashtable.
pubpc class DataItem { private int key; private int data; pubpc DataItem(int key, int data){ this.key = key; this.data = data; } pubpc int getKey(){ return key; } pubpc int getData(){ return data; } }
Hash Method
Define a hashing method to compute the hash code of the key of the data item.
pubpc int hashCode(int key){ return key % size; }
Search Operation
Whenever an element is to be searched. Compute the hash code of the key passed and locate the element using that hashcode as index in the array. Use pnear probing to get element ahead if element not found at computed hash code.
pubpc DataItem search(int key){ //get the hash int hashIndex = hashCode(key); //move in array until an empty while(hashArray[hashIndex] !=null){ if(hashArray[hashIndex].getKey() == key) return hashArray[hashIndex]; //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } return null; }
Insert Operation
Whenever an element is to be inserted. Compute the hash code of the key passed and locate the index using that hashcode as index in the array. Use pnear probing for empty location if an element is found at computed hash code.
pubpc void insert(DataItem item){ int key = item.getKey(); //get the hash int hashIndex = hashCode(key); //move in array until an empty or deleted cell while(hashArray[hashIndex] !=null && hashArray[hashIndex].getKey() != -1){ //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } hashArray[hashIndex] = item; }
Delete Operation
Whenever an element is to be deleted. Compute the hash code of the key passed and locate the index using that hashcode as index in the array. Use pnear probing to get element ahead if an element is not found at computed hash code. When found, store a dummy item there to keep performance of hashtable intact.
pubpc DataItem delete(DataItem item){ int key = item.getKey(); //get the hash int hashIndex = hashCode(key); //move in array until an empty while(hashArray[hashIndex] !=null){ if(hashArray[hashIndex].getKey() == key){ DataItem temp = hashArray[hashIndex]; //assign a dummy item at deleted position hashArray[hashIndex] = dummyItem; return temp; } //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } return null; }
HashTable Implementation
DataItem.java
package com.tutorialspoint.datastructure; pubpc class DataItem { private int key; private int data; pubpc DataItem(int key, int data){ this.key = key; this.data = data; } pubpc int getKey(){ return key; } pubpc int getData(){ return data; } }
HashTable.java
package com.tutorialspoint.datastructure; pubpc class HashTable { private DataItem[] hashArray; private int size; private DataItem dummyItem; pubpc HashTable(int size){ this.size = size; hashArray = new DataItem[size]; dummyItem = new DataItem(-1,-1); } pubpc void display(){ for(int i=0; i<size; i++) { if(hashArray[i] != null) System.out.print(" (" +hashArray[i].getKey()+"," +hashArray[i].getData() + ") "); else System.out.print(" ~~ "); } System.out.println(""); } pubpc int hashCode(int key){ return key % size; } pubpc DataItem search(int key){ //get the hash int hashIndex = hashCode(key); //move in array until an empty while(hashArray[hashIndex] !=null){ if(hashArray[hashIndex].getKey() == key) return hashArray[hashIndex]; //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } return null; } pubpc void insert(DataItem item){ int key = item.getKey(); //get the hash int hashIndex = hashCode(key); //move in array until an empty or deleted cell while(hashArray[hashIndex] !=null && hashArray[hashIndex].getKey() != -1){ //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } hashArray[hashIndex] = item; } pubpc DataItem delete(DataItem item){ int key = item.getKey(); //get the hash int hashIndex = hashCode(key); //move in array until an empty while(hashArray[hashIndex] !=null){ if(hashArray[hashIndex].getKey() == key){ DataItem temp = hashArray[hashIndex]; //assign a dummy item at deleted position hashArray[hashIndex] = dummyItem; return temp; } //go to next cell ++hashIndex; //wrap around the table hashIndex %= size; } return null; } }
Demo Program
HashTableDemo.java
package com.tutorialspoint.datastructure; pubpc class HashTableDemo { pubpc static void main(String[] args){ HashTable hashTable = new HashTable(20); hashTable.insert(new DataItem(1, 20)); hashTable.insert(new DataItem(2, 70)); hashTable.insert(new DataItem(42, 80)); hashTable.insert(new DataItem(4, 25)); hashTable.insert(new DataItem(12, 44)); hashTable.insert(new DataItem(14, 32)); hashTable.insert(new DataItem(17, 11)); hashTable.insert(new DataItem(13, 78)); hashTable.insert(new DataItem(37, 97)); hashTable.display(); DataItem item = hashTable.search(37); if(item != null){ System.out.println("Element found: "+ item.getData()); }else{ System.out.println("Element not found"); } hashTable.delete(item); item = hashTable.search(37); if(item != null){ System.out.println("Element found: "+ item.getData()); }else{ System.out.println("Element not found"); } } }
If we compile and run the above program then it would produce following result −
~~ (1,20) (2,70) (42,80) (4,25) ~~ ~~ ~~ ~~ ~~ ~~ ~~ (12,44) (13,78) (14,32) ~~ ~~ (17,11) (37,97) ~~ Element found: 97 Element not found
DSA using Java - Heap
Overview
Heap represents a special tree based data structure used to represent priority queue or for heap sort. We ll going to discuss binary heap tree specifically.
