8.DATA STRUCTURES UNIT 1 AND 2 CS3301PPT.pptxvenigkrish89
The document provides an extensive overview of data structures, specifically focusing on lists and abstract data types (ADTs). It discusses linear and non-linear data structures, their operations such as creation, insertion, deletion, and modification, while explaining the conceptual differences between arrays and linked lists. Additionally, it covers various types of linked lists including singly linear, circular, doubly linear, and doubly circular linked lists, alongside their operations and implementation challenges.
The document discusses data structures and algorithms. It aims to understand abstract data types (ADTs) and their implementation, apply sorting and searching techniques, and learn algorithm design. It covers linear data structures like arrays and linked lists, and non-linear structures like trees and graphs. Specifically, it describes the list ADT and implementations using arrays and linked lists, discussing creation, insertion, deletion and other list operations.
The document discusses data structures and abstract data types (ADTs). It provides examples of common ADTs like lists, trees, stacks, and graphs. It specifically focuses on lists, describing two common implementations of lists as arrays and linked lists. It discusses the advantages and disadvantages of each implementation and provides examples of common list operations like insertion, deletion, and searching.
This document discusses lists as an abstract data type (ADT) and their implementation using arrays and linked lists. It defines a list as a finite, ordered sequence of elements and describes common list operations like insertion, deletion, traversal etc. Linked lists are introduced as an alternative implementation where each node contains a data field and link to the next node. The advantages of linked lists over arrays for dynamic data are also highlighted. Various real-world applications of lists are listed like implementing stacks, queues, graphs and dynamic memory allocation.
The document discusses arrays and linked lists as abstract data types (ADTs). It describes arrays as the simplest data structure, storing elements in sequential memory locations. Linked lists store elements using pointers, with each node containing data and a pointer to the next node. The document outlines common operations on arrays and linked lists like traversal, insertion, deletion, and searching. It also discusses different types of linked lists like singly linked, doubly linked, and circular linked lists.
EC2311 – Data Structures and C ProgrammingPadma Priya
The document covers linear data structures and their implementations in C programming, focusing on abstract data types (ADTs) such as lists, stacks, and queues. It discusses the characteristics and operations of each data structure, including traversal, search, insertion, and deletion, and differentiates between static and dynamic structures. Additionally, it provides implementation details, advantages, and disadvantages of using arrays and linked lists for these structures.
Data structures and Algorithm analysis_Lecture 2.pptxAhmedEldesoky24
This document discusses different data structures for lists, including abstract data types (ADTs), arrays, singly linked lists, and doubly linked lists. It describes common list operations like insert, remove, find, and their time complexities for each implementation. Array-based lists allow direct access but expensive updates. Linked lists have efficient insertion/deletion but slow random access. Doubly linked lists and circular lists add previous pointers for easier traversal in both directions.
The document outlines an online course on Data Structures for second-year engineering students, detailing course objectives, unit topics, and types of data structures such as arrays, linked lists, stacks, queues, trees, and graphs. It discusses abstract data types, various algorithms for sorting and searching, and performance analysis of data structures. Additionally, it includes a list of textbooks, references, and resources for further study.
The document discusses lists as a data structure and how they can be implemented. Lists are collections of ordered elements that allow inserting, removing, and accessing elements by position. Lists can be implemented using arrays by storing elements in consecutive memory locations and tracking the current position. Operations like adding, removing, getting, and updating elements require shifting elements in the array. Linked lists are also discussed as an alternative implementation that uses linked memory locations rather than a consecutive array.
This document summarizes a lecture on arrays and linked lists. It discusses arrays, including how to declare and access array elements. It then covers linear arrays and 2-dimensional arrays. Linked lists are introduced, including how they are composed of nodes that link to the next node. Operations on linked lists like traversing, searching, inserting and deleting nodes are described. Doubly linked lists are also covered, which include pointers to both the next and previous nodes.
This document discusses various common data structures, including their definitions, examples, and basic operations. It begins by defining an abstract data type and explaining that a data structure provides one way to implement an ADT by organizing data. Then it provides examples of common data structures like queues, stacks, binary search trees, lists, arrays, linked lists, graphs, and hashing. For each it briefly explains what it is, potential applications, and some basic operations that can be performed on it.
This document discusses the key concepts and operations related to linked lists. It describes the different types of linked lists including singly linked lists, doubly linked lists, circular linked lists, and circular doubly linked lists. It provides algorithms for common linked list operations like insertion, deletion, and traversal. Memory allocation and various applications of linked lists are also covered.
