Linked lists are linear data structures where each node contains a data field and a pointer to the next node. There are two types: singly linked lists where each node has a single next pointer, and doubly linked lists where each node has next and previous pointers. Common operations on linked lists include insertion and deletion which have O(1) time complexity for singly linked lists but require changing multiple pointers for doubly linked lists. Linked lists are useful when the number of elements is dynamic as they allow efficient insertions and deletions without shifting elements unlike arrays.
This document discusses linked lists and their implementation. It begins by defining a list as a sequence of zero or more elements of a given type that can be linearly ordered. Linked lists are introduced as a flexible data structure that uses nodes connected by pointers to dynamically allocate elements in memory. The key operations on linked lists are described, including appending, traversing, inserting, deleting nodes. Code examples are provided to implement these operations using a ListNode struct containing a data element and pointer to the next node. Functions like appendNode and displayList are demonstrated, with appendNode adding to the end of the list and displayList traversing the list to output each element.
Array implementation and linked list as datat structureTushar Aneyrao
The document discusses arrays and linked lists. It defines arrays as collections of elements of the same data type stored in contiguous memory. Linked lists store elements in memory locations that are not contiguous. Each element of a linked list contains a data field and a pointer to the next node. This allows for efficient insertion and deletion of nodes compared to arrays. The document provides examples of implementing common linked list operations like insertion at the head, tail, and deletion.
This document discusses different types of linked lists including singly linked lists, circular linked lists, and doubly linked lists. It provides details on representing stacks and queues using linked lists. Key advantages of linked lists over arrays are that linked lists can dynamically grow in size as needed, elements can be inserted and deleted without shifting other elements, and there is no memory wastage. Operations like insertion, deletion, traversal, and searching are described for singly linked lists along with sample C code to implement a linked list, stack, and queue.
Linked List Static and Dynamic Memory AllocationProf Ansari
Static variables are declared and named while writing the program. (Space for them exists as long as the program, in which they are declared, is running.) Static variables cannot be created or destroyed during execution of the program in which they are declared.
Dynamic variables are created (and may be destroyed) during program execution since dynamic variables do not exist while the program is compiled, but only when it is run, they cannot be assigned names while it is being written. The only way to access dynamic variables is by using pointers. Once it is created, however, a dynamic variable does contain data and must have a type like any other variable. If a dynamic variable is created in a function, then it can continue to exist even after the function terminates.
Linked Linear List
We saw in previous chapters how static representation of linear ordered list through Array leads to wastage of memory and in some cases overflows. Now we don't want to assign memory to any linear list in advance instead we want to allocate memory to elements as they are inserted in list. This requires Dynamic Allocation of memory and it can be achieved by using malloc() or calloc() function.
But memory assigned to elements will not be contiguous, which is a requirement for linear ordered list, and was provided by array representation. How we could achieve this?
A linked list is a data structure made up of nodes that are connected to each other via pointers. Each node contains a data field as well as a pointer to the next node. Linked lists allow dynamic sizes and efficient insertion/deletion of nodes. Common linked list operations include appending nodes to the end, inserting nodes in a sorted order, traversing the list to display nodes, and deleting nodes. The code sample shows a template for a linked list class with functions to implement these operations by traversing the list and manipulating the node pointers accordingly.
A linked list is a linear data structure consisting of nodes that are connected to each other through pointers. Each node contains a data field and a pointer to the next node. Linked lists allow for efficient insertion and removal of nodes and are more flexible than arrays in terms of memory allocation. Common types of linked lists include singly linked lists, doubly linked lists, circular linked lists, and header linked lists.
The document defines and describes stacks, queues, and linked lists. It defines a stack as a LIFO data structure that allows push and pop operations. A queue is defined as a FIFO data structure that allows enqueue and dequeue operations. Linked lists are collections of nodes that contain data and a pointer to the next node. The document discusses implementations of stacks, queues, and linked lists using arrays and linked nodes. It also covers priority queues, deques, and circular linked lists.
This document discusses doubly linked lists. A doubly linked list is a list where each node contains a pointer to the next node and previous node. This allows traversal in both directions. The document explains how to implement a doubly linked list using a struct with next and previous pointers. It covers insertion, deletion, searching, and printing nodes in a doubly linked list by traversing forwards and backwards. Key operations like adding a node to the beginning, middle or end of the list are demonstrated along with deleting nodes and freeing memory.
A stack is a linear data structure that follows the LIFO (last in, first out) principle. Elements are inserted and removed from the top of the stack. Common stack operations include push to add an element and pop to remove the top element. Stacks can be implemented using arrays or linked lists. Stacks are useful for operations like converting infix expressions to postfix and evaluating postfix expressions using a stack to hold operands. Queues follow the FIFO (first in, first out) principle with elements added to the rear and removed from the front. Common queue operations are enqueue to add and dequeue to remove elements. Queues can also be implemented using arrays or linked lists. Linked lists store elements in nodes with each node
The document discusses linked lists, including their definition as a dynamic linear data structure composed of connected nodes where each node contains a data element and a pointer, common operations on linked lists such as traversal, insertion, and deletion, and variations like single vs. double linked lists and circular lists. Algorithms for searching, inserting, and deleting nodes from a singly linked list are presented along with advantages of linked lists over arrays for dynamic data structures.
The document discusses linked lists and their implementation in C. It defines linked lists as dynamic data structures that store data in nodes linked together via pointers. The key operations on linked lists include insertion and deletion of nodes, as well as traversing and searching the list. It describes implementing linked lists as singly linked lists, doubly linked lists, and circular linked lists. Functions are provided for basic linked list operations like insertion, deletion, display on singly linked lists, and implementations of stacks and queues using linked lists.