Binary heap tree can be classified as a binary tree with two constraints −
Completeness − Binary heap tree is a complete binary tree except the last level which may not have all elements but elements from left to right should be filled in.
Heapness − All parent nodes should be greater or smaller to their children. If parent node is to be greater than its child then it is called Max heap otherwise it is called Min heap. Max heap is used for heap sort and Min heap is used for priority queue. We re considering Min Heap and will use array implementation for the same.
Basic Operations
Following are basic primary operations of a Min heap which are following.
Insert − insert an element in a heap.
Get Minimum − get minimum element from the heap.
Remove Minimum − remove the minimum element from the heap
Insert Operation
Whenever an element is to be inserted. Insert element at the end of the array. Increase the size of heap by 1.
Heap up the element while heap property is broken. Compare element with parent s value and swap them if required.
pubpc void insert(int value) { size++; intArray[size - 1] = value; heapUp(size - 1); } private void heapUp(int nodeIndex){ int parentIndex, tmp; if (nodeIndex != 0) { parentIndex = getParentIndex(nodeIndex); if (intArray[parentIndex] > intArray[nodeIndex]) { tmp = intArray[parentIndex]; intArray[parentIndex] = intArray[nodeIndex]; intArray[nodeIndex] = tmp; heapUp(parentIndex); } } }
Get Minimum
Get the first element of the array implementing the heap being root.
pubpc int getMinimum(){ return intArray[0]; }
Remove Minimum
Whenever an element is to be removed. Get the last element of the array and reduce size of heap by 1.
Heap down the element while heap property is broken. Compare element with children s value and swap them if required.
pubpc void removeMin() { intArray[0] = intArray[size - 1]; size--; if (size > 0) heapDown(0); } private void heapDown(int nodeIndex){ int leftChildIndex, rightChildIndex, minIndex, tmp; leftChildIndex = getLeftChildIndex(nodeIndex); rightChildIndex = getRightChildIndex(nodeIndex); if (rightChildIndex >= size) { if (leftChildIndex >= size) return; else minIndex = leftChildIndex; } else { if (intArray[leftChildIndex] <= intArray[rightChildIndex]) minIndex = leftChildIndex; else minIndex = rightChildIndex; } if (intArray[nodeIndex] > intArray[minIndex]) { tmp = intArray[minIndex]; intArray[minIndex] = intArray[nodeIndex]; intArray[nodeIndex] = tmp; heapDown(minIndex); } }
Heap Implementation
Heap.java
package com.tutorialspoint.datastructure; pubpc class Heap { private int[] intArray; private int size; pubpc Heap(int size){ intArray = new int[size]; } pubpc boolean isEmpty(){ return size == 0; } pubpc int getMinimum(){ return intArray[0]; } pubpc int getLeftChildIndex(int nodeIndex){ return 2*nodeIndex +1; } pubpc int getRightChildIndex(int nodeIndex){ return 2*nodeIndex +2; } pubpc int getParentIndex(int nodeIndex){ return (nodeIndex -1)/2; } pubpc boolean isFull(){ return size == intArray.length; } pubpc void insert(int value) { size++; intArray[size - 1] = value; heapUp(size - 1); } pubpc void removeMin() { intArray[0] = intArray[size - 1]; size--; if (size > 0) heapDown(0); } /** * Heap up the new element,until heap property is broken. * Steps: * 1. Compare node s value with parent s value. * 2. Swap them, If they are in wrong order. * */ private void heapUp(int nodeIndex){ int parentIndex, tmp; if (nodeIndex != 0) { parentIndex = getParentIndex(nodeIndex); if (intArray[parentIndex] > intArray[nodeIndex]) { tmp = intArray[parentIndex]; intArray[parentIndex] = intArray[nodeIndex]; intArray[nodeIndex] = tmp; heapUp(parentIndex); } } } /** * Heap down the root element being least in value,until heap property is broken. * Steps: * 1.If current node has no children, done. * 2.If current node has one children and heap property is broken, * 3.Swap the current node and child node and heap down. * 4.If current node has one children and heap property is broken, find smaller one * 5.Swap the current node and child node and heap down. * */ private void heapDown(int nodeIndex){ int leftChildIndex, rightChildIndex, minIndex, tmp; leftChildIndex = getLeftChildIndex(nodeIndex); rightChildIndex = getRightChildIndex(nodeIndex); if (rightChildIndex >= size) { if (leftChildIndex >= size) return; else minIndex = leftChildIndex; } else { if (intArray[leftChildIndex] <= intArray[rightChildIndex]) minIndex = leftChildIndex; else minIndex = rightChildIndex; } if (intArray[nodeIndex] > intArray[minIndex]) { tmp = intArray[minIndex]; intArray[minIndex] = intArray[nodeIndex]; intArray[nodeIndex] = tmp; heapDown(minIndex); } } }
Demo Program
HeapDemo.java
package com.tutorialspoint.datastructure; pubpc class HeapDemo { pubpc static void main(String[] args){ Heap heap = new Heap(10); /* 5 //Level 0 * */ heap.insert(5); /* 1 //Level 0 * | * 5---| //Level 1 */ heap.insert(1); /* 1 //Level 0 * | * 5---|---3 //Level 1 */ heap.insert(3); /* 1 //Level 0 * | * 5---|---3 //Level 1 * | * 8--| //Level 2 */ heap.insert(8); /* 1 //Level 0 * | * 5---|---3 //Level 1 * | * 8--|--9 //Level 2 */ heap.insert(9); /* 1 //Level 0 * | * 5---|---3 //Level 1 * | | * 8--|--9 6--| //Level 2 */ heap.insert(6); /* 1 //Level 0 * | * 5---|---2 //Level 1 * | | * 8--|--9 6--|--3 //Level 2 */ heap.insert(2); System.out.println(heap.getMinimum()); heap.removeMin(); /* 2 //Level 0 * | * 5---|---3 //Level 1 * | | * 8--|--9 6--| //Level 2 */ System.out.println(heap.getMinimum()); } }
If we compile and run the above program then it would produce following result −
1 2
DSA using Java - Graph
Overview
Graph is a datastructure to model the mathematical graphs. It consists of a set of connected pairs called edges of vertices. We can represent a graph using an array of vertices and a two dimentional array of edges.
Important terms
Vertex − Each node of the graph is represented as a vertex. In example given below, labeled circle represents vertices. So A to G are vertices. We can represent them using an array as shown in image below. Here A can be identified by index 0. B can be identified using index 1 and so on.
Edge − Edge represents a path between two vertices or a pne between two vertices. In example given below, pnes from A to B, B to C and so on represents edges. We can use a two dimentional array to represent array as shown in image below. Here AB can be represented as 1 at row 0, column 1, BC as 1 at row 1, column 2 and so on, keeping other combinations as 0.
Adjacency − Two node or vertices are adjacent if they are connected to each other through an edge. In example given below, B is adjacent to A, C is adjacent to B and so on.
Path − Path represents a sequence of edges betweeen two vertices. In example given below, ABCD represents a path from A to D.
Basic Operations
Following are basic primary operations of a Graph which are following.
Add Vertex − add a vertex to a graph.
Add Edge − add an edge between two vertices of a graph.
Display Vertex − display a vertex of a graph.
