KAOS, is a goal-oriented software requirements capturing approach in requirements engineering. It is a specific Goal modeling method; another is i*. It allows for requirements to be calculated from goal diagrams.[1] KAOS stands for Knowledge Acquisition in automated specification or Keep All Objectives Satisfied.
The University of Oregon and the University of Louvain (Belgium) designed the KAOS methodology in 1990 by Axel van Lamsweerde and others. It is now widely taught worldwide at the university level for capturing software requirements.
Black box testing refers to testing software without knowledge of its internal implementation by focusing on inputs and outputs. There are several techniques including boundary value analysis, equivalence partitioning, state transition testing, and graph-based testing. Black box testing is useful for testing functionality, behavior, and non-functional aspects from the end user's perspective.
This document provides an overview of software testing concepts and processes. It discusses the importance of testing in the software development lifecycle and defines key terms like errors, bugs, faults, and failures. It also describes different types of testing like unit testing, integration testing, system testing, and acceptance testing. Finally, it covers quality assurance and quality control processes and how bugs are managed throughout their lifecycle.
This document provides an overview of software testing concepts and definitions. It discusses key topics such as software quality, testing methods like static and dynamic testing, testing levels from unit to acceptance testing, and testing types including functional, non-functional, regression and security testing. The document is intended as an introduction to software testing principles and terminology.
Requirements analysis, also called requirements engineering, is the process of determining user expectations for a new or modified product. These features, called requirements, must be quantifiable, relevant and detailed. In software engineering, such requirements are often called functional specifications. Requirements analysis is an important aspect of project management.
Acceptance testing is formal testing conducted by clients or end users to determine if a system meets business needs and requirements. There are two main types: user acceptance testing (UAT) ensures the system satisfies contractual criteria before being approved, while business acceptance testing (BAT) is conducted by the supplier's development team to ensure the system will pass acceptance. Acceptance testing has the objectives of confirming the system criteria and identifying any discrepancies.
Software testing is an investigation conducted to provide stakeholders with information about the quality of the product or service under test. I hope this ppt will help u to learn about software testing.
This ppt covers the following
A strategic approach to testing
Test strategies for conventional software
Test strategies for object-oriented software
Validation testing
System testing
The art of debugging
Black box testing refers to testing software without knowledge of its internal implementation by focusing on inputs and outputs. There are several techniques including boundary value analysis, equivalence partitioning, state transition testing, and graph-based testing. Black box testing is useful for testing functionality, behavior, and non-functional aspects from the end user's perspective.
This document provides an overview of software testing concepts and processes. It discusses the importance of testing in the software development lifecycle and defines key terms like errors, bugs, faults, and failures. It also describes different types of testing like unit testing, integration testing, system testing, and acceptance testing. Finally, it covers quality assurance and quality control processes and how bugs are managed throughout their lifecycle.
This document provides an overview of software testing concepts and definitions. It discusses key topics such as software quality, testing methods like static and dynamic testing, testing levels from unit to acceptance testing, and testing types including functional, non-functional, regression and security testing. The document is intended as an introduction to software testing principles and terminology.
Requirements analysis, also called requirements engineering, is the process of determining user expectations for a new or modified product. These features, called requirements, must be quantifiable, relevant and detailed. In software engineering, such requirements are often called functional specifications. Requirements analysis is an important aspect of project management.
Acceptance testing is formal testing conducted by clients or end users to determine if a system meets business needs and requirements. There are two main types: user acceptance testing (UAT) ensures the system satisfies contractual criteria before being approved, while business acceptance testing (BAT) is conducted by the supplier's development team to ensure the system will pass acceptance. Acceptance testing has the objectives of confirming the system criteria and identifying any discrepancies.
Software testing is an investigation conducted to provide stakeholders with information about the quality of the product or service under test. I hope this ppt will help u to learn about software testing.
This ppt covers the following
A strategic approach to testing
Test strategies for conventional software
Test strategies for object-oriented software
Validation testing
System testing
The art of debugging
Java is a relatively high level language. It offers several ready-to-use resources, which facilitates learning for today's developers and focuses on the actual implementation of the business, instead of worrying about the management of the infrastructure at the system level.
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
YouTube channel : https://www.youtube.com/c/prelrik
This course of slides are very useful for beginners or less experienced testers. The course focuses to teach how actually testers work in LIVE environment.
The document discusses requirements elicitation techniques. It describes requirements elicitation as identifying the needs of users and stakeholders to communicate to developers. Effective techniques include interviews, requirements workshops, brainstorming, storyboards, use cases, role playing and prototyping. Requirements elicitation faces problems of scope, understanding, and volatility. Scope issues include unclear boundaries and unnecessary design data. Understanding challenges involve incomplete user needs, communication gaps between users and analysts, and differing views. Requirements also tend to change over time.
Software quality program and establishiment coceptsGuruKrishnaTeja
This document outlines the key concepts and objectives of a Software Quality Program (SQP). The SQP establishes quality requirements, defines development and maintenance processes, and uses metrics to measure productivity, quality, and documentation. It plans evaluations of software and development processes. Responsibility for the SQP is assigned and its procedures, tools, and records are documented. The SQP scope identifies deliverables and ensures the desired quality is achieved. It defines referenced documents, procedures, tools, records, and establishes tasks like data collection and quality planning to develop high quality software.
The document discusses software quality and defines key aspects:
- It explains the importance of software quality for users and developers.
- Qualities like correctness, reliability, efficiency are defined.
- Methods for measuring qualities like ISO 9126 standard are presented.
- Quality is important throughout the software development process.
- Both product quality and process quality need to be managed.
The document discusses different types of software metrics that can be used to measure various aspects of software development. Process metrics measure attributes of the development process, while product metrics measure attributes of the software product. Project metrics are used to monitor and control software projects. Metrics need to be normalized to allow for comparison between different projects or teams. This can be done using size-oriented metrics that relate measures to the size of the software, or function-oriented metrics that relate measures to the functionality delivered.
