Linked list

Introduction
What Is Linked List? (2002)
 linked list is one in which all nodes are linked together
 Each node contains two parts.
Data contains elements .
 Next/Link contains address of next node .

Structure of singly linked list
nextdata
A B C
nextnext datadata
head
 The head always points to the first node .
 All nodes are connected to each other through Link fields.
 Null pointer indicated end of the list.
X
Singly Linked List Contd..

Benefits of linked list over array
 Disadvantages of arrays :
Insertion and deletion operations are slow.
Slow searching in unordered array.
Wastage of memory.
Fixed size.
More expensive
 Linked lists solve some of these problems :
Insertions and deletions are simple and faster.
Linked List reduces the access time.
No wastage of memory.
Linked list is able to grow in size.
Less expensive

Linked List Types
 Single Linked list
 Double linked list
 Circular single linked list
 Circular double linked list

Operations on linked list
The basic operations on linked lists are :
1. Insertion
2. Deletion
3. Searching

1. Insertion
 Insertion operation is used to insert a new node in the linked list at the
specified position.
 When the list itself is empty , the new node is inserted as a first node.
 Types of Insertion
There are 3 ways to insert a new node into a list :
 Insertion at the beginning
 Insertion at the end
 Insertion after a particular node

Structure of Node of Single Linked List
/* Class Node */
class Node
{
int data;
Node next;
/* Constructor */
public Node()
{
next= null;
data = 0;
}

/* Function to insert an element at begining */
public void insert()
{
Node newNode = new Node();
if (head == null)
{
newNode.next = null;
head = newNode;
tail = newNode;
} else {
newNode.next = head;
head = newNode;
}
}
}
newnode
Data Next
Algorithm
Step 1: Create a newNode with given value.
Step 2: Check whether list is Empty (head == NULL)
Step 3: If it is Empty then, set newNode→next = NULL and
head = newNode.
Step 4: If it is Not Empty then, set newNode→next = head
and head = newNode.

/* Function to insert an element at end */
{
Node newNode = new Node();
if (head == null) {
head = newNode;
tail = newNode;
} else {
tail.next = newNode;
tail = newNode;
}
}
}

2.Deletion
 Deletion operation is used to delete a particular node in the linked list.
 we simply have to perform operation on the link of the nodes(which
contains the address of the next node) to delete a particular element.
 Types of Deletion
Deletion operation may be performed in the following conditions:
 Delete first element.
 Delete last element.
 Delete a particular element

/* Function to delete an element from first */
public void removeFirst() {
if (head == null)
return;
else {
if (head == tail) {
head = null;
tail = null;
} else {
head = head.next;
}
}
}
Step 1: Check whether list is Empty (head == NULL)
Step 2: If it is Empty then, display 'List is Empty!!! Deletion is
not possible' and terminate the function.
Step 3: If it is Not Empty then, define a Node pointer 'temp'
and initialize with head.
Step 4: Check whether list is having only one node (temp →
next == NULL)
Step 5: If it is TRUE then set head = NULL and delete temp
(Setting Empty list conditions)
Step 6: If it is FALSE then set head = temp → next, and delete
temp.

Deleting the last node of a singly linked list
public void removeLast()
{
if (tail == null)
return;
else {
if (head == tail) {
head = null;
tail = null;
}
else {
Node prev = head;
while (previ.next != tail)
{
prev = prev.next;
}
tail = prev;
tail.next = null;
}
}
}

3. Searching
– Searching involves finding the required element in the list
– We can use various techniques of searching like linear search
or binary search where binary search is more efficient in case
of Arrays
– But in case of linked list since random access is not available it
would become complex to do binary search in it
– We can perform simple linear search traversal

Circular linked list
A circular linked list is one which has
 No ending.
 The last node of a linked list is connected with the address of its first node .
 In the circular linked list we can insert elements anywhere in the list whereas in the array we
cannot insert element anywhere in the list because it is in the contiguous memory.

