This document discusses the features of object-oriented programming, including objects, classes, encapsulation, abstraction, polymorphism, and inheritance. It provides examples and definitions for each concept. Objects have identity, state, and behavior. Classes provide blueprints for objects and define their attributes and methods. Encapsulation binds data and methods together, and hides implementation details. Abstraction involves hiding details and showing functionality. Polymorphism allows the same method to operate in different ways depending on the object, like calculating area for different shapes. Inheritance allows classes to share structure and behavior with parent classes.
This document discusses techniques for refining domain models, including:
- Adding association classes to model relationships between concepts
- Modeling whole-part relationships using aggregation
- Representing time intervals to capture historical and planned attribute values
- Organizing domain model elements using packages and showing dependencies between packages
The document describes the waterfall model of software development. It begins by listing the presenters and defining sequential and incremental software development models. It then discusses the waterfall model in more detail, describing it as a linear sequential process where each phase must be completed before the next begins. The document outlines the history, use cases, diagram, phases and advantages/disadvantages of the waterfall model.
Formal Specification in Software Engineering SE9koolkampus
This document discusses formal specification techniques for software. It describes algebraic techniques for specifying interfaces as abstract data types and model-based techniques for specifying system behavior. Algebraic specifications define operations and their relationships, while model-based specifications represent the system state using mathematical constructs like sets and sequences. Formal specification finds errors earlier and reduces rework, though it requires more upfront effort. The document also provides an example of formally specifying an air traffic control system and insulin pump.
The document describes an employee management system that was developed to simplify maintaining records for employees in a company. It maintains personal and official details of employees, including salary calculation, attendance tracking, and various leave categories. The system aims to overcome issues with the previous manual paper-based system by providing a computerized database, faster searching and updating of records, and generation of reports for management. It includes modules for administration, employee access, and functionality for attendance, leave, salary processing, and more.
This document summarizes a project titled "Placement Management System" submitted by Mehul Ranavasiya and Devashish Vaghela towards fulfilling requirements for a Bachelor of Technology degree. The project was developed under the guidance of Dr. Madhuri Bhavsar and aims to develop a web-based system for managing student and company information related to training and placement activities. The document includes sections on introduction, system analysis, design, testing, future enhancements, and bibliography.
The document discusses translating statements from English to propositional logic, including:
- Conjunction and disjunction are commutative but order matters for statements with mixed operators
- How to translate conditional statements like "if P then Q" and biconditionals like "P if and only if Q"
- Necessary and sufficient conditions and how they relate to conditionals
- Examples of translating various English language statements into propositional logic statements
This document discusses the features of object-oriented programming, including objects, classes, encapsulation, abstraction, polymorphism, and inheritance. It provides examples and definitions for each concept. Objects have identity, state, and behavior. Classes provide blueprints for objects and define their attributes and methods. Encapsulation binds data and methods together, and hides implementation details. Abstraction involves hiding details and showing functionality. Polymorphism allows the same method to operate in different ways depending on the object, like calculating area for different shapes. Inheritance allows classes to share structure and behavior with parent classes.
This document discusses techniques for refining domain models, including:
- Adding association classes to model relationships between concepts
- Modeling whole-part relationships using aggregation
- Representing time intervals to capture historical and planned attribute values
- Organizing domain model elements using packages and showing dependencies between packages
The document describes the waterfall model of software development. It begins by listing the presenters and defining sequential and incremental software development models. It then discusses the waterfall model in more detail, describing it as a linear sequential process where each phase must be completed before the next begins. The document outlines the history, use cases, diagram, phases and advantages/disadvantages of the waterfall model.
Formal Specification in Software Engineering SE9koolkampus
This document discusses formal specification techniques for software. It describes algebraic techniques for specifying interfaces as abstract data types and model-based techniques for specifying system behavior. Algebraic specifications define operations and their relationships, while model-based specifications represent the system state using mathematical constructs like sets and sequences. Formal specification finds errors earlier and reduces rework, though it requires more upfront effort. The document also provides an example of formally specifying an air traffic control system and insulin pump.
The document describes an employee management system that was developed to simplify maintaining records for employees in a company. It maintains personal and official details of employees, including salary calculation, attendance tracking, and various leave categories. The system aims to overcome issues with the previous manual paper-based system by providing a computerized database, faster searching and updating of records, and generation of reports for management. It includes modules for administration, employee access, and functionality for attendance, leave, salary processing, and more.