SQA activities involve formulating quality plans, applying software engineering techniques, conducting reviews, implementing multi-tiered testing, enforcing process adherence, controlling changes, measuring change impact, performing audits, and keeping records. The key goals are to evaluate software quality, monitor adherence to standards and procedures throughout the development lifecycle, and ensure quality is maintained.
This document discusses software project management artifacts. Artifacts are organized into management and engineering sets. The management set includes artifacts like the work breakdown structure, business case, and software development plan. The engineering set includes requirement, design, implementation, and deployment artifact sets. Each set captures information through various notations and tools to manage the software development lifecycle.
This document discusses the requirement analysis and software development methodology selection for developing a ticketing system called the Snow City System. It analyzes the requirements of the system, which include scanning tickets, calculating charges based on time spent, notifying customers of charges, and generating reports. It evaluates various software development methodologies and determines that the fourth generation techniques methodology is most appropriate due to its features around non-procedural languages, report generation, data manipulation, and screen interaction that map well to the system requirements. The document also discusses various dependability measurement attributes that are relevant for the system, including reliability, efficiency, integrity, maintainability, and availability.
This document discusses software quality assurance. It defines software quality and describes two types - quality of design and quality of conformance. It discusses quality concepts at the organizational, project, and process levels. It also describes software reviews, their types and purposes. Software quality assurance aims to establish organizational procedures and standards to achieve high quality software. Key SQA activities include applying technical methods, reviews, testing, enforcing standards and measurement.
This document discusses software metrics and measurement. It describes how measurement can be used throughout the software development process to assist with estimation, quality control, productivity assessment, and project control. It defines key terms like measures, metrics, and indicators and explains how they provide insight into the software process and product. The document also discusses using metrics to evaluate and improve the software process as well as track project status, risks, and quality. Finally, it covers different types of metrics like size-oriented, function-oriented, and quality metrics.
Black box testing is a software testing technique where the internal structure and implementation of the system is not known. It focuses on validating the functionality of the system based on requirements and specifications. Some key techniques of black box testing include equivalence partitioning, boundary value analysis, and error guessing. Equivalence partitioning divides test cases into equivalence classes based on expected behavior. Boundary value analysis tests values at the boundaries of equivalence classes. Error guessing involves creating test cases based on intuition about potential errors. Black box testing is applied at various levels including unit, integration, system, and non-functional testing.
Software testing is the process of evaluation a software item to detect differences between given input and expected output. Also to assess the feature of A software item. Testing assesses the quality of the product. Software testing is a process that should be done during the development process. In other words software testing is a verification and validation process.
Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test techniques include, but are not limited to the process of executing a program or application with the intent of finding software bugs (errors or other defects).
Software testing can be stated as the process of validating and verifying that a computer program/application/product:
• meets the requirements that guided its design and development,
• works as expected,
• can be implemented with the same characteristics,
• and satisfies the needs of stakeholders.
Software Development Process Cycle:-
PLAN (P): Device a plan. Define your objective and determine the strategy and supporting methods required to achieve that objective.
DO (D): Execute the plan. Create the conditions and perform the necessary training to execute the plan.
CHECK (C): Check the results. Check to determine whether work is progressing according to the plan and whether the results are obtained.
ACTION (A): Take the necessary and appropriate action if checkup reveals that the work is not being performed according to plan or not as anticipated.
The document discusses the evolving role of software engineering and reasons for the software crisis. It notes that the nature and complexity of software has changed, requiring a move away from relying on individual experts. Additionally, many software projects fail or run over budget and schedule. Common causes include large problems, lack of training, skill shortages, and low productivity growth. The document examines historical software failures from Ariane 5 to Windows XP and argues for adopting systematic software engineering practices and processes.
This document defines bug tracking terms and provides guidance on effective bug reporting. It explains that a bug tracking system is used to keep track of reported software bugs. Effective bug reports are clear, contain one bug each, and include all necessary information like steps to reproduce, expected vs. actual results, and environment details. The lifecycle of a bug involves states like open, in progress, resolved, reopened and closed. Popular bug tracking systems include JIRA, Bugzilla, Mantis and others.
Quality management tin software engineering with respect to S.Q.C., S.Q.P., S.Q.A. ISO QUALITY Factors, McCall's Quality Factors, Garvin's Quality Factors and all aspects about quality in software engineering.
This document discusses requirements engineering modeling. It begins by explaining the objectives and overview of requirements engineering and modeling. It then discusses guidelines for creating requirements analysis models, including principles and rules of thumb. It describes structured and object-oriented analysis approaches to requirements modeling. Finally, it discusses classifications of modeling elements based on the object-oriented approach, including scenario-based, class-based, and behavioral modeling.
Unit 1( modelling concepts & class modeling)Manoj Reddy
The document discusses object-oriented modeling and design. It covers key concepts like classes, objects, inheritance, polymorphism, and encapsulation. It also discusses the Unified Modeling Language (UML) which provides standard notation for visualizing, specifying, constructing, and documenting models. The document is a lecture on object-oriented concepts for students to understand modeling using classes, objects, and relationships.
Java is a relatively high level language. It offers several ready-to-use resources, which facilitates learning for today's developers and focuses on the actual implementation of the business, instead of worrying about the management of the infrastructure at the system level.
What is Quality ||
Software Quality Metrics ||
Types of Software Quality Metrics ||
Three groups of Software Quality Metrics ||
Customer Satisfaction Metrics ||
Tools used for Quality Metrics/Measurements ||
PERT and CPM ||
YouTube channel : https://www.youtube.com/c/prelrik
This course of slides are very useful for beginners or less experienced testers. The course focuses to teach how actually testers work in LIVE environment.