/* Function to insert element at begining In Circular linked list*/
public void insert(int val) {
Node newNode= new Node();
if(start == null)
{
newNode.next=newNode
head = newNode;
tail = newNode;
}
else {
head.next=head
last.next = newNode;
head = newNode; }
size++ ;
}
Circular linked list contd..

/* Function to insert element at end In Circular linked list*/
{
Node newNode= new Node();
if(start == null)
{
head=tail= newNode;
newNode.next=newNode;
}
else
{
last= newNode;
last.next=newNode
newnode.next=head;
}
}

/* Function to insert element at position in circular linked list */
public void insertAtPos(int val , int pos)
{
Node newNode= new Node(val,null);
Node ptr = start;
pos = pos - 1 ;
for (int i = 1; i < size - 1; i++)
{
if (i == pos)
{
Node tmp = ptr.getLink() ;
ptr.setLink( newNode);
newNode.setLink(tmp);
break;
}
ptr = ptr.getLink();
}
size++ ;
}

public void deletet()
{
if(size==0){
System.out.println("nList is Empty");
}else{
System.out.println("ndeleting node " + head.data + " from start");
head = head.next;
tail.next=head;
size--;
}
}
Deletion at beginning in the Circular linked list

Function to count the total number of nodes in a linear linked list.
int count(int search_for)
{
Node current = head;
int count = 0;
while (current != null)
{
if (current.data == search_for)
count++;
current = current.next;
}
return count;
}

Doubly Linked List
1. Doubly linked list is a linked data structure that consists of a set of
sequentially linked records called nodes.
2 . Each node contains three fields ::
-: one is data part which contain data only.
-:two other field is links part that are point or references to the
previous or to the next node in the sequence of nodes.

 The beginning and ending nodes' previous and next links respectively, point to
some kind of terminator ,typically a sentinel node or null to facilitate traversal of
the list.
Hence each node has knowledge of its successor and also its predecessor.
In doubly linked list, from every node the list can be traversed in both the directions.
Doubly Linked List (contd.)
Doubly Linked List contd..

DLL’s compared to SLL’s
 Advantages:
 Can be traversed in either direction
(may be essential for some programs)
 Some operations, such as deletion and
inserting before a node, become
easier
 Disadvantages:
 Requires more space
 List manipulations are slower
(because more links must be changed)
 Greater chance of having bugs
(because more links must be
manipulated)

Let’s see how the Node structure will look like
class Node
{
int data;
Node next, prev;
//constructs a new DoublyLinkedList object with head and tail as null
public Node()
{
next = null;
prev = null;
data = 0;
}

Insertion at the beginning of doubly linked list
public Node addAtStart(int data){
System.out.println("Adding Node " + data + " at the start");
Node newnode = new Node(data);
if(head=null)
{
head = newnode;
tail = newnode;
}
else
{
/*Make next of new node as head and previous as NULL */
newnode.next = head;
head.previous = newnode;
head = newnode;
}
size++;
return n;
}

Insertion at last of doubly linked list
public Node addAtEnd(int data)
{
System.out.println("Adding Node " + data + " at the End");
Node newNode= new Node(data);
if(head = =null{
head = newNode;
tail = newNode;
}else{
tail.next = newNode; /*Change the next of last/tail node */
newNode.previous = tail; /*Make last node as previous of new node */
tail =newNode;
}
size++;
return n;
}

Deletion at the beginning of doubly linked list
public void delete()
{
if(head==null)
{
System.out.println("nList is Empty");
}
Else if(head==tail)
{
head=tail=null;
}
else{
System.out.println("ndeleting node " + head.data + " from start");
head = head.next;
size--;
}
}

public void print()
{
Node temp = head;
System.out.print("Doubly Linked List: ");
while(temp!=null){
System.out.print(" " + temp.data);
temp = temp.next;
}
System.out.println();
}

Definition :-
– Many a times a complex problem becomes easier to solve if you have the
appropriate data structure at hand. More so when the input size involved is very
large.
– Skip Lists are an alternative representation of balanced trees that provides
approximate O(log n) access times with the advantage that the implementation is
straightforward and the storage requirement is less than a standard balanced tree
structure.
– A distinct difference from most search structures is that the behavior of
skip lists is probabilistic without dependence on the order of insertion of elements.