This document summarizes a project titled "Placement Management System" submitted by Mehul Ranavasiya and Devashish Vaghela towards fulfilling requirements for a Bachelor of Technology degree. The project was developed under the guidance of Dr. Madhuri Bhavsar and aims to develop a web-based system for managing student and company information related to training and placement activities. The document includes sections on introduction, system analysis, design, testing, future enhancements, and bibliography.
The document discusses translating statements from English to propositional logic, including:
- Conjunction and disjunction are commutative but order matters for statements with mixed operators
- How to translate conditional statements like "if P then Q" and biconditionals like "P if and only if Q"
- Necessary and sufficient conditions and how they relate to conditionals
- Examples of translating various English language statements into propositional logic statements
The document discusses data persistency and different methods for achieving it. It defines persistence as the ability of data to outlive the execution of the program that created it. Common ways to achieve persistence include saving data in files or using cookies and sessions with PHP to store data across HTTP requests since HTTP is a stateless protocol. The document also distinguishes between persistent data, which is infrequently accessed and not likely to be modified, and dynamic data which is asynchronously updated.
The Unified Process (UP) is a popular iterative software development framework that uses use cases, architecture-centric design, and the Unified Modeling Language. It originated from Jacobson's Objectory process in the 1980s and was further developed by Rational Software into the Rational Unified Process. The UP consists of four phases - inception, elaboration, construction, and transition - and emphasizes iterative development, architectural drivers, and risk-managed delivery.
The document discusses key concepts in object-oriented programming including objects, classes, encapsulation, abstraction, polymorphism, and inheritance. It provides definitions and examples of each concept. For objects, it describes how objects have an identity, state, and behavior. For classes, it explains that a class is a blueprint that defines common properties and behaviors for a collection of objects.
The document discusses virtual memory, including its needs, importance, advantages, and disadvantages. Virtual memory allows a computer to use more memory for programs than is physically installed by storing unused portions on disk. This allows processes to exceed physical memory limits. Page replacement algorithms like FIFO, LRU, and OPT are used to determine which pages to swap in and out between memory and disk.
Course file for theory of computation dt 08 08-2016.sumit jain
The document provides details of the course plan for Theory of Computation at Acropolis Technical Campus in Indore, India. It lists the course code, semester, tutors, and course overview. The course aims to cover finite automata, pushdown automata, context-free grammars, and Turing machines. It outlines 6 course learning objectives and 6 course outcomes. It also maps the course outcomes to program outcomes and program specific outcomes. The document provides information on topic delivery, time schedules, books, syllabus, and lab work objectives.
Visual Basic is an object-oriented programming language that supports object-oriented programming features like abstraction, encapsulation, polymorphism, and inheritance. It emphasizes objects and classes, with a program divided into objects that communicate through functions. Objects are instances of classes that contain data members and methods. Classes group similar objects and methods become class functions.
This document discusses algorithms and their analysis. It defines an algorithm as a step-by-step procedure to solve a problem or calculate a quantity. Algorithm analysis involves evaluating memory usage and time complexity. Asymptotics, such as Big-O notation, are used to formalize the growth rates of algorithms. Common sorting algorithms like insertion sort and quicksort are analyzed using recurrence relations to determine their time complexities as O(n^2) and O(nlogn), respectively.
This document contains two sample question papers for an Operating Systems exam for a 4th semester BTech course in IT/CSE. Each paper has three sections - Section A contains 10 short answer questions worth 2 marks each, Section B contains 4 long answer questions worth 5 marks each, and Section C contains 2 long answer questions worth 10 marks each. The questions cover topics like virtual memory, processes, threads, CPU scheduling algorithms, deadlocks, memory management techniques like paging, segmentation, swapping etc.
Here are the key elements of a use case diagram:
- Actor: Represents a role that interacts with the system. Examples include employee, manager etc.
- Use case: Represents a discrete unit of functionality that provides value to an actor. Examples include add employee, generate payroll etc.
- Association: Connects an actor to a use case to show that the actor can interact with that use case.