The document discusses requirements elicitation techniques. It describes requirements elicitation as identifying the needs of users and stakeholders to communicate to developers. Effective techniques include interviews, requirements workshops, brainstorming, storyboards, use cases, role playing and prototyping. Requirements elicitation faces problems of scope, understanding, and volatility. Scope issues include unclear boundaries and unnecessary design data. Understanding challenges involve incomplete user needs, communication gaps between users and analysts, and differing views. Requirements also tend to change over time.
Software quality program and establishiment coceptsGuruKrishnaTeja
This document outlines the key concepts and objectives of a Software Quality Program (SQP). The SQP establishes quality requirements, defines development and maintenance processes, and uses metrics to measure productivity, quality, and documentation. It plans evaluations of software and development processes. Responsibility for the SQP is assigned and its procedures, tools, and records are documented. The SQP scope identifies deliverables and ensures the desired quality is achieved. It defines referenced documents, procedures, tools, records, and establishes tasks like data collection and quality planning to develop high quality software.
The document discusses software quality and defines key aspects:
- It explains the importance of software quality for users and developers.
- Qualities like correctness, reliability, efficiency are defined.
- Methods for measuring qualities like ISO 9126 standard are presented.
- Quality is important throughout the software development process.
- Both product quality and process quality need to be managed.
The document discusses different types of software metrics that can be used to measure various aspects of software development. Process metrics measure attributes of the development process, while product metrics measure attributes of the software product. Project metrics are used to monitor and control software projects. Metrics need to be normalized to allow for comparison between different projects or teams. This can be done using size-oriented metrics that relate measures to the size of the software, or function-oriented metrics that relate measures to the functionality delivered.
SQA activities involve formulating quality plans, applying software engineering techniques, conducting reviews, implementing multi-tiered testing, enforcing process adherence, controlling changes, measuring change impact, performing audits, and keeping records. The key goals are to evaluate software quality, monitor adherence to standards and procedures throughout the development lifecycle, and ensure quality is maintained.
This document discusses software project management artifacts. Artifacts are organized into management and engineering sets. The management set includes artifacts like the work breakdown structure, business case, and software development plan. The engineering set includes requirement, design, implementation, and deployment artifact sets. Each set captures information through various notations and tools to manage the software development lifecycle.
This document discusses the requirement analysis and software development methodology selection for developing a ticketing system called the Snow City System. It analyzes the requirements of the system, which include scanning tickets, calculating charges based on time spent, notifying customers of charges, and generating reports. It evaluates various software development methodologies and determines that the fourth generation techniques methodology is most appropriate due to its features around non-procedural languages, report generation, data manipulation, and screen interaction that map well to the system requirements. The document also discusses various dependability measurement attributes that are relevant for the system, including reliability, efficiency, integrity, maintainability, and availability.
This document discusses software quality assurance. It defines software quality and describes two types - quality of design and quality of conformance. It discusses quality concepts at the organizational, project, and process levels. It also describes software reviews, their types and purposes. Software quality assurance aims to establish organizational procedures and standards to achieve high quality software. Key SQA activities include applying technical methods, reviews, testing, enforcing standards and measurement.
This document discusses software metrics and measurement. It describes how measurement can be used throughout the software development process to assist with estimation, quality control, productivity assessment, and project control. It defines key terms like measures, metrics, and indicators and explains how they provide insight into the software process and product. The document also discusses using metrics to evaluate and improve the software process as well as track project status, risks, and quality. Finally, it covers different types of metrics like size-oriented, function-oriented, and quality metrics.
Black box testing is a software testing technique where the internal structure and implementation of the system is not known. It focuses on validating the functionality of the system based on requirements and specifications. Some key techniques of black box testing include equivalence partitioning, boundary value analysis, and error guessing. Equivalence partitioning divides test cases into equivalence classes based on expected behavior. Boundary value analysis tests values at the boundaries of equivalence classes. Error guessing involves creating test cases based on intuition about potential errors. Black box testing is applied at various levels including unit, integration, system, and non-functional testing.
Software testing is the process of evaluation a software item to detect differences between given input and expected output. Also to assess the feature of A software item. Testing assesses the quality of the product. Software testing is a process that should be done during the development process. In other words software testing is a verification and validation process.
Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation. Test techniques include, but are not limited to the process of executing a program or application with the intent of finding software bugs (errors or other defects).
Software testing can be stated as the process of validating and verifying that a computer program/application/product:
• meets the requirements that guided its design and development,
• works as expected,
• can be implemented with the same characteristics,
• and satisfies the needs of stakeholders.
Software Development Process Cycle:-
PLAN (P): Device a plan. Define your objective and determine the strategy and supporting methods required to achieve that objective.
DO (D): Execute the plan. Create the conditions and perform the necessary training to execute the plan.
CHECK (C): Check the results. Check to determine whether work is progressing according to the plan and whether the results are obtained.
ACTION (A): Take the necessary and appropriate action if checkup reveals that the work is not being performed according to plan or not as anticipated.
The document discusses the evolving role of software engineering and reasons for the software crisis. It notes that the nature and complexity of software has changed, requiring a move away from relying on individual experts. Additionally, many software projects fail or run over budget and schedule. Common causes include large problems, lack of training, skill shortages, and low productivity growth. The document examines historical software failures from Ariane 5 to Windows XP and argues for adopting systematic software engineering practices and processes.
This document defines bug tracking terms and provides guidance on effective bug reporting. It explains that a bug tracking system is used to keep track of reported software bugs. Effective bug reports are clear, contain one bug each, and include all necessary information like steps to reproduce, expected vs. actual results, and environment details. The lifecycle of a bug involves states like open, in progress, resolved, reopened and closed. Popular bug tracking systems include JIRA, Bugzilla, Mantis and others.
Quality management tin software engineering with respect to S.Q.C., S.Q.P., S.Q.A. ISO QUALITY Factors, McCall's Quality Factors, Garvin's Quality Factors and all aspects about quality in software engineering.