This document contains a presentation on linked lists. It includes:
1. An introduction to linked lists describing their representation using linked allocation and algorithms for inserting and deleting nodes.
2. Algorithms for inserting a node at the first, last, and ordered positions in a single linked list, as well as deleting a node and copying a linked list.
3. A section on linear linked list multiple choice questions.
Data Structure Introduction
Data Structure Definition
Data Structure Types
Data Structure Characteristics
Need for Data Structure
Stack Definition
Stack Representation
Stack Operations
Stack Algorithm
Program for Stack in C++
Linked List Definition
Linked List Representation
Linked List Operations
Linked List Algorithm
Program for Linked List in C++
Linked List Defination
Linked List Representation
Linked List Operations
Linked List Algorithm
Program for Linked List in C++
This document discusses linked lists and polynomials represented as linked lists. It provides details on singly linked lists, including how to implement insertion and deletion of nodes. It also describes how to represent stacks and queues as dynamically linked lists. Finally, it discusses representing polynomials using arrays or linked lists, and how to perform addition and multiplication of polynomials in each representation.
The document discusses double and circular linked lists. It covers inserting and deleting nodes from doubly linked lists and circular linked lists. Specifically, it describes how to insert nodes at different positions in a doubly linked list, such as at the front, after a given node, at the end, and before a given node. It also explains how to delete nodes from a doubly linked list. For circular linked lists, it outlines how to insert nodes in an empty list, at the beginning, at the end, and between nodes. It also provides the steps to delete nodes from a circular linked list.
The document discusses sorting algorithms, abstract data types (ADTs), and linked lists. It describes selection sort and insertion sort algorithms for sorting arrays. It then explains that linked lists are a more flexible data structure than arrays and defines a singly linked list as an ADT with nodes that point to the next node in the list. Functions for typical linked list operations like insertion, deletion, checking if empty, and printing the list are discussed.
The document discusses linked lists and their advantages over arrays. It defines a linked list as a linear data structure composed of nodes, where each node contains data and a pointer to the next node. The key points are:
- Linked lists have dynamic sizes while arrays are fixed. Inserting and deleting from linked lists is more efficient as it doesn't require shifting elements.
- Linked lists don't allow random access so operations like sorting are less efficient, while arrays don't waste space if fully filled.
- The document then describes the basic operations on a singly linked list like creation, insertion, deletion and searching and provides algorithms to implement these operations.
The document discusses list data structures and their implementation using arrays and linked memory. It describes common list operations like insertion, removal, searching, and provides examples of how to implement them with arrays and linked lists. Key list operations include adding and removing elements from different positions, accessing elements by index or pointer, and traversing the list forward and backward. Linked lists offer more flexibility than arrays by not requiring predefined memory allocation.
- A linked list is a data structure where each node contains a data field and a pointer to the next node.
- It allows dynamic size and efficient insertion/deletion compared to arrays.
- A doubly linked list adds a pointer to the previous node, allowing traversal in both directions.
- A circular linked list connects the last node back to the first node, making it a continuous loop.
- Variations require changes to the node structure and functions like append/delete to handle the added previous/next pointers.
Here are the key steps to insert a new node into a linked list:
1. Check for available memory (node)
2. Create the new node and set its data
3. If inserting at head, update head pointer; else insert after the given node by updating next pointers.
4. Return
This presentations gives an introduction to the data structure linked-lists. I discuss the implementation of header-based linked-lists in C. The presentation runs through the code and provides the visualization of the code w.r.t pointers.
The document discusses various types of linked lists including circular linked lists, linked implementation of stacks and queues, and applications of linked lists. Circular linked lists form a closed loop where the last node points to the first node. Linked stacks and queues can be implemented using linked lists which allows dynamic memory allocation instead of fixed size arrays. Applications of linked lists include representing polynomials for arithmetic operations, adding long integers, and non-integer/heterogeneous lists.
linked list
singly linked list
insertion in singly linked list
DELETION IN SINGLY LINKED LIST
Searching a singly linked list
Doubly Linked List
insertion from Doubly linked list
DELETION from Doubly LINKED LIST
Searching a doubly linked list
Circular linked list
The document describes splay trees, a type of self-adjusting binary search tree. Splay trees differ from other balanced binary search trees in that they do not explicitly rebalance after each insertion or deletion, but instead perform a process called "splaying" in which nodes are rotated to the root. This splaying process helps ensure search, insert, and delete operations take O(log n) amortized time. The document explains splaying operations like zig, zig-zig, and zig-zag that rotate nodes up the tree, and analyzes how these operations affect the tree's balance over time through a concept called the "rank" of the tree.
Dokumen tersebut memberikan penjelasan mengenai konsep dasar data mining klasifikasi, proses klasifikasi menggunakan algoritma Naive Bayes, serta contoh kasus klasifikasi menggunakan atribut usia, pendapatan, pekerjaan, dan punya deposito atau tidak.
A linked list is a data structure made up of nodes that are connected to each other via pointers. Each node contains a data field as well as a pointer to the next node. Linked lists allow dynamic sizes and efficient insertion/deletion of nodes. Common linked list operations include appending nodes to the end, inserting nodes in a sorted order, traversing the list to display nodes, and deleting nodes. The code sample shows a template for a linked list class with functions to implement these operations by traversing the list and manipulating the node pointers accordingly.
