For each process is created and it is linked using link list
Basic concepts and nomenclatureEditEach record of a linked list is often called an 'element' or 'node'. Show
The field of each node that contains the address of the next node is usually called the 'next link' or 'next pointer'. The remaining fields are known as the 'data', 'information', 'value', 'cargo', or 'payload' fields. The 'head' of a list is its first node. The 'tail' of a list may refer either to the rest of the list after the head, or to the last node in the list. In Lisp and some derived languages, the next node may be called the 'cdr' (pronounced could-er) of the list, while the payload of the head node may be called the 'car'. Singly linked listEditSingly linked lists contain nodes which have a data field as well as 'next' field, which points to the next node in line of nodes. Operations that can be performed on singly linked lists include insertion, deletion and traversal. A singly linked list whose nodes contain two fields: an integer value and a link to the next node The following code demonstrates how to add a new node with data "value" to the end of a singly linked list: node addNode(node head, int value) {
node temp, p; // declare two nodes temp and p
temp = createNode(); // assume createNode creates a new node with data = 0 and next pointing to NULL.
temp->data = value; // add element's value to data part of node
if (head == NULL) {
head = temp; // when linked list is empty
}
else {
p = head; // assign head to p
while (p->next != NULL) {
p = p->next; // traverse the list until p is the last node. The last node always points to NULL.
}
p->next = temp; // Point the previous last node to the new node created.
}
return head;
}
Doubly linked listEditIn a 'doubly linked list', each node contains, besides the next-node link, a second link field pointing to the 'previous' node in the sequence. The two links may be called 'forward('s') and 'backwards', or 'next' and 'prev'('previous'). A doubly linked list whose nodes contain three fields: an integer value, the link forward to the next node, and the link backward to the previous node A technique known as XOR-linking allows a doubly linked list to be implemented using a single link field in each node. However, this technique requires the ability to do bit operations on addresses, and therefore may not be available in some high-level languages. Many modern operating systems use doubly linked lists to maintain references to active processes, threads, and other dynamic objects.[2] A common strategy for rootkits to evade detection is to unlink themselves from these lists.[3] Multiply linked listEditIn a 'multiply linked list', each node contains two or more link fields, each field being used to connect the same set of data records in a different order of same set (e.g., by name, by department, by date of birth, etc.). While doubly linked lists can be seen as special cases of multiply linked list, the fact that the two and more orders are opposite to each other leads to simpler and more efficient algorithms, so they are usually treated as a separate case. Circular linked listEditIn the last node of a list, the link field often contains a null reference, a special value is used to indicate the lack of further nodes. A less common convention is to make it point to the first node of the list; in that case, the list is said to be 'circular' or 'circularly linked'; otherwise, it is said to be 'open' or 'linear'. It is a list where the last pointer points to the first node. In the case of a circular doubly linked list, the first node also points to the last node of the list. Sentinel nodesEditIn some implementations an extra 'sentinel' or 'dummy' node may be added before the first data record or after the last one. This convention simplifies and accelerates some list-handling algorithms, by ensuring that all links can be safely dereferenced and that every list (even one that contains no data elements) always has a "first" and "last" node. Empty listsEditAn empty list is a list that contains no data records. This is usually the same as saying that it has zero nodes. If sentinel nodes are being used, the list is usually said to be empty when it has only sentinel nodes. Hash linkingEditThe link fields need not be physically part of the nodes. If the data records are stored in an array and referenced by their indices, the link field may be stored in a separate array with the same indices as the data records. List handlesEditSince a reference to the first node gives access to the whole list, that reference is often called the 'address', 'pointer', or 'handle' of the list. Algorithms that manipulate linked lists usually get such handles to the input lists and return the handles to the resulting lists. In fact, in the context of such algorithms, the word "list" often means "list handle". In some situations, however, it may be convenient to refer to a list by a handle that consists of two links, pointing to its first and last nodes. Combining alternativesEditThe alternatives listed above may be arbitrarily combined in almost every way, so one may have circular doubly linked lists without sentinels, circular singly linked lists with sentinels, etc. TradeoffsEditAs with most choices in computer programming and design, no method is well suited to all circumstances. A linked list data structure might work well in one case, but cause problems in another. This is a list of some of the common tradeoffs involving linked list structures. Linked lists vs. dynamic arraysEditA dynamic array is a data structure that allocates all elements contiguously in memory, and keeps a count of the current number of elements. If the space reserved for the dynamic array is exceeded, it is reallocated and (possibly) copied, which is an expensive operation. Linked lists have several advantages over dynamic arrays. Insertion or deletion of an element at a specific point of a list, assuming that we have indexed a pointer to the node (before the one to be removed, or before the insertion point) already, is a constant-time operation (otherwise without this reference it is O(n)), whereas insertion in a dynamic array at random locations will require moving half of the elements on average, and all the elements in the worst case. While one can "delete" an element from an array in constant time by somehow marking its slot as "vacant", this causes fragmentation that impedes