This document discusses requirements engineering modeling. It begins by explaining the objectives and overview of requirements engineering and modeling. It then discusses guidelines for creating requirements analysis models, including principles and rules of thumb. It describes structured and object-oriented analysis approaches to requirements modeling. Finally, it discusses classifications of modeling elements based on the object-oriented approach, including scenario-based, class-based, and behavioral modeling.
Unit 1( modelling concepts & class modeling)Manoj Reddy
The document discusses object-oriented modeling and design. It covers key concepts like classes, objects, inheritance, polymorphism, and encapsulation. It also discusses the Unified Modeling Language (UML) which provides standard notation for visualizing, specifying, constructing, and documenting models. The document is a lecture on object-oriented concepts for students to understand modeling using classes, objects, and relationships.
The document discusses scenario-based requirements analysis and modeling. It covers topics like creating preliminary use cases, refining use cases, writing formal use cases, and developing supplemental models like activity diagrams and swimlane diagrams. The key aspects are using use cases to describe functions from an actor's perspective, refining use cases to explore alternatives and exceptions, and creating additional models like activity and swimlane diagrams to further illustrate flows and responsibilities. Requirements analysis bridges system descriptions and software design to establish customer needs and a basis for validation.
The document provides information about object-oriented modeling and design concepts including classes, objects, inheritance, polymorphism, and the Unified Modeling Language (UML). It discusses how object-oriented modeling uses classes to define objects, relationships, and behaviors. It also describes the basic UML diagram types like use case diagrams, class diagrams, sequence diagrams, and state diagrams that can be used to design software systems using an object-oriented approach.
This document discusses object-oriented design and architectural design. It begins by outlining topics related to determining how to build a system using object-oriented design, including design goals, architectural designs, class modeling, design patterns, state chart modeling, collaboration modeling, and more. It then discusses what software design is, including that it is a problem-solving process to implement functional requirements while meeting non-functional constraints. Design involves making decisions to resolve issues while choosing from design alternatives. The document also discusses top-down and bottom-up design approaches, software design principles, and the object-oriented design process.
This document discusses scalability requirements engineering for large scale systems. It summarizes an existing goal-oriented approach for modeling scalability requirements proposed by Duboc et al. This approach defines scalability as the ability of a system to maintain quality goal satisfaction under varying operational conditions. It involves identifying scalability obstacles, then generating scalability goals and assumptions to resolve these obstacles. The document argues this approach may not be well-suited for modeling requirements of very large scale systems, as it assumes workload characteristics can be bounded over a system's lifetime, which may not hold true for systems intended to continuously evolve over many years.
The document discusses requirements analysis and modeling approaches. It covers:
1) The objectives and types of requirements models, including scenario-based, data, class-oriented, flow-oriented, and behavioral models.
2) Elements of analysis models like use cases, classes, attributes, operations, and relationships.
3) Approaches to requirements modeling like structured analysis, object-oriented analysis, and CRC modeling.
4) Concepts of data modeling including data objects, attributes, and relationships.
The document discusses key concepts in software design engineering including:
- Design should implement requirements from analysis and be understandable.
- Qualities like modularity, appropriate data structures, and independent components improve design.
- Fundamental concepts like abstraction, architecture, patterns, and modularity compartmentalize a design.
- Design principles guide creating a design that is traceable, reusable, and accommodates change.
The document discusses key concepts in software design engineering including:
- Design should implement requirements from analysis and be understandable.
- Qualities like modularity, appropriate data structures, and independent components improve design.
- Fundamental concepts like abstraction, architecture, patterns, and modularity compartmentalize a design.
- Design principles guide creating a design that is traceable, reusable, and accommodates change.
This document presents an integrated approach for requirements elicitation and modeling using KAOS and SysML. It introduces system engineering and describes the requirements elicitation process using KAOS, a goal-based approach. It then provides an overview of SysML and how requirements can be modeled in SysML by mapping KAOS models to SysML models. The document aims to demonstrate this integrated approach through a practical case study.
This document provides an introduction to object-oriented analysis and design (OOAD). It defines key OOAD concepts like analysis, design, objects, classes, and relationships. It explains that analysis involves understanding problem domains while design defines software solutions as objects. OOAD uses an object-oriented approach in both analysis and design, with a logical solution based on objects. The document also outlines objectives of an OOAD introduction, basic OOAD principles like abstraction and encapsulation, and modeling techniques like the three model concept of class, state, and interaction models.
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Pattern oriented architecture for web based architectureshuchi tripathi
This document discusses web application architecture and design patterns. It describes a three-layer architecture with presentation, application, and data layers. For the presentation layer, forms are commonly used to structure user interfaces. The application layer focuses on business processes and components. The data access layer exposes database data. Popular design patterns like MVC, PAC, and others are explained as ways to achieve separation of concerns and improve maintainability. MVC divides the presentation layer into separate controller and view components. PAC defines a hierarchical structure of cooperating agents with presentation, abstraction, and control components.
The document discusses the design and implementation process in software engineering. It covers topics like using the Unified Modeling Language (UML) for object-oriented design, design patterns, and implementation issues. It then discusses the design process, including identifying system contexts and interactions, architectural design, identifying object classes, and creating design models like subsystem, sequence, and state diagrams. The example of designing a weather station system is used to illustrate these design concepts and activities.
This document discusses object-oriented analysis and design (OOAD) and domain modeling. It states that knowing an object-oriented language is necessary but not sufficient, and that understanding how to "think in objects" is also critical. A domain model visualizes concepts in the real world domain and is not a description of software objects. The document provides guidelines for creating domain models, such as listing candidate conceptual classes and identifying relationships to include. It warns against representing something as an attribute when it should be a conceptual class.