A linked list is a linear data structure consisting of nodes that are connected to each other through pointers. Each node contains a data field and a pointer to the next node. Linked lists allow for efficient insertion and removal of nodes and are more flexible than arrays in terms of memory allocation. Common types of linked lists include singly linked lists, doubly linked lists, circular linked lists, and header linked lists.
The document defines and describes stacks, queues, and linked lists. It defines a stack as a LIFO data structure that allows push and pop operations. A queue is defined as a FIFO data structure that allows enqueue and dequeue operations. Linked lists are collections of nodes that contain data and a pointer to the next node. The document discusses implementations of stacks, queues, and linked lists using arrays and linked nodes. It also covers priority queues, deques, and circular linked lists.
This document discusses doubly linked lists. A doubly linked list is a list where each node contains a pointer to the next node and previous node. This allows traversal in both directions. The document explains how to implement a doubly linked list using a struct with next and previous pointers. It covers insertion, deletion, searching, and printing nodes in a doubly linked list by traversing forwards and backwards. Key operations like adding a node to the beginning, middle or end of the list are demonstrated along with deleting nodes and freeing memory.
A stack is a linear data structure that follows the LIFO (last in, first out) principle. Elements are inserted and removed from the top of the stack. Common stack operations include push to add an element and pop to remove the top element. Stacks can be implemented using arrays or linked lists. Stacks are useful for operations like converting infix expressions to postfix and evaluating postfix expressions using a stack to hold operands. Queues follow the FIFO (first in, first out) principle with elements added to the rear and removed from the front. Common queue operations are enqueue to add and dequeue to remove elements. Queues can also be implemented using arrays or linked lists. Linked lists store elements in nodes with each node
The document discusses linked lists, including their definition as a dynamic linear data structure composed of connected nodes where each node contains a data element and a pointer, common operations on linked lists such as traversal, insertion, and deletion, and variations like single vs. double linked lists and circular lists. Algorithms for searching, inserting, and deleting nodes from a singly linked list are presented along with advantages of linked lists over arrays for dynamic data structures.
The document discusses linked lists and their implementation in C. It defines linked lists as dynamic data structures that store data in nodes linked together via pointers. The key operations on linked lists include insertion and deletion of nodes, as well as traversing and searching the list. It describes implementing linked lists as singly linked lists, doubly linked lists, and circular linked lists. Functions are provided for basic linked list operations like insertion, deletion, display on singly linked lists, and implementations of stacks and queues using linked lists.
This document contains a presentation on linked lists. It includes:
1. An introduction to linked lists describing their representation using linked allocation and algorithms for inserting and deleting nodes.
2. Algorithms for inserting a node at the first, last, and ordered positions in a single linked list, as well as deleting a node and copying a linked list.
3. A section on linear linked list multiple choice questions.
Data Structure Introduction
Data Structure Definition
Data Structure Types
Data Structure Characteristics
Need for Data Structure
Stack Definition
Stack Representation
Stack Operations
Stack Algorithm
Program for Stack in C++
Linked List Definition
Linked List Representation
Linked List Operations
Linked List Algorithm
Program for Linked List in C++
Linked List Defination
Linked List Representation
Linked List Operations
Linked List Algorithm
Program for Linked List in C++
This document discusses linked lists and polynomials represented as linked lists. It provides details on singly linked lists, including how to implement insertion and deletion of nodes. It also describes how to represent stacks and queues as dynamically linked lists. Finally, it discusses representing polynomials using arrays or linked lists, and how to perform addition and multiplication of polynomials in each representation.
The document discusses double and circular linked lists. It covers inserting and deleting nodes from doubly linked lists and circular linked lists. Specifically, it describes how to insert nodes at different positions in a doubly linked list, such as at the front, after a given node, at the end, and before a given node. It also explains how to delete nodes from a doubly linked list. For circular linked lists, it outlines how to insert nodes in an empty list, at the beginning, at the end, and between nodes. It also provides the steps to delete nodes from a circular linked list.
The document discusses sorting algorithms, abstract data types (ADTs), and linked lists. It describes selection sort and insertion sort algorithms for sorting arrays. It then explains that linked lists are a more flexible data structure than arrays and defines a singly linked list as an ADT with nodes that point to the next node in the list. Functions for typical linked list operations like insertion, deletion, checking if empty, and printing the list are discussed.
The document discusses linked lists and their advantages over arrays. It defines a linked list as a linear data structure composed of nodes, where each node contains data and a pointer to the next node. The key points are:
- Linked lists have dynamic sizes while arrays are fixed. Inserting and deleting from linked lists is more efficient as it doesn't require shifting elements.
- Linked lists don't allow random access so operations like sorting are less efficient, while arrays don't waste space if fully filled.
- The document then describes the basic operations on a singly linked list like creation, insertion, deletion and searching and provides algorithms to implement these operations.
The document discusses list data structures and their implementation using arrays and linked memory. It describes common list operations like insertion, removal, searching, and provides examples of how to implement them with arrays and linked lists. Key list operations include adding and removing elements from different positions, accessing elements by index or pointer, and traversing the list forward and backward. Linked lists offer more flexibility than arrays by not requiring predefined memory allocation.
- A linked list is a data structure where each node contains a data field and a pointer to the next node.
- It allows dynamic size and efficient insertion/deletion compared to arrays.
- A doubly linked list adds a pointer to the previous node, allowing traversal in both directions.
- A circular linked list connects the last node back to the first node, making it a continuous loop.
- Variations require changes to the node structure and functions like append/delete to handle the added previous/next pointers.