Notations:
- Actor: Stick figure
- Use case: Oval
- Association: Solid line
- System boundary: Rectangle
5.2 Sequence Diagrams:
Sequence diagrams are interaction diagrams that detail how operations are carried out — what messages are sent and when. They are
Given two integer arrays val[0...n-1] and wt[0...n-1] that represents values and weights associated with n items respectively. Find out the maximum value subset of val[] such that sum of the weights of this subset is smaller than or equal to knapsack capacity W. Here the BRANCH AND BOUND ALGORITHM is discussed .
Parallel computing is the simultaneous use of multiple compute resources to solve a computational problem faster. It allows for larger problems to be solved and provides cost savings over serial computing. There are different models of parallelism including data parallelism and task parallelism. Flynn's taxonomy categorizes computer architectures as SISD, SIMD, MISD and MIMD based on how instructions and data are handled. Shared memory and distributed memory are two common architectures that differ in scalability and communication handling. Programming models include shared memory, message passing and data parallel approaches. Design considerations for parallel programs include partitioning work, communication between processes, and synchronization.
Prototyping involves rapidly developing an initial version of a system to validate requirements and gain user feedback. There are two main approaches - evolutionary prototyping iteratively develops prototypes into the final system, while throw-away prototyping discards the prototype after validating requirements. Rapid prototyping techniques include using high-level languages, database programming, and component reuse to quickly develop initial versions. User interface prototyping is also important to get early user input on look and feel.
[Question Paper] ASP.NET With C# (75:25 Pattern) [April / 2016]Mumbai B.Sc.IT Study
This is a Question Papers of Mumbai University for B.Sc.IT Student of Semester - V [ASP.NET With C#] (75:25 Pattern). [Year - April / 2016] . . . Solution Set of this Paper is Coming soon . . .
mathematical notations and functions, algorithmic notations, control structures, complexity of algorithms, other asymptotic notations for complexity of algorithms, subalgorithms, variables, data types.
Attendance management system project report.Manoj Kumar
Attendance management system project report is a document in PDF file. If you have any confusion in your document then you can clear your concepts here.
In the given presentation, process overview,process management scheduling typesand some more basic concepts were explained.
Kindly refere the presentation.
This document discusses graph data structures and algorithms. A graph consists of nodes and edges, where nodes represent entities and edges represent relationships between nodes. There are different types of graphs including undirected, directed, weighted, and cyclic graphs. Graphs can be represented using an adjacency matrix or adjacency list. Graphs are used to model real-world networks and solve problems in areas like social networks, maps, robot path planning, and neural networks.
This document discusses different data structures and algorithms. It provides examples of common data structures like arrays, linked lists, stacks, queues, trees, and graphs. It describes what each data structure is, how it stores and organizes data, and examples of its applications. It also discusses abstract data types, algorithms, and how to analyze the time and space complexity of algorithms.
The document describes a virtual education system project submitted by Dhara Gorsiya. It includes an introduction describing the system's objectives to provide online learning and remove barriers like geographical constraints. It outlines the system's users - administrators, faculty and students. The analysis section describes problems with the current in-person education system like travel costs and occupied classrooms. The proposed virtual system aims to allow learning from anywhere at low cost, enable real-time student-faculty interaction and provide free learning environment. The document covers technologies used, project management, system modeling diagrams and data modeling for the virtual education system.
The document discusses primary keys and foreign keys in entity relationship diagrams (ERDs). It defines a primary key as a unique identifier for each instance of an entity. A foreign key completes a relationship by identifying the parent entity and maintains referential integrity between entities. The document then provides an example of designing an ERD for a college, identifying the entities, relationships, keys, and other attributes to draw the complete diagram.
This document discusses entity relationship diagrams and how to create them. It defines the different types of cardinal relationships as one-to-one, one-to-many, many-to-one, and many-to-many. It provides examples of each type of relationship. The document then outlines the steps to create an ER diagram, including identifying entities, relationships, cardinality, and attributes. It provides an example of an ER diagram for a university with students, courses, and professors.
The document discusses data persistency and different methods for achieving it. It defines persistence as the ability of data to outlive the execution of the program that created it. Common ways to achieve persistence include saving data in files or using cookies and sessions with PHP to store data across HTTP requests since HTTP is a stateless protocol. The document also distinguishes between persistent data, which is infrequently accessed and not likely to be modified, and dynamic data which is asynchronously updated.