The document discusses design patterns and the Gang of Four (GoF) patterns. It provides an overview of the different types of patterns including creational, structural, and behavioral patterns. It then focuses on the Adapter pattern, describing its problem of resolving incompatible interfaces, its solution of using an adapter to convert one interface to another, and provides an example of how an point-of-sale system may need to adapt different third-party services that each have different APIs.
The document discusses key concepts in software design, including:
- Design involves modeling the system architecture, interfaces, and components before implementation. This allows assessment and improvement of quality.
- Important design concepts span abstraction, architecture, patterns, separation of concerns, modularity, information hiding, and functional independence. Architecture defines overall structure and interactions. Patterns help solve common problems.
- Separation of concerns and related concepts like modularity and information hiding help decompose problems into independently designed and optimized pieces to improve manageability. Functional independence means each module has a single, well-defined purpose with minimal interaction.
Requirements analysis involves building models that depict user scenarios, system functions, and data flows. This includes identifying analysis classes, their attributes, operations, and relationships. Classes are identified by examining use cases and extracting nouns or noun phrases. Classes should retain information, have identifiable operations, and represent common entities or roles. Attributes and operations are then defined for each class. Relationships between classes like dependencies and associations are also modeled. The analysis can be organized into packages.
This document provides an overview of topics covered in Chapter 7 on software design and implementation, including object-oriented design using UML, design patterns, implementation issues, and open source development. It discusses the design and implementation process, build vs buy approaches, object-oriented design processes involving system models, and key activities like defining system context, identifying objects and interfaces. Specific examples are provided for designing a wilderness weather station system.
This document provides an overview of operating systems. It discusses that an operating system acts as an interface between the user and hardware, managing resources and running applications. Key parts of an operating system include the kernel and system programs. Operating systems allow for multiprogramming and time-sharing to enable efficient sharing of resources between multiple processes. Interprocess communication and process synchronization are important aspects that operating systems facilitate.
This document is a lab manual for database management systems. It contains instructions for installing and using Visual Studio and SQL Server software. Visual Studio is a popular integrated development environment used to develop a wide range of computer programs and applications. It includes features like a code editor, debugger, and various designers. The document provides guidance on tasks for several labs covering topics like creating applications in Visual Studio, installing and managing databases in SQL Server, and building a school management system to apply concepts.
The document provides an outline for a course on data structures and algorithms. It includes topics like data types and operations, time-space tradeoffs, algorithm development, asymptotic notations, common data structures, sorting and searching algorithms, and linked lists. The course will use Google Classroom and have assignments, quizzes, and a final exam.
This document discusses algorithms and their analysis. It defines an algorithm as a finite sequence of unambiguous instructions that terminate in a finite amount of time. It discusses areas of study like algorithm design techniques, analysis of time and space complexity, testing and validation. Common algorithm complexities like constant, logarithmic, linear, quadratic and exponential are explained. Performance analysis techniques like asymptotic analysis and amortized analysis using aggregate analysis, accounting method and potential method are also summarized.
The document contains a multiple choice quiz with questions about various topics in computer science. There are 47 multiple choice questions testing knowledge about topics like binary, memory, operating systems, programming languages, networks, and security. The questions are short, with single sentences providing the prompts and possible multiple choice answers.
The document contains 40 multiple choice questions related to computer science class 12. It covers topics like variables, data types, operators, loops, functions, arrays and more. The questions test concepts like escape sequences, format specifiers, assignment operators, comments, input/output functions, and the difference between various loops in C programming language. It is a practice test to help students prepare for their computer science exam.
This document provides an introduction to databases. It defines what a database is, the steps to create one, and benefits such as fast querying and flexibility. It describes database models like hierarchical, network, entity-relationship, and relational. Key database concepts are explained, including entities, attributes, primary keys, and foreign keys. Finally, it outlines database management system components, common users, and introduces Microsoft Access.
Program, Language, & Programming Language
Object Oriented Programming vs Procedure Oriented Programming
About C
Why still Learn C?
Basic Terms
C Stuff
C Syntax
C Program
Flowcharts provide a graphical representation of steps in a process or algorithm using standard symbols. They were developed in the 1920s-1930s to document business processes but are now widely used to depict computer programs and workflows. The key symbols include boxes, diamonds, arrows, and other shapes to represent tasks, decisions, data, and flow. Flowcharts clarify complex processes, help teams understand them, and can be used to improve or design new procedures.
Algorithm
What is an algorithm?
How are mathematical statements and algorithms related?
What do algorithms have to do with computers?
Pseudo Code
What is pseudocode?
Writing pseudocode
Pseudo Code vs Algorithm
This document outlines the chapters and content covered in a Computer Science course. It includes 17 total chapters, with 5 theoretical chapters, 8 practical chapters, and 4 optional chapters. The chapters cover topics like programming concepts, algorithms, an overview of the C language, variables, operators, input/output statements, selection and iteration control structures, functions, arrays, strings, pointers, data files, data management systems, and Microsoft Access. It also provides a study plan which includes performing practical work every Tuesday, having question/answer sessions every Friday, and using other days for theoretical content, as well as creating a WhatsApp group for the class.
The document discusses computer crimes and cyber crimes under Pakistani law. It defines computer crimes such as copyright violation, cracking codes, cyberbullying and various types of computer viruses. It then outlines specific cyber crimes in Pakistan such as spreading false information about an individual, making or spreading explicit images without consent, cyberstalking, and hacking for stalking. The punishments for these crimes under Pakistani law include prison sentences up to 7 years and fines up to 10 million Pakistani rupees.
Components of Data Communication
Characteristics of Data Transmission
Communication Media
Communication Speed
Communication Hardware
Communication Software
OSI Model
This document provides an overview of basic concepts in information technology, including definitions of computers and computer systems, their key characteristics and components. It describes common input devices like keyboards, mice, and scanners, as well as output devices like monitors, printers and speakers. It also discusses computer hardware, software, data, procedures, and different generations of computers from the past to present.