The document outlines the course structure for IT 4043: Data Structures and Algorithms, including lecture and practical hours, assessments, and a syllabus covering topics like abstract data types, list operations, stacks, and algorithms. It also discusses data structures such as arrays, linked lists, and their applications in real-world data storage. Additionally, examples of methods and implementations related to linear lists and abstract data types are provided.
This document discusses data structures and algorithms. It defines data types and data structures, and provides examples of common data structures like arrays, linked lists, stacks, queues, and trees. It also discusses operations on data structures like traversing, searching, inserting, and deleting. Algorithms are used to manipulate the data in data structures. The time and space complexity of algorithms are also introduced. Overall, the document provides an overview of key concepts related to data structures and algorithms.
This document provides an overview of a lecture on data structures. It discusses how data structures prepare students for advanced courses and covers common structures like arrays, linked lists, stacks, queues, trees and graphs. It implements these in C++. The grading breakdown is provided. Key concepts are defined, like what a data structure is and why they are needed. Examples of various data structures are outlined like arrays, linked lists, stacks and queues. Arrays are described in more detail about how they are declared and accessed.
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.
This document discusses linear and non-linear data structures. Linear data structures like arrays, stacks, and queues store elements sequentially. Static linear structures like arrays have fixed sizes while dynamic structures like linked lists can grow and shrink. Non-linear structures like trees and graphs store elements in a hierarchical manner. Common abstract data types (ADTs) include stacks, queues, and lists, which define operations without specifying implementation. Lists can be implemented using arrays or linked lists.
This document provides an introduction to data structures and algorithms. It defines key terms like data structure, abstract data type, and algorithm. It also covers different types of data structures like arrays, linked lists, stacks, and queues. Specifically, it discusses the List abstract data type and implementations of lists using arrays and linked lists. It provides examples of common list operations like insertion, deletion, searching, and printing when using arrays and linked lists to represent a list. The running time of these operations is discussed as well.
The document explains the fundamentals of data structures, covering their definitions, design aspects, and common types such as arrays, linked lists, and trees, while emphasizing the importance of efficient data organization for program performance. It details operations on data structures, complexity analysis of algorithms, and various implementation techniques for specific structures. Additionally, the document discusses performance metrics and applications of structures such as binary trees and heaps, alongside their comparative advantages and limitations.
This document discusses data structures and provides examples of different linear data structures including arrays, stacks, queues, and linked lists. It begins by defining what a data structure is, explaining that a data structure organizes data in a systematic way to allow for efficient use. The document then reviews key concepts about each linear data structure, including common operations, implementations using arrays vs pointers, and examples of applications that each data structure can be used for. Real-world examples are provided to illustrate common uses of different data structures.
This document discusses data structures and algorithms. It defines data structures as representations of logical relationships between data elements that consider both the elements and their relationships. It classifies data structures as primitive, non-primitive, and abstract data types. It describes linear data structures like lists, stacks, and queues and non-linear structures. It provides examples of implementations like arrays, linked lists, and indirect addressing for different data structures.
Data can exist in various forms such as numbers, text, images, and more. Data itself has little meaning until it is processed to extract useful information. There are different types of data including categorical/qualitative data, which represents characteristics like gender, and numerical/quantitative data, which can be discrete like coin flips or continuous like measurements. Common data structures used to organize and store data include arrays, linked lists, stacks, queues, trees and graphs. Efficient searching of data structures is important and can be done using methods like linear search, which sequentially checks each element, and binary search, which can more quickly find elements in a sorted data set.
The document provides an overview of data structures and algorithms, emphasizing the classification of data structures into primitive and non-primitive types, with further details on linear and non-linear structures. It explains various implementations such as arrays, linked lists, stacks, and queues, including their operations like push, pop, enqueue, and dequeue, while highlighting their practical applications. The text also covers concepts like Abstract Data Types (ADT) and specific implementations, illustrating the significance of data organization and retrieval methods in programming.
A singly linked list is a linear data structuresangeethavinoth
The document presents information on Abstract Data Types (ADT), specifically focusing on lists and their operations such as insertion, deletion, searching, and updating. It discusses static and dynamic data structures, emphasizing the use of arrays as a form of static list. The document includes examples and syntax for array declaration and manipulation.