The Unified Process (UP) is a popular iterative software development framework that uses use cases, architecture-centric design, and the Unified Modeling Language. It originated from Jacobson's Objectory process in the 1980s and was further developed by Rational Software into the Rational Unified Process. The UP consists of four phases - inception, elaboration, construction, and transition - and emphasizes iterative development, architectural drivers, and risk-managed delivery.
The document discusses key concepts in object-oriented programming including objects, classes, encapsulation, abstraction, polymorphism, and inheritance. It provides definitions and examples of each concept. For objects, it describes how objects have an identity, state, and behavior. For classes, it explains that a class is a blueprint that defines common properties and behaviors for a collection of objects.
The document discusses virtual memory, including its needs, importance, advantages, and disadvantages. Virtual memory allows a computer to use more memory for programs than is physically installed by storing unused portions on disk. This allows processes to exceed physical memory limits. Page replacement algorithms like FIFO, LRU, and OPT are used to determine which pages to swap in and out between memory and disk.
Course file for theory of computation dt 08 08-2016.sumit jain
The document provides details of the course plan for Theory of Computation at Acropolis Technical Campus in Indore, India. It lists the course code, semester, tutors, and course overview. The course aims to cover finite automata, pushdown automata, context-free grammars, and Turing machines. It outlines 6 course learning objectives and 6 course outcomes. It also maps the course outcomes to program outcomes and program specific outcomes. The document provides information on topic delivery, time schedules, books, syllabus, and lab work objectives.
Visual Basic is an object-oriented programming language that supports object-oriented programming features like abstraction, encapsulation, polymorphism, and inheritance. It emphasizes objects and classes, with a program divided into objects that communicate through functions. Objects are instances of classes that contain data members and methods. Classes group similar objects and methods become class functions.
This document discusses algorithms and their analysis. It defines an algorithm as a step-by-step procedure to solve a problem or calculate a quantity. Algorithm analysis involves evaluating memory usage and time complexity. Asymptotics, such as Big-O notation, are used to formalize the growth rates of algorithms. Common sorting algorithms like insertion sort and quicksort are analyzed using recurrence relations to determine their time complexities as O(n^2) and O(nlogn), respectively.
This document contains two sample question papers for an Operating Systems exam for a 4th semester BTech course in IT/CSE. Each paper has three sections - Section A contains 10 short answer questions worth 2 marks each, Section B contains 4 long answer questions worth 5 marks each, and Section C contains 2 long answer questions worth 10 marks each. The questions cover topics like virtual memory, processes, threads, CPU scheduling algorithms, deadlocks, memory management techniques like paging, segmentation, swapping etc.
Here are the key elements of a use case diagram:
- Actor: Represents a role that interacts with the system. Examples include employee, manager etc.
- Use case: Represents a discrete unit of functionality that provides value to an actor. Examples include add employee, generate payroll etc.
- Association: Connects an actor to a use case to show that the actor can interact with that use case.
Notations:
- Actor: Stick figure
- Use case: Oval
- Association: Solid line
- System boundary: Rectangle
5.2 Sequence Diagrams:
Sequence diagrams are interaction diagrams that detail how operations are carried out — what messages are sent and when. They are
Given two integer arrays val[0...n-1] and wt[0...n-1] that represents values and weights associated with n items respectively. Find out the maximum value subset of val[] such that sum of the weights of this subset is smaller than or equal to knapsack capacity W. Here the BRANCH AND BOUND ALGORITHM is discussed .
Parallel computing is the simultaneous use of multiple compute resources to solve a computational problem faster. It allows for larger problems to be solved and provides cost savings over serial computing. There are different models of parallelism including data parallelism and task parallelism. Flynn's taxonomy categorizes computer architectures as SISD, SIMD, MISD and MIMD based on how instructions and data are handled. Shared memory and distributed memory are two common architectures that differ in scalability and communication handling. Programming models include shared memory, message passing and data parallel approaches. Design considerations for parallel programs include partitioning work, communication between processes, and synchronization.
Prototyping involves rapidly developing an initial version of a system to validate requirements and gain user feedback. There are two main approaches - evolutionary prototyping iteratively develops prototypes into the final system, while throw-away prototyping discards the prototype after validating requirements. Rapid prototyping techniques include using high-level languages, database programming, and component reuse to quickly develop initial versions. User interface prototyping is also important to get early user input on look and feel.