1st Year Computer Science Book
Sindh Text Book Board Introduction
Introduction
Syed Zaid Irshad
Rules (that You have to Follow)
Book Introduction
10 Chapters
Theoretical Chapters are 6
Practical Chapters are 4
Chapter 1: Basic Concept of Information Technology
Introduction of Computer
Definition
Characteristics
Parts of Computer
Input
Output
Memory
Primary Storage
Secondary Storage
Ports
Language Translator
Compiler
Interpreter
Generations of Programming Language
Ages of Computers
Generations of Computer
Classification of Computers
Chapter 2: Information Networks
Types of Network
LAN
WAN
MAN
GAN
Topologies
Star
Ring
Bus
Hybrid
File Transfer Protocol
World Wide Web
Chapter 3: Data Communication
Standards
Transmission
Simples
Half Duplex
Full Duplex
Media
Twisted Pair Cable
Coaxial Cable
Fiber Optic Cable
Microwave Transmission
Satellite Transmission
Open Systems Interconnection model (OSI model)
Chapter 4: Applications and Use of Computers
Difference Between Application and Use
Impacts of Computers
Chapter 5: Computer Architecture
Address of Memory Locations
Instruction Format
Fetch and Execute
Chapter 6: Security, Copyright and The Law
Computer Crime
Computer Viruses
Computer Privacy
Software Piracy and Law
Chapter 7: Operating System
User Interface
Graphical User Interface
Operating Systems
Chapter 8: Word Processing
Introduction to MS Word
Creating
Editing
Formatting
Printing
Chapter 9: Spreadsheet
Introduction to MS Excel
Creating
Editing
Formatting
Printing
Formulae
Project
Chapter 10: Internet Browsing and Using E-mail
Create Email ID
Send Mail
Download File
Upload File
Study Plan
Every Tuesday we perform Practical
Every Friday Half of the Lecture will be used as question answer session
Rest of the days are for Theoretical Stuff
Make WhatsApp Group for class where we can share stuff related to the Subject
This document discusses SQL set operators such as UNION, UNION ALL, INTERSECT, and MINUS. It provides examples of how to use each operator to combine result sets from multiple queries, eliminate duplicates, return common or unique rows, and control the order of rows in the final output. Tables used in the examples include the EMPLOYEES and JOB_HISTORY tables, which contain data on current and previous employee jobs. Guidelines are provided around matching columns in UNION queries and using parentheses and ORDER BY.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
artificial intelligence and data science contents.pptxGauravCar
What is artificial intelligence? Artificial intelligence is the ability of a computer or computer-controlled robot to perform tasks that are commonly associated with the intellectual processes characteristic of humans, such as the ability to reason.
› ...
Artificial intelligence (AI) | Definitio
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
2. Goal-Directed Requirements
Acquisition (KAOS)
(Organizational) goals lead to requirements.
Goals justify and explain requirements which are
not necessarily comprehensible by stakeholders.
Goals can be used to assign responsibilities to
agents so that prescribed constraints can be met.
Goals provide basic information for detecting and
resolving conflicts that arise from multiple
viewpoints
3. The KAOS Modeling Philosophy
• Modeling a social setting involves a variety of concepts,
including Goals, Agents, Concerned Objects, Actions,
Constraints and Responsibilities.
• Goals lead to assignments of responsibilities and designs of
actions and artifacts
• Use a metamodel to support reuse of generic domain
modeling patterns [Dardenne93]
• For example, the library domain is an instance of the
“resource allocation” meta-domain, which also covers
car/room/dwelling rental and is similar to airline/hotel
reservation, class registration etc.
4. The KAOS Acquisition Process
• Identify Goals, and their Concerned Objects.
• Identify potential Agents and their Capabilities.
• Operationalize Goals into Constraints.
• Refine Objects and Actions.
• Derive strengthened Objects and Actions to Ensure
• Constraints.
• Identify alternative Responsibilities.
• Assign Actions to responsible Agents.
All this could be just as useful to someone doing
organizational design, rather than software development!
5. Four KAOS models :
• Goal model
• Responsability model
• Operation model
• Object model
6. Goals are desired system properties that
have been expressed by some stakeholders.
Stakeholder (wikipedia): third party who temporarily holds
money or property; more recent meaning (widely used in
management): person or organization that has a legitimate
interest in a project or entity; the new use of the term arose
together with and due to the spread of
corporate social responsibility ideas…
interviews of domain experts and current & future
users
analysis of existing systems
reading of available technical documents
Goal modelGoal model
7. 7
• Each goal is either a root or is justified by at least
another goal that explain WHY it is needed.
• Each goal except a leave is refined as a collection of
subgoals describing HOW it can be reached.
• Identifying goals proceeds from either top-down,
bottom-up and non-directional approaches: from
intermediate goals are identified higher-level (business
or strategical) goals and lower-level (system
requirements) ones.
Goal modelGoal model
8. 8
Clear distinction between two low-level types of
goals:
• Requirements, to be achieved by a software agent,
• Expectations, to be achieved by an agent which is
part of the system environment.
Conflicts (and more generally obstacles that prevent
goals to be achieved) must be identified as soon as
possible.
Goal modelGoal model
9. 9
Domain properties:
Properties relevant to the application domain, used in
refinements to prove that a refinement is complete. Ex:
in order to satisfy a service request, an infrastructure to
perform the service must be available.
There are two types of domain properties :
- domain hypotheses: domain object properties expected
to hold ; ex: the elevator system has at least one cage to
carry passengers,
- domain invariants: properties known to hold in every
state of some domain object, e.g. a physical law,
regulation or a constraint enforced by some
environmental agent ; eg : for light buttons, we could
state that « the light is either on or off ».