Add Vertex Operation
//add vertex to the array of vertex pubpc void addVertex(char label){ lstVertices[vertexCount++] = new Vertex(label); }
Add Edge Operation
//add edge to edge array pubpc void addEdge(int start,int end){ adjMatrix[start][end] = 1; adjMatrix[end][start] = 1; }
Display Edge Operation
//display the vertex pubpc void displayVertex(int vertexIndex){ System.out.print(lstVertices[vertexIndex].label+" "); }
Traversal Algorithms
Following are important traversal algorithms on a Graph.
Depth First Search − traverses a graph in depthwards motion.
Breadth First Search − traverses a graph in breadthwards motion.
Depth First Search Algorithm
Depth First Search algorithm(DFS) traverses a graph in a depthward motion and uses a stack to remember to get the next vertex to start a search when a dead end occurs in any iteration.
As in example given above, DFS algorithm traverses from A to B to C to D first then to E, then to F and lastly to G. It employs following rules.
Rule 1 − Visit adjacent unvisited vertex. Mark it visited. Display it. Push it in a stack.
Rule 2 − If no adjacent vertex found, pop up a vertex from stack. (It will pop up all the vertices from the stack which do not have adjacent vertices.)
Rule 3 − Repeat Rule 1 and Rule 2 until stack is empty.
pubpc void depthFirstSearch(){ //mark first node as visited lstVertices[0].visited = true; //display the vertex displayVertex(0); //push vertex index in stack stack.push(0); while(!stack.isEmpty()){ //get the unvisited vertex of vertex which is at top of the stack int unvisitedVertex = getAdjUnvisitedVertex(stack.peek()); //no adjacent vertex found if(unvisitedVertex == -1){ stack.pop(); }else{ lstVertices[unvisitedVertex].visited = true; displayVertex(unvisitedVertex); stack.push(unvisitedVertex); } } //stack is empty, search is complete, reset the visited flag for(int i=0;i<vertexCount;i++){ lstVertices[i].visited = false; } }
Breadth First Search Algorithm
Breadth First Search algorithm(BFS) traverses a graph in a breadthwards motion and uses a queue to remember to get the next vertex to start a search when a dead end occurs in any iteration.
As in example given above, BFS algorithm traverses from A to B to E to F first then to C and G lastly to D. It employs following rules.
Rule 1 − Visit adjacent unvisited vertex. Mark it visited. Display it. Insert it in a queue.
Rule 2 − If no adjacent vertex found, remove the first vertex from queue.
Rule 3 − Repeat Rule 1 and Rule 2 until queue is empty.
pubpc void breadthFirstSearch(){ //mark first node as visited lstVertices[0].visited = true; //display the vertex displayVertex(0); //insert vertex index in queue queue.insert(0); int unvisitedVertex; while(!queue.isEmpty()){ //get the unvisited vertex of vertex which is at front of the queue int tempVertex = queue.remove(); //no adjacent vertex found while((unvisitedVertex=getAdjUnvisitedVertex(tempVertex)) != -1){ lstVertices[unvisitedVertex].visited = true; displayVertex(unvisitedVertex); queue.insert(unvisitedVertex); } } //queue is empty, search is complete, reset the visited flag for(int i=0;i<vertexCount;i++){ lstVertices[i].visited = false; } }
Graph Implementation
Stack.java
package com.tutorialspoint.datastructure; pubpc class Stack { private int size; // size of the stack private int[] intArray; // stack storage private int top; // top of the stack // Constructor pubpc Stack(int size){ this.size = size; intArray = new int[size]; //initiapze array top = -1; //stack is initially empty } // Operation : Push // push item on the top of the stack pubpc void push(int data) { if(!isFull()){ // increment top by 1 and insert data intArray[++top] = data; }else{ System.out.println("Cannot add data. Stack is full."); } } // Operation : Pop // pop item from the top of the stack pubpc int pop() { //retrieve data and decrement the top by 1 return intArray[top--]; } // Operation : Peek // view the data at top of the stack pubpc int peek() { //retrieve data from the top return intArray[top]; } // Operation : isFull // return true if stack is full pubpc boolean isFull(){ return (top == size-1); } // Operation : isEmpty // return true if stack is empty pubpc boolean isEmpty(){ return (top == -1); } }
Queue.java