[Question Paper] ASP.NET With C# (75:25 Pattern) [April / 2016]Mumbai B.Sc.IT Study
This is a Question Papers of Mumbai University for B.Sc.IT Student of Semester - V [ASP.NET With C#] (75:25 Pattern). [Year - April / 2016] . . . Solution Set of this Paper is Coming soon . . .
mathematical notations and functions, algorithmic notations, control structures, complexity of algorithms, other asymptotic notations for complexity of algorithms, subalgorithms, variables, data types.
Attendance management system project report.Manoj Kumar
Attendance management system project report is a document in PDF file. If you have any confusion in your document then you can clear your concepts here.
In the given presentation, process overview,process management scheduling typesand some more basic concepts were explained.
Kindly refere the presentation.
This document discusses graph data structures and algorithms. A graph consists of nodes and edges, where nodes represent entities and edges represent relationships between nodes. There are different types of graphs including undirected, directed, weighted, and cyclic graphs. Graphs can be represented using an adjacency matrix or adjacency list. Graphs are used to model real-world networks and solve problems in areas like social networks, maps, robot path planning, and neural networks.
This document discusses different data structures and algorithms. It provides examples of common data structures like arrays, linked lists, stacks, queues, trees, and graphs. It describes what each data structure is, how it stores and organizes data, and examples of its applications. It also discusses abstract data types, algorithms, and how to analyze the time and space complexity of algorithms.
The document describes a virtual education system project submitted by Dhara Gorsiya. It includes an introduction describing the system's objectives to provide online learning and remove barriers like geographical constraints. It outlines the system's users - administrators, faculty and students. The analysis section describes problems with the current in-person education system like travel costs and occupied classrooms. The proposed virtual system aims to allow learning from anywhere at low cost, enable real-time student-faculty interaction and provide free learning environment. The document covers technologies used, project management, system modeling diagrams and data modeling for the virtual education system.
The document discusses primary keys and foreign keys in entity relationship diagrams (ERDs). It defines a primary key as a unique identifier for each instance of an entity. A foreign key completes a relationship by identifying the parent entity and maintains referential integrity between entities. The document then provides an example of designing an ERD for a college, identifying the entities, relationships, keys, and other attributes to draw the complete diagram.
This document discusses entity relationship diagrams and how to create them. It defines the different types of cardinal relationships as one-to-one, one-to-many, many-to-one, and many-to-many. It provides examples of each type of relationship. The document then outlines the steps to create an ER diagram, including identifying entities, relationships, cardinality, and attributes. It provides an example of an ER diagram for a university with students, courses, and professors.
This document outlines the design of an entity relationship diagram for a college database. It identifies the key entities as departments, sections, courses, instructors, and students. It describes the relationships between these entities, such as departments having sections and courses, instructors teaching courses, and students enrolling in courses. It then represents these relationships in an entity relationship diagram with identifying cardinalities like one-to-many and many-to-many.
1. The document describes designing an entity relationship diagram for a college database.
2. The entities include departments, sections, courses, instructors, and students. Relationships between the entities like departments having sections and courses, instructors teaching courses, and students enrolling in courses are also described.
3. A 4-step process is outlined to construct the ER diagram, which involves identifying entities and relationships, assigning cardinalities between relationships, and listing attributes for each entity.
This document outlines the design of an entity relationship diagram for a college database. It identifies the key entities as departments, sections, courses, instructors, and students. It describes the relationships between these entities, such as departments having sections and courses, instructors teaching courses, and students enrolling in courses. It then represents these relationships in an entity relationship diagram with identifying cardinalities like one-to-many and many-to-many.
The document discusses entity relationship (ER) diagrams, which are used to design databases. It provides details on the major components of ER diagrams, including entities, relationships, attributes, keys, and cardinality. As an example, it presents an ER diagram for a college database showing students enrolled in subjects taught by instructors using both Chen's notation and Crow's foot notation. The diagram models the one-to-many relationships between students and subjects and instructors and subjects.
Csc1100 elements of programming (revised july 2014) 120lh-2-studentIIUM
This document outlines a course on Elements of Programming offered at the International Islamic University Malaysia. The 3-credit, semester-long course introduces students to structured and object-oriented programming principles using C++. It aims to provide students with programming skills and the ability to apply structured principles to problem solving. Assessment methods include quizzes, assignments, group projects, midterm and final exams. Topics covered include data types, control structures, functions, arrays, pointers, structures and file I/O. The course maps to several of the program learning outcomes, including demonstrating programming principles, applying algorithms, and understanding Islamic ethics in application development.