Goal modelGoal model
Infrastructure available
10. 10
Requirements can be gathered by means of open
interviews. A more efficient way is to conduct less
open interviews be reusing requirements patterns.
One of the long-term benefits of investing in KAOS
technology consists in progressively modelling generic
patterns of requirements.
Completeness of the goal model is ensured be
reviewing the different diagrams during validation
sessions with stakeholders.
Goal modelGoal model
11. 11
• Information system: software system to be and the
part of the environment with which it interacts.
• Agent: humain being or automated component that
are responsible for achieving requirements and
expectations.
– We may stop refining goals into subgoals when they are
placed (as requirements) under the responsibility of a single
agent.
• Assignment is used to link expectations to related
agents (several agents may be assigned to an
expectation).
Responsibility modelResponsibility model
13. 13
Completeness criterion 1: a goal model is said to be
complete with respect to the refinement relationship
‘if and only if’ every leaf goal is either an expectation, a
domain property or a requirement.
Completeness criterion 2: a goal model is complete
with respect to the responsability relationship ‘if and
only if’ every requirement is placed under the
responsability of one and only one agent (either
explicitly or implicitly).
Goal modelGoal model
14. 14
Goal modelGoal model
…with this generic goal pattern
(case driven decomposition)…
Beginning the Elevator case study…
23. 23
Goal modelGoal model
Qualitative comparaison:
• links to parent goals to which each requirement contributes
• creating a conflit if it contributes negatively
The design having a bidirectional button panel on each floor
seems to be the best compromise.
24. 24
Goal modelGoal model
Based on the bidirectional button panel design, we can
now refine the goal « Button depressed »:
25. 25
Goal modelGoal model
Let’s now refine the goal « Passengers brought to
requested destination », applying the milestone tactics:
26. 26
Goal modelGoal model
To refine the goal « No casualty », we use a generic
pattern that also use a milestone-driven refinement tactic:
Generic goal « No casualty »
The following figure shows how this pattern has been
used, and how the « No intrusion » goal has been
decomposed.
27. 27
Leaf goals are refined later:
•“Emergency stop available”.
•“System protected against fire”.
•“System protected against power failure”
•“No move in overweight conditions”.
36. 36
Object modelObject model
The Object model is used to define and document the
concepts of the application domain that are relevant
with respect to the known requirements and to provide
static constraints on the operational system that will
satisfy the requirements.
Part of the Object model are objects pertaining to the
stakeholder’s domain and other objects for expressing
requirements or constraints on the operational model.
There are three types of objects: entities, agents,
relationships.
37. 37
Entities: independant (needn’t refer to other objects)
and passive (can’t perform operations) objects; may
have attributes whose values define a set of states the
entity can transition to
Agents: independant and active objects; they can
perform operations that usually imply state transitions
on entities (ex: elevator company, passenger, elevator
controler)
Associations: dependant and passive objects that may
have attributes (ex: "At" that links a cage and a floor)
Object modelObject model
38. 38
Ex: entity « Alarm bell » as a component of the « Elevator »:
Object identification is driven by the goal definition process. Most
goals’s short and long definitions refer to domain objects being
modelled and documented.
All modelled objects shall have their own entries in the glossary
section of the requirements document. During review of the object
model, stakeholders will formally agree on a common vocabulary.
Another way to identify new objects consists in looking at the
requirements and discover the system components they are
necessary for satisfying them.
Object modelObject model
39. 39
Objects may be represented in goal diagrams; the concerns relationship
is used to link a requirement to the objects that are needed for it to be
satisfied. Identifying those objects shall further restrict the space of
solutions that can be proposed by the future system provider. Ex:
Object modelObject model
42. 42
Object « Floor »:
Object modelObject model
The KAOS model is compliant with UML class diagrams in that
KAOS entities correspond to UML classes; and KAOS associations
correspond to UML binary association links or n-ary association
classes. Inheritance is available to all types of objects (including
associations).
Objects can be qualified with attributes.
43. 43
The Operation model describes all the behaviors that agents
need to fulfill their requirements.
Behaviors are expressed in term of operations performed by
agents.
Ex: press button, enter, exit (perform by passengers) ; open
doors, close doors, move up, move down (perform by elevators).
Those operations work on objects: they can create objects,
trigger object state transitions and activate other operations (by
sending an event).
Operations are justified by the goal they operationalize: an
operation without a goal means there’re missing goals, while a
requirement without operations is just wishful thinking.
Operation modelOperation model
44. 44
Operations identification sources:
• stakeholders, that typically describe processes rather
than goals during interviews; the analyst then asks
specific questions in order to identify the reasons
behing the existing processes and hence unveil the
goals that justify these processes;
• existing requirements: operations explain how they
have to be realized.
Operation modelOperation model
45. 45
Requirements can be operationalized by:
• some object(s)
• some agent behavior(s)
• a combinaison of both
They are respectively requirements that describe
static, dynamic, and both properties on the system:
• the requirement « Elevator equiped with floor doors » will be
operationalized by an object « Floor door »
• requirements that describe dynamic system properties are
operationalized by operations
• the expectation « Stop button used » will be operationalized
with an operation « Push button » and the « Button » entity
Operation modelOperation model
46. 46
In a process, operations are represented as ovals,
concerned objects are connected to the operations by
means of input and output links.
Events are represented as: . Events may be
external or produced by operations (through an output
link). They may start (cause) or stop operations.
An operation model (or process) typically composes
operations performed by one or several agents to
achieve a requirement.
Operation modelOperation model
48. 48
Completeness criterion 3 : to be complete, a process
diagram must specify
(i) the agents who perform the operations
(ii) the input and output data for each operation.
Completeness criterion 4 : to be complete, a process
diagram must specify when operations are to be
executed.
Completeness criterion 5 : all operations are to be
justified by the existence of some requirements
(through the use of operationalization links).