package com.tutorialspoint.datastructure; pubpc class Queue { private final int MAX; private int[] intArray; private int front; private int rear; private int itemCount; pubpc Queue(int size){ MAX = size; intArray = new int[MAX]; front = 0; rear = -1; itemCount = 0; } pubpc void insert(int data){ if(!isFull()){ if(rear == MAX-1){ rear = -1; } intArray[++rear] = data; itemCount++; } } pubpc int remove(){ int data = intArray[front++]; if(front == MAX){ front = 0; } itemCount--; return data; } pubpc int peek(){ return intArray[front]; } pubpc boolean isEmpty(){ return itemCount == 0; } pubpc boolean isFull(){ return itemCount == MAX; } pubpc int size(){ return itemCount; } }
Vertex.java
package com.tutorialspoint.datastructure; pubpc class Vertex { pubpc char label; pubpc boolean visited; pubpc Vertex(char label){ this.label = label; visited = false; } }
Graph.java
package com.tutorialspoint.datastructure; pubpc class Graph { private final int MAX = 20; //array of vertices private Vertex lstVertices[]; //adjacency matrix private int adjMatrix[][]; //vertex count private int vertexCount; private Stack stack; private Queue queue; pubpc Graph(){ lstVertices = new Vertex[MAX]; adjMatrix = new int[MAX][MAX]; vertexCount = 0; stack = new Stack(MAX); queue = new Queue(MAX); for(int j=0; j<MAX; j++) // set adjacency for(int k=0; k<MAX; k++) // matrix to 0 adjMatrix[j][k] = 0; } //add vertex to the vertex pst pubpc void addVertex(char label){ lstVertices[vertexCount++] = new Vertex(label); } //add edge to edge array pubpc void addEdge(int start,int end){ adjMatrix[start][end] = 1; adjMatrix[end][start] = 1; } //display the vertex pubpc void displayVertex(int vertexIndex){ System.out.print(lstVertices[vertexIndex].label+" "); } //get the adjacent unvisited vertex pubpc int getAdjUnvisitedVertex(int vertexIndex){ for(int i=0; i<vertexCount; i++) if(adjMatrix[vertexIndex][i]==1 && lstVertices[i].visited==false) return i; return -1; } pubpc void depthFirstSearch(){ //mark first node as visited lstVertices[0].visited = true; //display the vertex displayVertex(0); //push vertex index in stack stack.push(0); while(!stack.isEmpty()){ //get the unvisited vertex of vertex which is at top of the stack int unvisitedVertex = getAdjUnvisitedVertex(stack.peek()); //no adjacent vertex found if(unvisitedVertex == -1){ stack.pop(); }else{ lstVertices[unvisitedVertex].visited = true; displayVertex(unvisitedVertex); stack.push(unvisitedVertex); } } //stack is empty, search is complete, reset the visited flag for(int i=0;i<vertexCount;i++){ lstVertices[i].visited = false; } } pubpc void breadthFirstSearch(){ //mark first node as visited lstVertices[0].visited = true; //display the vertex displayVertex(0); //insert vertex index in queue queue.insert(0); int unvisitedVertex; while(!queue.isEmpty()){ //get the unvisited vertex of vertex which is at front of the queue int tempVertex = queue.remove(); //no adjacent vertex found while((unvisitedVertex=getAdjUnvisitedVertex(tempVertex)) != -1){ lstVertices[unvisitedVertex].visited = true; displayVertex(unvisitedVertex); queue.insert(unvisitedVertex); } } //queue is empty, search is complete, reset the visited flag for(int i=0;i<vertexCount;i++){ lstVertices[i].visited = false; } } }
Demo Program
GraphDemo.java
package com.tutorialspoint.datastructure; pubpc class GraphDemo { pubpc static void main(String args[]){ Graph graph = new Graph(); graph.addVertex( A ); //0 graph.addVertex( B ); //1 graph.addVertex( C ); //2 graph.addVertex( D ); //3 graph.addVertex( E ); //4 graph.addVertex( F ); //5 graph.addVertex( G ); //6 /* 1 2 3 * 0 |--B--C--D * A--| * | * | 4 * |-----E * | 5 6 * | |--F--G * |--| */ graph.addEdge(0, 1); //AB graph.addEdge(1, 2); //BC graph.addEdge(2, 3); //CD graph.addEdge(0, 4); //AC graph.addEdge(0, 5); //AF graph.addEdge(5, 6); //FG System.out.print("Depth First Search: "); //A B C D E F G graph.depthFirstSearch(); System.out.println(""); System.out.print("Breadth First Search: "); //A B E F C G D graph.breadthFirstSearch(); } }
If we compile and run the above program then it would produce following result −
Depth First Search: A B C D E F G Breadth First Search: A B E F C G D
DSA using Java - Search techniques
Search refers to locating a desired element of specified properties in a collection of items. We are going to start our discussion using following commonly used and simple search algorithms.