Here are the key steps to insert a new node into a linked list:
1. Check for available memory (node)
2. Create the new node and set its data
3. If inserting at head, update head pointer; else insert after the given node by updating next pointers.
4. Return
This presentations gives an introduction to the data structure linked-lists. I discuss the implementation of header-based linked-lists in C. The presentation runs through the code and provides the visualization of the code w.r.t pointers.
The document discusses various types of linked lists including circular linked lists, linked implementation of stacks and queues, and applications of linked lists. Circular linked lists form a closed loop where the last node points to the first node. Linked stacks and queues can be implemented using linked lists which allows dynamic memory allocation instead of fixed size arrays. Applications of linked lists include representing polynomials for arithmetic operations, adding long integers, and non-integer/heterogeneous lists.
linked list
singly linked list
insertion in singly linked list
DELETION IN SINGLY LINKED LIST
Searching a singly linked list
Doubly Linked List
insertion from Doubly linked list
DELETION from Doubly LINKED LIST
Searching a doubly linked list
Circular linked list
The document describes splay trees, a type of self-adjusting binary search tree. Splay trees differ from other balanced binary search trees in that they do not explicitly rebalance after each insertion or deletion, but instead perform a process called "splaying" in which nodes are rotated to the root. This splaying process helps ensure search, insert, and delete operations take O(log n) amortized time. The document explains splaying operations like zig, zig-zig, and zig-zag that rotate nodes up the tree, and analyzes how these operations affect the tree's balance over time through a concept called the "rank" of the tree.
Dokumen tersebut memberikan penjelasan mengenai konsep dasar data mining klasifikasi, proses klasifikasi menggunakan algoritma Naive Bayes, serta contoh kasus klasifikasi menggunakan atribut usia, pendapatan, pekerjaan, dan punya deposito atau tidak.
មេរៀនៈ Data Structure and Algorithm in C/C++Ngeam Soly
This document provides an introduction to a lecture on data structures and algorithms. It discusses the lecturer's contact information and expectations for reading ahead of lectures. It then covers topics that will be discussed in the course, including programs and programming, introduction to programming, crafting programs effectively, what makes a good program, and why data structures and algorithms are important subjects. The document provides an overview of what will be covered in the course.
The binary search is faster than the sequential search. The complexity of binary search is O(log n) whereas the complexity of a sequential search is O(n). Stacks are used to evaluate algebraic or arithmetic expressions using prefix or postfix notations. Heap sort involves creating a max heap from the array and then replacing the root with the last element and rebuilding the heap for the remaining elements, repeating this process to sort the entire array.
This document discusses data structures and their applications. It defines key terms like data, data item, entity, attribute, field, record, and file. It explains that a data structure is a logical organization of data that specifies the data elements and operations that can be performed on them. Common operations include traversing, searching, inserting, and deleting. The choice of data structure depends on how frequently certain operations will be performed. Real-life data manipulation requires storage, retrieval, and transformation of user data.
This document provides information about Dream Valley College for Girls Centre for Educational Excellence. It includes an index and presentation on data structures covering topics like arrays, linked lists, queues, trees, and graphs. The presentation was presented by Harish Sir and includes definitions, examples, and diagrams to explain each data structure concept.
The document discusses arrays in Java. It defines arrays as ordered lists that store multiple values of the same type. Arrays allow accessing elements using indexes, and declaring arrays involves specifying the type and size. The document covers key array concepts like initialization, bounds checking, passing arrays as parameters, multidimensional arrays, and sorting and searching arrays.
Deletion in a B-tree involves removing a key from any node while maintaining the properties of the B-tree. There are three main cases for deletion: 1) deleting from a leaf node with enough keys, 2) deleting from a leaf node with the minimum number of keys which may involve borrowing keys from a sibling, and 3) deleting from an internal node which may involve moving keys between subtrees or merging child nodes. The goal is to delete the target key while keeping all nodes with at least the minimum number of keys.
stack and queue array implementation in java.CIIT Atd.
This document discusses stack and queue data structures. It provides code examples in Java to demonstrate push and pop operations in a stack and enqueue and dequeue operations in a queue using arrays. Key aspects covered include LIFO and FIFO behavior, stack and queue operations, and sample code to implement stacks and queues in Java with output examples.
B-trees and B+-trees are common indexing structures used in relational database management systems. B-trees allow for rapid searching of data in large tables. They balance search trees through node splitting and ensure search efficiency even with millions of records. B+-trees are similar but only store data records in leaf nodes, improving search performance further. Both support efficient insertion and deletion through node splitting and merging as needed to maintain balance.
This document discusses phasor diagrams which are diagrams that use phasors to represent the amplitude and phase of sinusoidal quantities. Phasor diagrams allow engineers to add vectors that represent voltages and currents to show their relationship and calculate power. They provide a simple geometric method to analyze AC circuits and understand relationships between voltage, current, and power in sinusoidal steady state conditions.
The document discusses various sorting and searching algorithms, including quick sort, merge sort, linear search, and binary search. It provides details on implementing quick sort, including selecting a pivot, partitioning the list around the pivot, and recursively sorting the sublists. The worst-case time complexity of quick sort is O(n^2) if the pivot is poorly chosen, but it can be improved to O(n log n) on average by selecting the median element as the pivot. The document also introduces merge sort and its implementation.
The document discusses stacks and their implementation. It defines a stack as a LIFO data structure where elements can only be inserted or removed from the top. The basic stack operations are PUSH, which inserts an element onto the top of the stack, and POP, which removes the top element. Stacks can be used to check if parentheses in an arithmetic expression are correctly nested by scanning the expression and using a stack to match opening and closing parentheses.