Operation modelOperation model
49. 49
Operations can be triggered explicitely by an event. If
no event is specified, the operation will be triggered
implicitly when all the data needed in input are
available (data flow).
Requirements left unoperationalized are called « open
requirements »; solution providers have the complete
freedom to address the requirement as they want. The
less open requirements are left in the model, the more
precise the requirements document will be by
eliminating possible implementations.
Operation modelOperation model
51. 51
Typical instance of a process pattern KAOS analysts have
to reproduce in all projects:
Operation modelOperation model
(is responsible for)(operationalizes)
A requirement is said to be "closed" when this trian-
gular relationship Responsability-Operationalization-
Performance has been established.
53. 53
Dealing with obstacles.
Obstacles are situations in which a goal, a requirement
or an expectation is violated. The obstacle is said to
"obstruct" the goal, requirement or expectation.
Dealing with obstacles is very important for safety-
critical systems: it allows analysts to identify and address
circumstances at requirements engineering time
(instead of at programming or running time) in order to
produce for instance robust requirements or new
requirements to avoid or reduce impacts of obstacles.
The result will be a more reliable software.
ObstaclesObstacles
54. 54
Obstacle analysis with KAOS is a goal-oriented activity. It
begins with exploring the goal model and with negating
each goal in turn.
As a goal G is refined into goals G1, …, Gn if and only if
G1, …, Gn all together imply G, we know that if goal G is
violated, it is because at least one of its subgoals is
violated.
Each leaf obstacle is then reviewed with domain experts
to study whether it is worth considering it in the
obstacle analysis. It allows the analyst to prune the
obstacle space and to focus on the most relevant
obstacles.
ObstaclesObstacles
57. 57
Next, conditions for the obstacle to be raised are looked for. Typical
ways used to identify obstacles start by considering component
failures or people behaving in an unexpected way, maliciously or
because of some people’s capability limitation (disable people,
children, …).
Ex: an obstacle to the goal "Elevator direction updated few seconds
before next stop" occurs when blind people want to use the elevator
system as they can’t read the indications.
Obstacles are linked to the goals they obstruct (obstruction link).
Obstacles are refined the same way as goals, but while goals are
generally ‘AND-refined’, obstacles are most often ‘OR-refined’.
ObstaclesObstacles
58. 58
Obstacle to « Passengers informed of elevator direction »:
ObstaclesObstacles
OR refinement
(Obstruct)
59. 59
Having identified the conditions for it to occur, the
analyst can fix the obstacle in several ways. A first way
consists in defining new requirements that prevent the
obstacle from occuring.
In the preceding example, one can add a new
requirement: "Elevator direction announced by voice
upon floor arrival".
New requirements are linked to the obstacle they
resolve by a resolution link.
Other requirements for blind people could be "Floor
level announced by voice upon floor arrival" and "Call
buttons in Braille".
ObstaclesObstacles
61. 61
An important source of obstacles concerns system (and
components) reliability and robustness. Reliability and
robustness requirements aim at preventing failures to
occur. One can for instance introduce requirements in
terms of Mean Time Before Failure (MTBF), or in terms
of a maintenance program to replace components
systematically at the right time, and so on.
A second way to fix an obstacle is to restore the
obstructed goal once the obstacle occurs. For instance, if
an elevator failure puts the system out of order, a
restoration requirement can prescribe the maximum
delay within which the system must be repaired.
ObstaclesObstacles
62. 62
• A third way to fix an obstacle consists in minimizing its
effects.
– Suppose the building is equiped with two elevator cages,
one serving floors 1 to 10, the other one floors 10 to 20. If
one cage goes out of order, a requirement should
prescribe that the system shall be self-reconfigured so that
the other cage provides service to all floors (from 1 to 20).
• It’s also possible to fix obstacles by modifying the
KAOS model in different ways, for instance by
substituting an agent with a more "capable" one, by
weakening the obstructed goal so that the obstacle is
no longer relevant or by substituting a goal to another
one.
ObstaclesObstacles
63. 63
Possible refinement of the goal « Robust and reliable elevator
system »:
ObstaclesObstacles
Each branch can be
opted for separately to
satisfy the goal, but
KAOS does not force
exclusion
64. 64
The structure of the requirements document generated
from a KAOS model is borrowed from the IEEE 830-1998
standard for software requirements specification :
Table of contents
1. Introduction
1.1 Document purpose
1.2 System purpose
1.3 Definitions, acronyms, and abbreviations → glossary derived from
1.4 References the KAOS model
1.5 Overview
2. Overall description
2.1 System perspective
2.2 User requirements → a subsection for each goal diagram
2.3 User characteristics and a list of the requirements
2.4 Constraints
2.5 Assumptions and dependencies → assumptions & obstacles not
2.6 Apportioning of requirements dealed with
ConclusionConclusion
65. 65
3. System requirements
3.1 System architecture → decomposition of the system by
KAOS agents (responsability model)
3.2 Object model → diagrams of the KAOS object model
3.3 Operation model → diagrams of the KAOS operation model
A major benefit of KAOS is that it provides a bidirectional traceability
between the problem description and the expected solution description.
As systems require frequent changes, it is vital to keep the requirements
document up to date with respect to the current state of development.
Requirements documents with KAOS tend to be more complete.
Completness must be understood by looking at the five completness
criteria: a complete KAOS model leaves no space for wishful thinking (a
goal not refined), requirements with no responsible, unjustified
operations, and operations for which we ignore who will execute what
and when.
ConclusionConclusion
66. 66
Completeness of the goal model also relies on 3 points :
the quality of the requirements definition phase
(interviewing stakeholders, if operated properly, leads to
a good goal covering rate)
the validation meetings during which stakeholders
review consolidated goal diagrams (conflicts are
addressed, forgotten goals have a new chance to come
up)
refinement techniques that guarantee completness
and consistency (generic refinement patterns that
require formal notations for safety-critical applications).
ConclusionConclusion