SELF ORGANIZING LIST
– A self-organizing list is a list that reorders its elements based on some self-organizing
heuristic to improve average access time.
– The aim of a self-organizing list is to improve efficiency of linear search by moving
more frequently accessed items towards the head of the list.
– The simplest implementation of self-organizing list is as a linked list.
– A self-organizing list achieves near constant time for element access in the best case.
– A self-organizing list uses a reorganizing algorithm to adapt to various query
distributions at runtime.

HISTORY
– The concept of self-organizing list was introduced by McCabe in 1965.
– In a pioneering work, he introduced two heuristics – the MTF rule and the
transposition rule
– Further improvements were made and algorithms suggested by Ronald
Rivest, nemes ,D Knuth and so on.
Self Organizing List Contd..

DIFFERENT TYPES OF TECHNIQUES TO
ORGANIZE LISTS
– MOVE TO FRONT(MTF)
– TRANSPOSE
– COUNT
– ORDERING

MOVE TO FRONT(MTF)
– This technique moves the element
which is accessed to the head of the list.
– This has the advantage of being easily
implemented and requiring no extra
memory.
– This heuristic also adapts quickly to
rapid changes in the query distribution.

B) TRANSPOSE
– This technique involves swapping an
accessed node with its predecessor.
– Therefore, if any node is accessed, it is
swapped with the node in front unless
it is the head node, thereby increasing
its priority.
– This algorithm is again easy to
implement and space efficient and is
more likely to keep frequently
accessed nodes at the front of the list.

C) COUNT
– In this technique, the number of times
each node was searched for is counted i.e.
every node keeps a separate counter
variable which is incremented every time it
is called.
– The nodes are then rearranged according
to decreasing count.
– Thus, the nodes of highest count i.e. most
frequently accessed are kept at the head of
the list.

ORDERING TECHNIQUE
– This technique orders a list with a particular criterion.
– For e.g in a list with nodes 2,3,7,10.
– If we want to access node 5, then the accessed node is
added between 3 and 7 to maintain the order of the
list i.e. increasing order.

DIFERENCE BETWEEN THESE
TECHNIQUES
– In the first three techniques i.e. move to front, transpose and count ,node is
added at the end whereas in the ordering technique , node is added
somewhere to maintain the order of the list.

In the first three techniques i.e. move to front, transpose and count ,node is added at the end whereas
in the ordering technique , node is added somewhere to maintain the order of the list.

APPLICATIONS
– Language translators like compilers and interpreters use self-organizing lists to
maintain symbol tables during compilation or interpretation of program source code.
– Currently research is underway to incorporate the self-organizing list data structure in
embedded systems to reduce bus transition activity which leads to power dissipation in
some circuits.
– These lists are also used in artificial intelligence and neural networks as well as self-
adjusting programs.
– The algorithms used in self-organizing lists are also used as caching algorithms as in
the case of LFU algorithm.

 Sparse table stores the information from one index ‘i’
to some index ‘j’ which is at a specific distance from ‘i’.
 Suppose our query is regarding minimum element in range
(L,R) or Range Minimum Query (RMQ) on a given array.
 Sparse Table uses dynamic programming to store the
index of minimum element in any range (i,j) .
 We can use Sparse table to store the minimum of the
elements between index ‘i’ to i+’2^j’.

0 1 2 3 4 5 6 7
3 1 5 3 4 7 6 1
Build a Sparse Table on array 3 1 5 3 4 7 6 1
0 1 2 3 4 5 6 7
3 1 5 3 4 7 6 1
1 1 3 3 4 6 1
1 1 3 3 1
1

Linked list

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