The document discusses various topics related to dynamic linked lists including their meaning, traversal, insertion, and deletion operations. It describes implementing a list abstract data type using either an array or linked list as the underlying data structure. Key points covered include traversing a linked list using pointers, inserting and deleting nodes by allocating and deallocating memory dynamically, and the additional operations needed for a sorted linked list such as insert as first and remove first elements.
The document discusses B-trees, which are self-balancing tree data structures that allow efficient insertion and deletion of data while keeping the tree height shallow. B-trees allow for efficient searching, insertion, and deletion of data in logarithmic time by allowing nodes to have more than two child nodes, and by splitting and merging nodes as needed to balance the tree during operations. The document covers the basic structure and properties of B-trees and explains the algorithms for insertion and deletion of keys through cases involving splitting, merging, redistribution and underflow of nodes.
This document discusses dynamic memory allocation and linked lists. It describes functions like malloc, calloc, free, and realloc for allocating and releasing memory at runtime. It also explains the concepts of linked lists, where each node contains data and a pointer to the next node, allowing flexible growth and rearrangement but slower random access than arrays.
The document discusses B-trees, which are self-balancing search trees used to store large datasets. B-trees overcome limitations of storing data in memory by keeping the tree partially balanced and stored on disk. The document outlines properties of B-trees including that internal nodes must have a minimum number of children based on the tree's order, and that inserting data may cause nodes to split and keys to propagate up the tree to maintain balance.
The document discusses implementing a singly-linked list to store prime numbers between 1 and 10,00,000. It explains that a linked list allows dynamic memory allocation as nodes are added, with each node containing a data field and link to the next node. To insert a new prime number, a node is allocated, its data field is set, and it is added to the end of the linked list by making the current last node's next pointer point to the new node. This allows storing an unknown number of prime numbers without predefined array size limits.
1) Linked lists are a data structure that store elements in individual nodes that are connected to each other using pointers. This allows for dynamic memory allocation as opposed to static allocation in arrays.
2) The basic operations on linked lists include creation, insertion, deletion, traversal, searching, concatenation, and displaying the list. Insertion and deletion can be done at the beginning, middle, or end of the list.
3) Linked lists are useful for applications that require dynamic memory allocation, like stacks, queues, and storing objects that may vary in number, such as images to burn to a CD.
A linked list is a data structure where each node contains a data field and a reference to the next node. The head node points to the first node, and nodes are connected through next references. Linked lists allow for efficient insertions and deletions compared to arrays. Common types include singly linked, doubly linked, circular singly linked, and circular doubly linked lists. Operations on linked lists include insertion, deletion, and searching.
In computer science, a linked list is a linear collection of data elements, in which linear order is not given by their physical placement in memory. Instead, each element points to the next
Revisiting a data structures in detail with linked list stack and queuessuser7319f8
This document discusses various data structures including arrays, stacks, queues, and linked lists. It provides code examples for creating and manipulating each type of data structure. Specifically, it shows code for inserting and deleting elements from arrays and linked lists. It also includes algorithms and code for common stack and queue operations like push, pop, enqueue, and dequeue. The document provides a detailed overview of linear and non-linear data structures.
This document provides information about linked lists. It defines a linked list as a linear data structure where nodes are linked using pointers. Each node contains a data field and a pointer to the next node. It compares linked lists to arrays, noting that linked lists can dynamically allocate memory as needed, while arrays have fixed sizes. It describes the two main types of linked lists - singly linked and doubly linked. It provides examples of basic linked list operations like insertion, deletion and traversal for both singly and doubly linked lists. It also discusses some applications of linked lists like implementing stacks, queues and representing polynomials.
This document discusses representations of sparse matrices using linked lists. It explains that sparse matrices, which contain mostly zero values, can be stored more efficiently using a triplet representation or linked representation rather than a standard 2D array. The triplet representation stores only the non-zero elements, their row and column indices, and matrix size information. It provides an example of a 4x5 sparse matrix represented as a triplet array with 6 non-zero elements. Linked representation stores the sparse matrix as a linked list, where each node contains the row, column and value of a non-zero element. Applications of sparse matrix representations include storing large sparse datasets efficiently.
This document discusses linked lists and representing stacks and queues using linked lists. It provides information on different types of linked lists including singly, doubly, and circular linked lists. It describes inserting, deleting, and traversing nodes in a singly linked list. It also provides a C program example to implement a stack using a linked list with functions for push, pop, and display operations. The document discusses how linked lists are dynamic data structures that can grow and shrink in size as needed, unlike arrays.
Linked lists are linear data structures where elements are linked using pointers. The three main types are singly, doubly, and circular linked lists. Linked lists allow dynamic memory allocation and fast insertion/deletion compared to arrays but slower access. A linked list contains nodes, each with a data field and pointer to the next node. Basic operations on linked lists include insertion, deletion, traversal, and search. Doubly linked lists include pointers to both the next and previous nodes.
The document outlines the key concepts of linked lists including:
- Linked lists allow for dynamic resizing and efficient insertion/deletion unlike arrays.
- A linked list contains nodes that have a data field and a pointer to the next node.
- Common operations on linked lists include insertion, deletion, searching, and traversing the list.
- The time complexity of these operations depends on whether it's at the head, tail, or interior node.
- Linked lists can be implemented using classes for the node and linked list objects.
This presentation covers data structures including arrays, linked lists, and stacks. It discusses array types (one and multi-dimensional), linked list types (singly, doubly, circular), and common operations for each. Stack operations like push, pop, peek and applications for infix, prefix, postfix notation conversion are also explained with examples. Code snippets are provided for array traversal, insertion, deletion as well as linked list creation, insertion, deletion and traversal.