the performance of iteration. Moreover, arbitrarily many elements may be inserted into a linked list, limited only by the total memory available; while a dynamic array will eventually fill up its underlying array data structure and will have to reallocate—an expensive operation, one that may not even be possible if memory is fragmented, although the cost of reallocation can be averaged over insertions, and the cost of an insertion due to reallocation would still be amortized O(1). This helps with appending elements at the array's end, but inserting into (or removing from) middle positions still carries prohibitive costs due to data moving to maintain contiguity. An array from which many elements are removed may also have to be resized in order to avoid wasting too much space. On the other hand, dynamic arrays (as well as fixed-size array data structures) allow constant-time random access, while linked lists allow only sequential access to elements. Singly linked lists, in fact, can be easily traversed in only one direction. This makes linked lists unsuitable for applications where it's useful to look up an element by its index quickly, such as heapsort. Sequential access on arrays and dynamic arrays is also faster than on linked lists on many machines, because they have optimal locality of reference and thus make good use of data caching. Another disadvantage of linked lists is the extra storage needed for references, which often makes them impractical for lists of small data items such as characters or boolean values, because the storage overhead for the links may exceed by a factor of two or more the size of the data. In contrast, a dynamic array requires only the space for the data itself (and a very small amount of control data).[note 1] It can also be slow, and with a naïve allocator, wasteful, to allocate memory separately for each new element, a problem generally solved using memory pools. Some hybrid solutions try to combine the advantages of the two representations. Unrolled linked lists store several elements in each list node, increasing cache performance while decreasing memory overhead for references. CDR coding does both these as well, by replacing references with the actual data referenced, which extends off the end of the referencing record. A good example that highlights the pros and cons of using dynamic arrays vs. linked lists is by implementing a program that resolves the Josephus problem. The Josephus problem is an election method that works by having a group of people stand in a circle. Starting at a predetermined person, one may count around the circle n times. Once the nth person is reached, one should remove them from the circle and have the members close the circle. The process is repeated until only one person is left. That person wins the election. This shows the strengths and weaknesses of a linked list vs. a dynamic array, because if the people are viewed as connected nodes in a circular linked list, then it shows how easily the linked list is able to delete nodes (as it only has to rearrange the links to the different nodes). However, the linked list will be poor at finding the next person to remove and will need to search through the list until it finds that person. A dynamic array, on the other hand, will be poor at deleting nodes (or elements) as it cannot remove one node without individually shifting all the elements up the list by one. However, it is exceptionally easy to find the nth person in the circle by directly referencing them by their position in the array. The list ranking problem concerns the efficient conversion of a linked list representation into an array. Although trivial for a conventional computer, solving this problem by a parallel algorithm is complicated and has been the subject of much research. A balanced tree has similar memory access patterns and space overhead to a linked list while permitting much more efficient indexing, taking O(log n) time instead of O(n) for a random access. However, insertion and deletion operations are more expensive due to the overhead of tree manipulations to maintain balance. Schemes exist for trees to automatically maintain themselves in a balanced state: AVL trees or red–black trees. Singly linked linear lists vs. other listsEditWhile doubly linked and circular lists have advantages over singly linked linear lists, linear lists offer some advantages that make them preferable in some situations. A singly linked linear list is a recursive data structure, because it contains a pointer to a smaller object of the same type. For that reason, many operations on singly linked linear lists (such as merging two lists, or enumerating the elements in reverse order) often have very simple recursive algorithms, much simpler than any solution using iterative commands. While those recursive solutions can be adapted for doubly linked and circularly linked lists, the procedures generally need extra arguments and more complicated base cases. Linear singly linked lists also allow tail-sharing, the use of a common final portion of sub-list as the terminal portion of two different lists. In particular, if a new node is added at the beginning of a list, the former list remains available as the tail of the new one—a simple example of a persistent data structure. Again, this is not true with the other variants: a node may never belong to two different circular or doubly linked lists. In particular, end-sentinel nodes can be shared among singly linked non-circular lists. The same end-sentinel node may be used for every such list. In Lisp, for example, every proper list ends with a link to a special node, denoted by nil or (), whose CAR and CDR links point to itself. Thus a Lisp procedure can safely take the CAR or CDR of any list. The advantages of the fancy variants are often limited to the complexity of the algorithms, not in their efficiency. A circular list, in particular, can usually be emulated by a linear list together with two variables that point to the first and last nodes, at no extra cost. Doubly linked vs. singly linkedEditDouble-linked lists require more space per node (unless one uses XOR-linking), and their elementary operations are more expensive; but they are often easier to manipulate because they allow fast and easy sequential access to the list in both directions. In a doubly linked list, one can insert or delete a node in a constant number of operations