The document provides information about fully solved assignments for the winter 2013 semester in the BCA program. It lists the subject code and name as BCA2030 - Object Oriented Programming - C++. It provides 6 questions related to the subject and asks students to send their semester and specialization details to the provided email ID or call the given phone number to get the solved assignments. It provides answers to the 6 questions related to topics like objects and classes, friend functions, constructors vs destructors, operator overloading, virtual functions and polymorphism, and exception handling models.
The summary highlights that the document discusses getting fully solved winter 2013 semester assignments for the BCA program's subject on Object Oriented Programming - C
The document describes a lesson plan for teaching students about decoders. It includes:
1) Details about the class such as the number of students, their location, and the classroom.
2) An overview of the lesson which discusses decoders, number systems, logic gates, and behavioral goals for students to understand digital systems.
3) The lesson plan outlines the objectives, methodology, and activities which include lectures, classroom discussions, individual exercises, and a group practical work session.
The document describes the iterative process of developing an entity relationship diagram (ERD) for Tiny College. It provides 10 business rules obtained from interviews with college administrators. For each rule, it illustrates the relevant entities, attributes, and relationships in segments of the ERD. The ERD captures the entities of School, Department, Professor, Course, Class, Student, Building, Room, and Enroll (an associative entity). The relationships defined include operates, has, employs, offers, generates, is dean of, chairs, teaches, advises, enrolls in, contains, and is used for.
The steps are:
1. Find the module entity instance for "Database Systems"
2. Find the enrollment entity instances that match this module
3. For each matching enrollment, retrieve the associated student
This document provides an overview of entity-relationship modeling as a first step for designing a relational database. It describes how to model entities, attributes, relationships, and participation constraints. Key aspects covered include using boxes to represent entity types, diamonds for relationship types, and labeling relationships with degrees. The document also discusses handling multi-valued attributes and deciding whether to model concepts as attributes or entity types.
This lesson plan focuses on teaching trainees about magnitude comparators. The trainees will learn about the inputs, outputs, and truth tables of comparators. They will also learn how to design magnitude comparators with multiple bits, and identify the most and least significant bits. The lesson will use various teaching methods, including lecture, classroom discussion, individual work, partner work and group work. The objectives are for trainees to understand what comparators are, explain truth tables, differentiate between 4-bit and 8-bit comparators, and design an 8-bit comparator on the whiteboard.
lecture 8 Data Modeling Using the Entity-Relationship Model (3).pptxFarahAmoun
This document discusses data modeling using the entity-relationship model. It covers relationship types (unary, binary, ternary), examples of relationships, and constraints on relationships including cardinality ratio, participation, and multiplicity. Cardinality ratios include one-to-one, one-to-many, many-to-one, and many-to-many. Participation can be mandatory or optional. Multiplicity specifies the minimum and maximum number of entities that can be related.
This lesson plan covers a 50 minute lesson on binary systems for 12 trainees. The trainer will begin by motivating the trainees with questions about binary systems. The lesson will then explain how to read, write, and convert binary and decimal numbers through lectures, examples, exercises, and group work. Trainees will learn the benefits of binary systems and practice discriminating and converting between binary and decimal numbers. The lesson will conclude by having trainees work in groups to answer questions on a worksheet and reflecting on what they have learned.
This lesson plan covers a 50 minute lesson on binary systems for 12 trainees. The trainer will begin by motivating the trainees with questions about binary systems. The trainer will then explain how to read, write, and convert binary numbers, providing examples and exercises. Trainees will practice converting between binary and decimal both individually and in groups. To close, the trainer will have trainees work in groups on a handout, review answers, and take any final questions from the trainees.
This document provides information on the Teaching Syllabus for Information and Communications Technology (ICT) as an elective course for Senior High School students in Ghana. The syllabus is designed to provide advanced ICT skills to prepare students for further study and careers in ICT. It covers 12 themes over three years of study, including hardware, software, networking, programming, and educational technology. The syllabus outlines general aims, scope of content, time allocation, and provides details on course structure and organization for each year of study.