The document discusses lists as a data structure and how they can be implemented. Lists are collections of ordered elements that allow inserting, removing, and accessing elements by position. Lists can be implemented using arrays by storing elements in consecutive memory locations and tracking the current position. Operations like adding, removing, getting, and updating elements require shifting elements in the array. Linked lists are also discussed as an alternative implementation that uses linked memory locations rather than a consecutive array.
This document summarizes a lecture on arrays and linked lists. It discusses arrays, including how to declare and access array elements. It then covers linear arrays and 2-dimensional arrays. Linked lists are introduced, including how they are composed of nodes that link to the next node. Operations on linked lists like traversing, searching, inserting and deleting nodes are described. Doubly linked lists are also covered, which include pointers to both the next and previous nodes.
This document discusses various common data structures, including their definitions, examples, and basic operations. It begins by defining an abstract data type and explaining that a data structure provides one way to implement an ADT by organizing data. Then it provides examples of common data structures like queues, stacks, binary search trees, lists, arrays, linked lists, graphs, and hashing. For each it briefly explains what it is, potential applications, and some basic operations that can be performed on it.
This document discusses the key concepts and operations related to linked lists. It describes the different types of linked lists including singly linked lists, doubly linked lists, circular linked lists, and circular doubly linked lists. It provides algorithms for common linked list operations like insertion, deletion, and traversal. Memory allocation and various applications of linked lists are also covered.
The document outlines the course structure for IT 4043: Data Structures and Algorithms, including lecture and practical hours, assessments, and a syllabus covering topics like abstract data types, list operations, stacks, and algorithms. It also discusses data structures such as arrays, linked lists, and their applications in real-world data storage. Additionally, examples of methods and implementations related to linear lists and abstract data types are provided.
This document discusses data structures and algorithms. It defines data types and data structures, and provides examples of common data structures like arrays, linked lists, stacks, queues, and trees. It also discusses operations on data structures like traversing, searching, inserting, and deleting. Algorithms are used to manipulate the data in data structures. The time and space complexity of algorithms are also introduced. Overall, the document provides an overview of key concepts related to data structures and algorithms.
This document provides an overview of a lecture on data structures. It discusses how data structures prepare students for advanced courses and covers common structures like arrays, linked lists, stacks, queues, trees and graphs. It implements these in C++. The grading breakdown is provided. Key concepts are defined, like what a data structure is and why they are needed. Examples of various data structures are outlined like arrays, linked lists, stacks and queues. Arrays are described in more detail about how they are declared and accessed.
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.
This document discusses linear and non-linear data structures. Linear data structures like arrays, stacks, and queues store elements sequentially. Static linear structures like arrays have fixed sizes while dynamic structures like linked lists can grow and shrink. Non-linear structures like trees and graphs store elements in a hierarchical manner. Common abstract data types (ADTs) include stacks, queues, and lists, which define operations without specifying implementation. Lists can be implemented using arrays or linked lists.
This document provides an introduction to data structures and algorithms. It defines key terms like data structure, abstract data type, and algorithm. It also covers different types of data structures like arrays, linked lists, stacks, and queues. Specifically, it discusses the List abstract data type and implementations of lists using arrays and linked lists. It provides examples of common list operations like insertion, deletion, searching, and printing when using arrays and linked lists to represent a list. The running time of these operations is discussed as well.
The document explains the fundamentals of data structures, covering their definitions, design aspects, and common types such as arrays, linked lists, and trees, while emphasizing the importance of efficient data organization for program performance. It details operations on data structures, complexity analysis of algorithms, and various implementation techniques for specific structures. Additionally, the document discusses performance metrics and applications of structures such as binary trees and heaps, alongside their comparative advantages and limitations.
This document discusses data structures and provides examples of different linear data structures including arrays, stacks, queues, and linked lists. It begins by defining what a data structure is, explaining that a data structure organizes data in a systematic way to allow for efficient use. The document then reviews key concepts about each linear data structure, including common operations, implementations using arrays vs pointers, and examples of applications that each data structure can be used for. Real-world examples are provided to illustrate common uses of different data structures.
This document discusses data structures and algorithms. It defines data structures as representations of logical relationships between data elements that consider both the elements and their relationships. It classifies data structures as primitive, non-primitive, and abstract data types. It describes linear data structures like lists, stacks, and queues and non-linear structures. It provides examples of implementations like arrays, linked lists, and indirect addressing for different data structures.