Linked lists are data structures that store data in scattered locations in memory. Each data item or node contains a data part that holds the actual data and a link part that points to the next node. The nodes are linked together using these links. A linked list requires an external pointer to point to the first node. Operations like traversing, searching, inserting and deleting nodes can be performed on linked lists by manipulating these node links.
The document discusses linked lists and their basic operations. It defines a linked list as a series of connected nodes where each node contains a data element and a pointer to the next node. The basic operations of linked lists include inserting nodes, finding or deleting nodes by value, and traversing the list. It also discusses different types of linked lists like singly linked lists, doubly linked lists, and circular linked lists. The document explains how to implement operations like insertion, deletion, and traversal in detail with examples.
The document discusses different data structures including stacks, queues, linked lists, and their implementations. It defines stacks as LIFO structures that can add and remove items from one end only. Queues are FIFO structures that add to one end and remove from the other. Linked lists store data in nodes that point to the next node. Stacks, queues and linked lists can all be implemented using arrays or by linking nodes. Priority queues and deques are also discussed.
Linked lists are a data structure made up of connected nodes, where each node contains data and a pointer to the next node. The three basic operations on linked lists are insertion, deletion, and traversal of nodes. There are variations like circular linked lists where the last node points to the first, and doubly linked lists where each node points to both the next and previous nodes. Linked lists have advantages over arrays in that they are dynamically sized and nodes can be easily inserted and deleted without moving other elements.
A linked list is a data structure made up of nodes that are connected to each other. Each node contains data and a link to the next node. Linked lists can grow and shrink dynamically as nodes are added or removed. There are several types of linked lists including single linked lists where navigation is forward only, doubly linked lists where navigation is bidirectional, and circular linked lists where the last node links back to the first node. Common operations on linked lists include appending nodes to add to the end, inserting nodes in a sorted manner, and deleting nodes by value. These operations involve allocating memory for new nodes, linking nodes together, and removing nodes by adjusting pointers.
Linked list and its operations - Traversalkasthurimukila
The document discusses linked lists and operations performed on singly linked lists. It defines a linked list as a data structure containing nodes that point to the next node in the list. Singly linked lists contain nodes with a data field and pointer to the next node. Common operations on singly linked lists include traversing the list, inserting and deleting nodes from different positions, searching for a node, sorting list elements, and merging two linked lists.
Dokumen tersebut memberikan tips untuk membuat formatting kode program yang baik agar mudah dibaca dan dipahami. Terdapat dua jenis formatting, yaitu vertical dan horizontal formatting. Secara vertical, kode perlu diatur dengan memperhatikan konsep-konsep, jarak antar konsep, kerapatan kode yang berkaitan, dan letak deklarasi dan pemanggilan fungsi. Secara horizontal, perlu memperhatikan pemberian jarak, penyamaan baris, dan pengindentasian untuk membedakan struktur program.
Slide ini menjelaskan perihal penggunaan komentar yang baik dan buruk pada suatu kode program. Slide ini merupakan bahan ajar untuk mata kuliah Clean Code dan Design Pattern.
Dokumen tersebut memberikan tips-tips untuk membuat nama variabel, fungsi, kelas, dan paket yang baik dalam pembuatan kode program. Beberapa tips utama adalah menggunakan nama yang jelas maksudnya, hindari penggunaan encoding, gunakan kata benda untuk nama kelas dan verba untuk nama metode, serta tambahkan konteks yang bermakna.
Dokumen tersebut membahas tentang pengujian perangkat lunak, termasuk definisi pengujian perangkat lunak, tujuan pengujian, jenis pengujian seperti manual testing, automated testing, unit testing, integration testing, serta metode pengujian seperti white box testing dan black box testing.
Slide ini berisi penjelasan tentang Data Mining Klasifikasi. Di dalamnya ada tiga algoritma yang dibahas, yaitu: Naive Bayes, kNN, dan ID3 (Decision Tree).
Dokumen tersebut membahas algoritma program dinamis untuk menentukan lintasan terpendek antara dua simpul dalam sebuah graf. Metode yang digunakan adalah program dinamis mundur dimana permasalahan dibagi menjadi beberapa tahap dan dihitung secara mundur untuk menentukan nilai optimal pada setiap tahap. Hasil akhir adalah terdapat tiga lintasan terpendek dengan panjang 11 antara simpul 1 dan 10.
Teks tersebut membahas strategi algoritma Divide and Conquer untuk memecahkan masalah. Strategi ini membagi masalah menjadi submasalah kecil, memecahkan submasalah tersebut secara rekursif, lalu menggabungkan hasilnya untuk mendapatkan solusi masalah awal. Dua contoh masalah yang dijelaskan adalah mencari nilai maksimum dan minimum dalam tabel, serta mencari pasangan titik terdekat dalam himpunan titik.
Slide ini berisi penjelasan tentang teorema-teorema yang berlaku untuk notasi asimptotik beserta cara perhitungannya untuk kebutuhan waktu suatu algoritma.
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov
Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
FL Studio Producer Edition Crack 2025 Full Versiontahirabibi60507
Copy & Past Link 👉👉
http://drfiles.net/
FL Studio is a Digital Audio Workstation (DAW) software used for music production. It's developed by the Belgian company Image-Line. FL Studio allows users to create and edit music using a graphical user interface with a pattern-based music sequencer.