given only that node's address. To do the same in a singly linked list, one must have the address of the pointer to that node, which is either the handle for the whole list (in case of the first node) or the link field in the previous node. Some algorithms require access in both directions. On the other hand, doubly linked lists do not allow tail-sharing and cannot be used as persistent data structures. Circularly linked vs. linearly linkedEditA circularly linked list may be a natural option to represent arrays that are naturally circular, e.g. the corners of a polygon, a pool of buffers that are used and released in FIFO ("first in, first out") order, or a set of processes that should be time-shared in round-robin order. In these applications, a pointer to any node serves as a handle to the whole list. With a circular list, a pointer to the last node gives easy access also to the first node, by following one link. Thus, in applications that require access to both ends of the list (e.g., in the implementation of a queue), a circular structure allows one to handle the structure by a single pointer, instead of two. A circular list can be split into two circular lists, in constant time, by giving the addresses of the last node of each piece. The operation consists in swapping the contents of the link fields of those two nodes. Applying the same operation to any two nodes in two distinct lists joins the two list into one. This property greatly simplifies some algorithms and data structures, such as the quad-edge and face-edge. The simplest representation for an empty circular list (when such a thing makes sense) is a null pointer, indicating that the list has no nodes. Without this choice, many algorithms have to test for this special case, and handle it separately. By contrast, the use of null to denote an empty linear list is more natural and often creates fewer special cases. For some applications, it can be useful to use singly linked lists that can vary between being circular and being linear, or even circular with a linear initial segment. Algorithms for searching or otherwise operating on these have to take precautions to avoid accidentally entering an endless loop. One usual method is to have a second pointer walking the list at half or double the speed, and if both pointers meet at the same node, you know you found a cycle. Using sentinel nodesEditSentinel node may simplify certain list operations, by ensuring that the next or previous nodes exist for every element, and that even empty lists have at least one node. One may also use a sentinel node at the end of the list, with an appropriate data field, to eliminate some end-of-list tests. For example, when scanning the list looking for a node with a given value x, setting the sentinel's data field to x makes it unnecessary to test for end-of-list inside the loop. Another example is the merging two sorted lists: if their sentinels have data fields set to +∞, the choice of the next output node does not need special handling for empty lists. However, sentinel nodes use up extra space (especially in applications that use many short lists), and they may complicate other operations (such as the creation of a new empty list). However, if the circular list is used merely to simulate a linear list, one may avoid some of this complexity by adding a single sentinel node to every list, between the last and the first data nodes. With this convention, an empty list consists of the sentinel node alone, pointing to itself via the next-node link. The list handle should then be a pointer to the last data node, before the sentinel, if the list is not empty; or to the sentinel itself, if the list is empty. The same trick can be used to simplify the handling of a doubly linked linear list, by turning it into a circular doubly linked list with a single sentinel node. However, in this case, the handle should be a single pointer to the dummy node itself.[8] Types of Linked List and Operation on Linked ListIn the previous blog, we have seen the structure and properties of a Linked List. In this blog, we will discuss the types of a linked list and basic operations that can be performed on a linked list. Types of Linked ListFollowing are the types of linked list
Singly Linked ListA Singly-linked list is a collection of nodes linked together in a sequential way where each node of the singly linked list contains a data field and an address field that contains the reference of the next node. The structure of the node in the Singly Linked List is The nodes are connected to each other in this form where the value of the next variable of the last node is NULL i.e. next = NULL, which indicates the end of the linked list. Doubly Linked ListA Doubly Linked List contains an extra memory to store the address of the previous node, together with the address of the next node and data which are there in the singly linked list. So, here we are storing the address of the next as well as the previous nodes. The following is the structure of the node in the Doubly Linked List(DLL): The nodes are connected to each other in this form where the first node has prev = NULL and the last node has next = NULL. Advantages over Singly Linked List-
Disadvantages over Singly Linked List-
Circular Linked ListA circular linked list is either a singly or doubly linked list in which there are no NULL values. Here, we can implement the Circular Linked List by making the use of Singly or Doubly Linked List. In the case of a singly linked list, the next of the last node contains the address of the first node and in case of a doubly-linked list, the next of last node contains the address of the first node and prev of the first node contains the address of the last node. Advantages of a Circular linked list
Disadvantages of Circular linked list
Basic Operations on Linked List
We will see the various implementation of these operations on a singly linked list. Following is the structure of the node in a linked list: class Node{ int data // variable containing the data of the node Node next // variable containing the address of next node }Linked List TraversalThe idea here is to step through the list from beginning to end. For example, we may want to print the list or search for a specific node in the list. The algorithm for traversing a list
Linked List node InsertionThere can be three cases that will occur when we are inserting a node in a linked list.