Data can exist in various forms such as numbers, text, images, and more. Data itself has little meaning until it is processed to extract useful information. There are different types of data including categorical/qualitative data, which represents characteristics like gender, and numerical/quantitative data, which can be discrete like coin flips or continuous like measurements. Common data structures used to organize and store data include arrays, linked lists, stacks, queues, trees and graphs. Efficient searching of data structures is important and can be done using methods like linear search, which sequentially checks each element, and binary search, which can more quickly find elements in a sorted data set.
The document provides an overview of data structures and algorithms, emphasizing the classification of data structures into primitive and non-primitive types, with further details on linear and non-linear structures. It explains various implementations such as arrays, linked lists, stacks, and queues, including their operations like push, pop, enqueue, and dequeue, while highlighting their practical applications. The text also covers concepts like Abstract Data Types (ADT) and specific implementations, illustrating the significance of data organization and retrieval methods in programming.
A singly linked list is a linear data structuresangeethavinoth
The document presents information on Abstract Data Types (ADT), specifically focusing on lists and their operations such as insertion, deletion, searching, and updating. It discusses static and dynamic data structures, emphasizing the use of arrays as a form of static list. The document includes examples and syntax for array declaration and manipulation.
Data warehouses, lakes, lakehouses, streams, fabrics, hubs, vaults, and meshes. We sometimes choose deliberately, sometimes influenced by trends, yet often get an organic blend. But the choices have orders of magnitude in impact on operations cost and iteration speed. Let's dissect the paradigms and their operational aspects once and for all.
Prescriptive Process Monitoring Under Uncertainty and Resource Constraints: A...Mahmoud Shoush
We introduced Black-Box Prescriptive Process Monitoring (BB-PrPM) – a reinforcement learning approach that learns when, whether, and how to intervene in business processes to boost performance under real-world constraints.
This work is presented at the International Conference on Advanced Information Systems Engineering CAiSE Conference #CAiSE2025
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2. What is Data Structure?
•A construct that can be defined within
a programming language to store a
collection of data
- one may store some data in an array of
integers, an array of objects, or an array
of arrays
3. Abstract Data Type (ADT)
•Definition: a collection of data together with
a set of operations on that data
- specifications indicate what ADT operations
do, but not how to implement them
- data structures are part of an ADT’s
implementation
•Programmer can use an ADT without
knowing its implementation.
4. Typical Operations on Data
•Add data to a data collection
•Remove data from a data collection
•Ask questions about the data in a data
collection. E.g., what is the value at a
particular location, and is x in the
collection?
5. Why we need ADT?
•Hide the unnecessary details
•Help manage software complexity
•Easier software maintenance
•Functionalities are less likely to
change
•Localised rather than global changes
8. Definition and operations of List
• List: a finite sequence of data items
a1, a2, a3, …, an
• List is very general in computing
- e.g. class list, list of characters, list of events
• Typical operations have:
- Creation
- Insert / remove an element
- Test for emptiness
- Find an item/element
- Current element / next / previous
- Find k-th element
- Print the entire list
9. Array-Based List Implementation
• One simple implementation is to use arrays
• A sequence of n-elements
• Maximum size should be pre-set based on prior knowledge.
• Internal variables:
• Maximum size maxSize (m)
• Current size curSize (n)
• Current index cur
• Array of elements listArray
n
curSize
a1 a2 a3 an
listArray
unused
0 1 2 n-1 m
cur
10. Inserting Into an Array
• While retrieval is very fast, insertion and deletion are very
slow
• Insert has to shift upwards to create gap
a1 a2 a7 a8
a4 a5 a6
a3
Step 1 : Shift upwards
8
Size arr
8 a1 a2 a3 a7 a8
Size arr
a4 a5 a6
Example : insert(2, it, arr)
Step 2 : Write into gap
it
Step 3 : Update Size
9
11. Deleting from an Array
• Delete has to shift downwards to close gap of deleted item
Step 1 : Close Gap
9 a1 a2 it a7
a8
size
a5 a6
a3
a8
arr
9 a1 a2 it a7 a8
size
a4 a5 a6
a3
arr
Example: deleteItem(4, arr)
Step 2 : Update Size
8
Not part of list
12. Linked List Approach
• Main problem of array is the slow deletion/insertion since it
has to shift items in its contiguous memory
• Solution: linked list where items need not be contiguous with
nodes of the form
• Sequence (list) of four items < a1,a2 ,a3 ,a4 > can be
represented by:
item next
ai
a1 a2 a3 a4
head represents
null