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers
Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
Read More:- https://www.esofttools.com/nsf-to-pst-converter.html
Copy & Paste On Google >>> https://dr-up-community.info/
EASEUS Partition Master Final with Crack and Key Download If you are looking for a powerful and easy-to-use disk partitioning software,
F-Secure Freedome VPN 2025 Crack Plus Activation New Versionsaimabibi60507
Copy & Past Link 👉👉
https://dr-up-community.info/
F-Secure Freedome VPN is a virtual private network service developed by F-Secure, a Finnish cybersecurity company. It offers features such as Wi-Fi protection, IP address masking, browsing protection, and a kill switch to enhance online privacy and security .
Landscape of Requirements Engineering for/by AI through Literature ReviewHironori Washizaki
Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
Why Orangescrum Is a Game Changer for Construction Companies in 2025Orangescrum
Orangescrum revolutionizes construction project management in 2025 with real-time collaboration, resource planning, task tracking, and workflow automation, boosting efficiency, transparency, and on-time project delivery.
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search.
Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.
Discover why Wi-Fi 7 is set to transform wireless networking and how Router Architects is leading the way with next-gen router designs built for speed, reliability, and innovation.
9. Definition
• Alloc is statement that can be used
to order place in memory while program
is running.
• Dealloc is statement that can be
used to delete place which had been
ordered while program is running.
20. Data structure that is prepared
sequentially, dynamically, and
infinite. Linked list is connected by
pointer.
Description
21. Array VS Linked List
ARRAY LINKED LIST
Static Dynamic
Insert and Delete are finite Insert and Delete are infinite
Random Access Sequential Access
Delete element is only delete value
Delete element is truly delete
space
22. • Single Linked List
• Double Linked List
• Circular Linked List
Types of Linked List
24. Linked list that its node consists of one
link/pointer that refers to another node.
Ilustration of node:
Description
Info Field (Info) Connection
Field (Next)
29. Pointer (awal and akhir) is given nil as
their value.
Creation
awal akhir
awal nil akhir nil
30. • If list is empty (awal = nil).
Front Insertion
baru
baru 1
baru 1
awal akhir
alloc(baru)
baru.next nil
baru.info 1
awal baru
akhir baru
31. • If list isn’t empty (awal ≠ nil). For example,
there is list that has two nodes:
Front Insertion (cont’d)
akhirawal
2 3
One node will be inserted in front of list:
1baru
alloc(baru)
baru.info 1
32. New node will be inserted before the node that
was refered by awal.
Front Insertion (cont’d)
baru 1
awal
2
akhir
3
baru↑.next awal
33. After new node was inserted, move awal to new
node.
Front Insertion (cont’d)
awal
2 3
baru 1
akhir
awal baru
34. The last result for front insertion if linked list
wasn’t empty:
Front Insertion (cont’d)
baru 1
awal
2 3
akhir
35. Procedure SisipDepanSingle(Input elemen : tipedata, I/O awal, akhir :
nama_pointer)
{I.S. : data yang akan disisipkan (elemen), pointer penunjuk awal dan pointer
penunjuk akhir sudah terdifinisi}
{F.S. : menghasilkan satu simpul yang disisipkan di depan pada single linked
list}
Kamus :
baru : nama_pointer
Algoritma :
alloc(baru)
baru↑.info elemen
If (awal = nil)
Then
baru↑.next nil
akhir baru
Else
baru↑.next awal
EndIf
awal baru
EndProcedure
36. • If list is empty (awal = nil) the
process is same as front
insertion if linked list is
empty.
Back Insertion
37. • If list isn’t empty (awal ≠ nil). For example,
there is list that has two nodes:
Back Insertion (cont’d)
awal
3 2
akhir
New node that will be inserted:
baru 1
alloc(baru)
baru.next nil
baru.info 1
38. New node will be inserted after the node that
was refered by akhir.
Back Insertion (cont’d)
baru 1
akhirawal
3 2 akhir.next baru
39. Move akhir to new node.
Back Insertion (cont’d)
akhir baru
akhirawal
3 2
baru 1
40. The last result for back insertion if linked list
wasn’t empty:
Back Insertion (cont’d)
awal
3 2
baru
1
akhir
41. Procedure SisipBelakangSingle(Input elemen : tipedata, I/O awal, akhir :
nama_pointer)
{I.S. : data yang akan disisipkan (elemen), pointer penunjuk awal dan pointer
penunjuk akhir sudah terdifinisi}
{F.S. : menghasilkan satu simpul yang disisipkan di belakang pada single
linked list}
Kamus :
baru : nama_pointer
Algoritma :
alloc(baru)
baru↑.info elemen
baru↑.next nil
If (awal = nil)
Then
awal baru
Else
akhir↑.next baru
EndIf
akhir baru
EndProcedure
42. • If list is empty (awal = nil) the
process is same as front
insertion if linked list is
empty.
Middle Insertion
43. • If list isn’t empty (awal ≠ nil).
Middle Insertion (cont’d)
awal
2 54
akhir
3
New node that will be inserted after 4:
baru 1
alloc(baru)
baru.info 1
44. Search node 4 using sequential search and
bantu pointer.
Middle Insertion (cont’d)
bantu
baru 1
awal
2 54
akhir
3
bantu
45. Connect the connection field from new node to
the neighbour node of node that was refered by
bantu.
Middle Insertion (cont’d)
baru.next bantu↑.next
baru 1
awal
2 54
akhir
3
bantu
46. After new node was connected with node 4 then
refer the connection field of node that was
refered by bantu to new node.