Sr.No | Technique & Description |
---|---|
1 | Linear search searches all items and its worst execution time is n where n is the number of items. |
2 | Binary search requires items to be in sorted order but its worst execution time is constant and is much faster than pnear search. |
3 | Interpolation search requires items to be in sorted order but its worst execution time is O(n) where n is the number of items and it is much faster than pnear search. |
DSA using Java - Sorting techniques
Sorting refers to arranging data in a particular format. Sorting algorithm specifies the way to arrange data in a particular order. Most common orders are numerical or lexicographical order.
Importance of sorting pes in the fact that data searching can be optimized to a very high level if data is stored in a sorted manner. Sorting is also used to represent data in more readable formats. Some of the examples of sorting in real pfe scenarios are following.
Telephone Directory − Telephone directory keeps telephone no. of people sorted on their names. So that names can be searched.
Dictionary − Dictionary keeps words in alphabetical order so that searching of any work becomes easy.
Types of Sorting
Following is the pst of popular sorting algorithms and their comparison.
Sr.No | Technique & Description |
---|---|
1 | Bubble sort is simple to understand and implement algorithm but is very poor in performance. |
2 | Selection sort as name specifies use the technique to select the required item and prepare sorted array accordingly. |
3 | Insertion sort is a variation of selection sort. |
4 | Shell sort is an efficient version of insertion sort. |
5 | Quick sort is a highly efficient sorting algorithm and is based on partitioning of array of data into smaller arrays. |
6 | Java objects can be sorted easily using java.util.Arrays.sort() |
DSA using Java - Recursion
Overview
Recursion refers to a technique in a programming language where a function calls itself. The function which calls itself is called a recursive method.
Characteristics
A recursive function must posses the following two characteristics
Base Case(s)
Set of rules which leads to base case after reducing the cases.
Recursive Factorial
Factorial is one of the classical example of recursion. Factorial is a non-negative number satisfying following conditions.
0! = 1
1! = 1
n! = n * n-1!
Factorial is represented by "!". Here Rule 1 and Rule 2 are base cases and Rule 3 are factorial rules.
As an example, 3! = 3 x 2 x 1 = 6
private int factorial(int n){ //base case if(n == 0){ return 1; }else{ return n * factorial(n-1); } }
Recursive Fibonacci Series
Fibonacci Series is another classical example of recursion. Fibonacci series a series of integers satisfying following conditions.
F0 = 0
F1 = 1
Fn = Fn-1 + Fn-2
Fibonacci is represented by "F". Here Rule 1 and Rule 2 are base cases and Rule 3 are fibonnacci rules.
As an example, F5 = 0 1 1 2 3
Demo Program
RecursionDemo.java
package com.tutorialspoint.algorithm; pubpc class RecursionDemo { pubpc static void main(String[] args){ RecursionDemo recursionDemo = new RecursionDemo(); int n = 5; System.out.println("Factorial of " + n + ": " + recursionDemo.factorial(n)); System.out.print("Fibbonacci of " + n + ": "); for(int i=0;i<n;i++){ System.out.print(recursionDemo.fibbonacci(i) +" "); } } private int factorial(int n){ //base case if(n == 0){ return 1; }else{ return n * factorial(n-1); } } private int fibbonacci(int n){ if(n ==0){ return 0; } else if(n==1){ return 1; } else { return (fibbonacci(n-1) + fibbonacci(n-2)); } } }
If we compile and run the above program then it would produce following result −
Factorial of 5: 120 Fibbonacci of 5: 0 1 1 2 3Advertisements