Telecommunications networks like the Internet, intranets, and extranets have become essential to the successful operations of all types of organizations and their computer-based information systems
An entity relationship diagram (ERD) shows the relationships of entity sets stored in a database. An entity in this context is a component of data. In other words,
An activity diagram visually presents a series of actions or flow of control in a system similar to a flowchart or a data flow diagram. They can also describe the steps in a use case diagram.
Data flow diagrams (DFDs) provide a graphical representation of how data moves through a system. DFDs use four main symbols: processes, data stores, external entities, and data flows. They allow system analysts and users to depict and understand the flow of data in a system. DFDs come in two main types: context diagrams provide an overview of the system and its interactions, while level 0 DFDs show more detail about the system's major sub-processes, data stores, and flows at a high level. Together, DFDs enable customers and users to specify requirements by modeling the system's data flows.
Information systems analysis and requirements analysis produces a requirements specification. This specification states the project goal and the related data storage, data movement
The system development life cycle (SDLC) is a conceptual model used in project management that describes the stages involved in an information system development project, from an initial feasibility study, through maintenance of the complete application.
The document is an introduction to system analysis and design (SAD) provided by Dr. Mohammed Kassim. It defines a system as a combination of interrelated components working together to accomplish a task. An information system is defined as a technologically implemented medium for recording, storing, and disseminating information to support decision making. The key components of an information system are identified as people, hardware, software, data, and networks. People resources include end users and information systems specialists. Hardware resources include computers and peripheral devices. Software resources include system software, application software, and procedures. Data resources include raw data stored in databases.
This document provides an introduction to the Python programming language. It discusses that Python is an interpreted, interactive, object-oriented scripting language that is designed to be highly readable. The document outlines Python's history and key features, including being easy to learn and use, having a broad standard library, and being portable. It also discusses popular implementations of Python like CPython and how organizations like Google, Yahoo, and NASA use Python for applications such as bioinformatics, simulations, games, and networking.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Example for ER diagram part11
1. Introdaction to Python
Dr. Mohammed Kassim Page 46
Example for ER diagram
Example: design as (Figures and Tables) Entity Relationship diagram for a college?
We have the following statements:
1. A college contains many departments
2. Each department can offer any number of courses
3. Many instructors can work in a department
4. An instructor can work only in one department
5. For each department there is a Head
6. Each instructor can take any number of courses
7. A course can be taken by only one instructor
8. A student can enroll for any number of courses
9. Each course can have any number of students
Step 1: Identify the Entities
What are the entities here?
1. Department
2. Course
3. Instructor
4. Student
Stem 2: Identify the relationships
1. One department offers many courses. But one particular course can be
offered by only one department. hence the cardinality between department
and course is One to Many (1:M)
2. Introdaction to Python
Dr. Mohammed Kassim Page 47
Example for ER diagram
2. One department has multiple instructors . But instructor belongs to only one
department. Hence the cardinality between department and instructor is One
to Many (1:M)
3. One course can be enrolled by many students and one student can enroll for
many courses. Hence the cardinality between course and student is Many to
Many (M:M)
4. One course is taught by only one instructor. But one instructor teaches many
courses. Hence the cardinality between course and instructor is Many to One
(M :1)
Step 3: Identify the key attributes
"Departmen_Name" can identify a department uniquely.
Course_ID is the key attribute for "Course" Entity.
Student_ID is the key attribute for "Student" Entity.
Instructor_ID is the key attribute for "Instructor" Entity.
Step 4: Identify other relevant attributes
For the department entity, other attributes are location
For course entity, other attributes are course_name,duration
For instructor entity, other attributes are first_name, last_name, phone
For student entity, first_name, last_name, phone
Step 5: Draw complete ER diagram
By connecting all these details, we can now draw ER diagram as given below.
3. Introdaction to Python
Dr. Mohammed Kassim Page 48
Example for ER diagram
M
1
1
1
M
M
Department
* Departmen_Name
location
Course
* Course_ID
* Departmen_Name
* Instructor_ID
course_name
duration
Instructor
* Instructor_ID
* Departmen_Name
first_name
last_name
phone
Student
* Student_ID
* Course_ID
first_name
last_name
phone
Entity Relationship (ER) model for a college
M
M
M
M
M
M
ERD as Tables for College