Insertion at the beginning Since there is no need to find the end of the list. If the list is empty, we make the new node as the head of the list. Otherwise, we we have to connect the new node to the current head of the list and make the new node, the head of the list. Insertion at end We will traverse the list until we find the last node. Then we insert the new node to the end of the list. Note that we have to consider special cases such as list being empty. In case of a list being empty, we will return the updated head of the linked list because in this case, the inserted node is the first as well as the last node of the linked list. Insertion after a given node We are given the reference to a node, and the new node is inserted after the given node. NOTE: If the address of the prevNode is not given, then you can traverse to that node by finding the data value. Linked List node DeletionTo delete a node from a linked list, we need to do these steps
In the deletion, there is a special case in which the first node is deleted. In this, we need to update the head of the linked list. Linked List node SearchingTo search any value in the linked list, we can traverse the linked list and compares the value present in the node. bool searchLL(Node head, int val) { Node temp = head // creating a temp variable pointing to the head of the linked list while( temp != NULL) // traversing the list { if( temp.data == val ) return true temp = temp.next } return false }Linked List node UpdationTo update the value of the node, we just need to set the data part to the new value. Below is the implementation in which we had to update the value of the first node in which data is equal to val and we have to set it to newVal. void updateLL(Node head, int val, int newVal) { Node temp = head while(temp != NULL) { if( temp.data == val) { temp.data = newVal return } temp = temp.next } }Suggested Problems to solve in Linked List
Happy coding! Enjoy Algorithms. Linked List | Set 1 (Introduction)Like arrays, Linked List is a linear data structure. Unlike arrays, linked list elements are not stored at a contiguous location; the elements are linked using pointers. Why Linked List? C
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First Simple Linked List in C Let us create a simple linked list with 3 nodes. C++
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Linked List Traversal Applications of linked list data structureA linked list is a linear data structure, in which the elements are not stored at contiguous memory locations. The elements in a linked list are linked using pointers as shown in the below image: Applications of linked list in computer science –
Applications of linked list in real world-
Applications of Circular Linked Lists:
An example problem: Design a data structure that supports following operations efficiently.
Doubly linked list is the best solution here. We maintain head and tail pointers, since inserted item is always greatest, we insert at tail. Deleting an item from head or tail can be done in O(1) time. So all operations take O(1) time. Recent Articles on Linked List
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Linked List In C++We will take a look at the singly linked list in detail in this tutorial. The following diagram shows the structure of a singly linked list. As shown above, the first node of the linked list is called “head” while the last node is called “Tail”. As we see, the last node of the linked list will have its next pointer as null since it will not have any memory address pointed to. Since each node has a pointer to the next node, data items in the linked list need not be stored at contiguous locations. The nodes can be scattered in the memory. We can access the nodes anytime as each node will have an address of the next node. We can add data items to the linked list as well as delete items from the list easily. Thus it is possible to grow or shrink the linked list dynamically. There is no upper limit on how many data items can be there in the linked list. So as long as memory is available, we can have as many data items added to the linked list. Apart from easy insertion and deletion, the linked list also doesn’t waste memory space as we need not specify beforehand how many items we need in the linked list. The only space taken by linked list is for storing the pointer to the next node that adds a little overhead. Next, we will discuss the various operations that can be performed on a linked list. OperationsJust like the other data structures, we can perform various operations for the linked list as well. But unlike arrays, in which we can access the element using subscript directly even if it is somewhere in between, we cannot do the same random access with a linked list. In order to access any node, we need to traverse the linked list from the start and only then we can access the desired node. Hence accessing the data randomly from the linked list proves to be expensive. We can perform various operations on a linked list as given below: #1) InsertionInsertion operation of linked list adds an item to the linked list. Though it may sound simple, given the structure of the linked list, we know that whenever a data item is added to the linked list, we need to change the next pointers of the previous and next nodes of the new item that we have inserted. The second thing that we have to consider is the place where the new data item is to be added. There are three positions in the linked list where a data item can be added. #1) At the beginning of the linked list A linked list is shown below 2->4->6->8->10. If we want to add a new node 1, as the first node of the list, then the head pointing to node 2 will now point to 1 and the next pointer of node 1 will have a memory address of node 2 as shown in the below figure. Thus the new linked list becomes 1->2->4->6->8->10. #2) After the given Node Here, a node is given and we have to add a new node after the given node. In the below-linked list a->b->c->d ->e, if we want to add a node f after node c then the linked list will look as follows: Thus in the above diagram, we check if the given node is present. If it’s present, we create a new node f. Then we point the next pointer of node c to point to the new node f. The next pointer of the node f now points to node d. #3) At the end of the Linked List In the third case, we add a new node at the end of the linked list. Consider we have the same linked list a->b->c->d->e and we need to add a node f to the end of the list. The linked list will look as shown below after adding the node. Thus we create a new node f. Then the tail pointer pointing to null is pointed to f and the next pointer of node f is pointed to null. We have implemented all three types of insert functions in the below C++ program. In C++, we can declare a linked list as a structure or as a class. Declaring linked list as a structure is a traditional C-style declaration. A linked list as a class is used in modern C++, mostly while using standard template library. In the following program, we have used structure to declare and create a linked list. It will have data and pointer to the next element as its members. #includeFinallinkedlist: 30–>20–>50–>10–>40–>null Next, we implement the linked list insert operation in Java. In Java language, the linked list is implemented as a class. The program below is similar in logic to the C++ program, the only difference is that we use a class for the linked list. class LinkedList { Node head; // head of list //linked list node declaration class Node { int data; Node next; Node(int d) {data = d; next = null; } } /* Insert a new node at the front of the list */public void push(int new_data) { //allocate and assign data to the node Node newNode = new Node(new_data); //new node becomes head of linked list newNode.next = head; //head points to new node head = newNode; } // Given a node,prev_node insert node after prev_node public void insertAfter(Node prev_node, int new_data) { //check if prev_node is null. if (prev_node == null) { System.out.println("The given node is required and cannot be null"); return; } //allocate node and assign data to it Node newNode = new Node(new_data); //next of new Node is next of prev_node newNode.next = prev_node.next; //prev_node->next is the new node. prev_node.next = newNode; } //inserts a new node at the end of the list public void append(intnew_data) { //allocate the node and assign data Node newNode = new Node(new_data); //if linked list is empty, then new node will be the head if (head == null) { head = new Node(new_data); return; } //set next of new node to null as this is the last node newNode.next = null; // if not the head node traverse the list and add it to the last Node last = head; while (last.next != null) last = last.next; //next of last becomes new node last.next = newNode; return; } //display contents of linked list public void displayList() { Node pnode = head; while (pnode != null) { System.out.print(pnode.data+"-->"); pnode = pnode.next; } if(pnode == null) System.out.print("null"); } } //Main class to call linked list class functions and construct a linked list class Main{ public static void main(String[] args) { /* create an empty list */ LinkedList lList = new LinkedList(); // Insert 40. lList.append(40); // Insert 20 at the beginning. lList.push(20); // Insert 10 at the beginning. lList.push(10); // Insert 50 at the end. lList.append(50); // Insert 30, after 20. lList.insertAfter(lList.head.next, 30); System.out.println("\nFinal linked list: "); lList. displayList (); } }Output: Finallinkedlist: 10–>20–>30–>40–>50–>null In both the program above, C++ as well as Java, we have separate functions to add a node in front of the list, end of the list and between the lists given in a node. In the end, we print the contents of the list created using all the three methods. #2) DeletionLike insertion, deleting a node from a linked list also involves various positions from where the node can be deleted. We can delete the first node, last node or a random kth node from the linked list. After deletion, we need to adjust the next pointer and the other pointers in the linked list appropriately so as to keep the linked list intact. In the following C++ implementation, we have given two methods of deletion i.e. deleting the first node in the list and deleting the last node in the list. We first create a list by adding nodes to the head. Then we display the contents of the list after insertion and each deletion. #includeOutput: Linkedlistcreated 10–>8–>6–>4–>2– Linkedlistafterdeletingheadnode 8–>6–>4–>2– Linkedlistafterdeletinglastnode 8–>6–>4–>NULL Next is the Java implementation for deleting nodes from the linked list. The implementation logic is the same as used in the C++ program. The only difference is that the linked list is declared as a class. class Main { // Linked list node / static class Node { int data; Node next; }; // delete first node of linked list static Node deleteFirstNode(Node head) { if (head == null) return null; // Move the head pointer to the next node Node temp = head; head = head.next; return head; } // Delete the last node in linked list static Node deleteLastNode(Node head) { if (head == null) return null; if (head.next == null) { return null; } // search for second last node Node second_last = head; while (second_last.next.next != null) second_last = second_last.next; // set next of second last to null second_last.next = null; return head; } // Add nodes to the head and create linked list static Node push(Node head, int new_data) { Node newNode = new Node(); newNode.data = new_data; newNode.next = (head); (head) = newNode; return head; } //main function public static void main(String args[]) { // Start with the empty list / Node head = null; //create linked list head = push(head, 1); head = push(head, 3); head = push(head, 5); head = push(head, 7); head = push(head, 9); Node temp; System.out.println("Linked list created :"); for (temp = head; temp != null; temp = temp.next) System.out.print(temp.data + "-->"); if(temp == null) System.out.println("null"); head = deleteFirstNode(head); System.out.println("Linked list after deleting head node :"); for (temp = head; temp != null; temp = temp.next) System.out.print(temp.data + "-->"); if(temp == null) System.out.println("null"); head = deleteLastNode(head); System.out.println("Linked list after deleting last node :"); for (temp = head; temp != null; temp = temp.next) System.out.print(temp.data + "-->"); if(temp == null) System.out.println("null"); } }Output: Linkedlistcreated: 9–>7–>5–>3–>1– Linkedlistafterdeletingheadnode: 7–>5–>3–>1– Linkedlistafterdeletinglastnode: 7–>5–>3–>null Count The Number Of NodesThe operation to count the number of nodes can be performed while traversing the linked list. We have already seen in the implementation above that whenever we need to insert/delete a node or display contents of the linked list, we need to traverse the linked list from start. Keeping a counter and incrementing it as we traverse each node will give us the count of the number of nodes present in the linked list. We will leave this program for the readers to implement. Arrays And Linked ListsHaving seen the operations and implementation of the linked list, let us compare how arrays and linked list fair in comparison with each other.
ApplicationsAs arrays and linked lists are both used to store items and are linear data structures, both these structures can be used in similar ways for most of the applications. Some of the applications for linked lists are as follows:
ConclusionLinked lists are the data structures that are used to store data items in a linear fashion but noncontiguous locations. A linked list is a collection of nodes that contain a data part and a next pointer that contains the memory address of the next element in the list. The last element in the list has its next pointer set to NULL, thereby indicating the end of the list. The first element of the list is called the Head. The linked list supports various operations like insertion, deletion, traversal, etc. In case of dynamic memory allocation, linked lists are preferred over arrays. Linked lists are expensive as far as their traversal is concerned since we cannot randomly access the elements like arrays. However, insertion-deletion operations are less expensive when compared arrays. We have learned all about linear linked lists in this tutorial. Linked lists can also be circular or doubly. We will have an in-depth look at these lists in our upcoming tutorials. => Check Here For Complete C++ Training Series. Recommended Reading
Data Structure and Algorithms - Linked ListAdvertisements Previous Page Next Page A linked list is a sequence of data structures, which are connected together via links. Linked List is a sequence of links which contains items. Each link contains a connection to another link. Linked list is the second most-used data structure after array. Following are the important terms to understand the concept of Linked List.
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