Middle Insertion (cont’d)
bantu.next baru
bantuawal
2
baru 1
4
akhir
3 5
47. The last result for middle insertion if linked list
wasn’t empty:
Middle Insertion (cont’d)
bantu
baru 1
2
akhir
5
awal
43
48. Procedure SisipTengahSingle(Input elemen : tipedata, I/O awal, akhir :
nama_pointer)
{I.S. : data yang akan disisipkan (elemen), pointer penunjuk awal dan pointer
penunjuk akhir sudah terdifinisi}
{F.S. : menghasilkan satu simpul yang disisipkan di tengah pada single linked list}
Kamus :
baru,bantu : nama_pointer
ketemu : boolean
datasisip : tipedata
Algoritma :
If (awal = nil)
Then
alloc(baru)
baru↑.info elemen
baru↑.next nil
49. awal baru
akhir baru
Else
Input(datasisip)
bantu awal
ketemu false
While (not ketemu and bantu ≠ nil) do
If (datasisip = bantu↑.info)
Then
ketemu true
Else
bantu bantu↑.next
EndIf
EndWhile
50. If (ketemu)
Then
alloc(baru)
baru↑.info elemen
If (bantu = akhir)
Then
sisip_belakang_single(elemen,awal,akhir)
Else
baru↑.next bantu↑.next
bantu↑.next baru
EndIf
Else
Output(“Data yang akan disisipkan tidak ada”);
EndIf
EndIf
EndProcedure
51. • Delete one node in beggining of linked list if
linked list has only one node (awal = akhir).
Front Deletion
awal akhir
1
52. If deletion happens in linked list with one node
then linked list will be empty.
Front Deletion (cont’d)
awal akhir
phapus
elemen
1phapus
phapus awal elemen phapus .info
dealloc(phapus)
awal nil akhir nil
1
awal akhir
53. • If linked list has more than one node (awal ≠
akhir). For example, linked list has two
nodes.
Front Deletion (cont’d)
awal
2 3
akhir
55. The last result for front deletion if linked list has
more than one node:
Front Deletion (cont’d)
phapus
awal
3
akhir
2
56. Procedure HapusDepanSingle(Output elemen : tipedata, I/O awal, akhir : nama_pointer)
{I.S. : pointer penunjuk awal dan pointer penunjuk akhir sudah terdifinisi}
{F.S. : menghasilkan single linked list yang sudah dihapus satu simpul di depan}
Kamus :
phapus : nama_pointer
Algoritma :
phapus awal
elemen baru↑.info
If (awal = akhir)
Then
awal nil
akhir nil
Else
awal awal ↑.next
EndIf
dealloc(phapus)
EndProcedure
57. • Delete one node in back of linked list if
linked list has only one node (awal = akhir).
This process is same as front
deletion if linked list has
only one node.
Back Deletion
58. • If linked list has more than one node (awal ≠
akhir). For example, linked list has three
nodes.
Back Deletion (cont’d)
awal
1 32
akhir
59. Back Deletion (cont’d)
phapus
awal
1 3
akhir
2
elemen
phapus phapusakhirawal
1 32
phapus awal
elemen akhir.info
phapus phapus.next
phapus phapus.next
akhir phapus
61. The last result for back deletion if linked list has
more than one node:
Back Deletion (cont’d)
phapus phapusakhir
3
awal
12
62. Procedure HapusBelakangSingle(Output elemen : tipedata, I/O awal, akhir : nama_pointer)
{I.S. : pointer penunjuk awal dan pointer penunjuk akhir sudah terdifinisi}
{F.S. : menghasilkan single linked list yang sudah dihapus satu simpul di belakang}
Kamus :
phapus : nama_pointer
Algoritma :
phapus awal
elemen baru↑.info
If (awal = akhir)
Then
awal nil
akhir nil
63. Else
while (phapus↑.next ≠ akhir) do
phapus phapus↑.next
endwhile
akhir phapus
phapus phapus↑.next
akhir↑.next nil
EndIf
dealloc(phapus)
EndProcedure
64. • Delete one node in middle of linked list if
linked list has only one node (awal = akhir).
This process is same as front
deletion if linked list has
only one node.
Middle Deletion
65. • If linked list has more than one node (awal ≠
akhir). For example, linked list has four
nodes and user want to delete third node.
Middle Deletion (cont’d)
awal
2 54
akhir
3
66. Search the third node start from the first node.
If node is found then save the info of this node
to the variable elemen.
Middle Deletion (cont’d)
phapus
posisihapus=2awal
2 54
akhir
3
posisihapus=1 posisihapus=3
phapus
elemen elemenphapus.info
67. Because the connection field of previous node must be
connected to the next node of node that will be
deleted so we need pointer bantu that refer the node
that will be deleted.
Middle Deletion (cont’d)
bantuawal
2 54
phapus akhir
3
posisihapus=3
68. Connect the connection field of the node that was
referred by pointer bantu to the neighbour node.
Delete the node that was referred by pointer phapus.
Middle Deletion (cont’d)
awal
2 54
phapus akhir
3
posisihapus=3bantu
bantu.next phapus.next
dealloc(phapus)
69. The last result for middle deletion if linked list
has more than one node:
Middle Deletion (cont’d)
5
akhir
2
phapus
posisihapus=1posisihapus=2 posisihapus=3
phapus
bantuawal
43 43 5
akhir
awal
70. Operation that visiting all nodes in linked list
start from the first node until last node.
Traversal
awal
2 54
akhir
3
For example, shown the process to output data:
• Place one pointer bantu in the first node
awa
l
2 54
akhir
3
bantu
71. The value in info field will be output to screen from the
node that was referred by bantu then pointer bantu
will move to the next node until all nodes were visited
(bantu = nil).
Traversal
awal
2 54
akhir
3
bantu bantu bantu bantu
3 4 2 5Screen Output: