Intelligent transportation systems (ITS) use advanced technologies like electronics, computers, communications and sensors to provide travellers with important information and improve transportation safety and efficiency. ITS applications range from basic systems like car navigation to more advanced integrated systems. Technologies involved in ITS include sensors for vehicle detection, GPS for location data, wireless communications for information sharing, and computational methods for data analysis. The benefits of ITS include safety improvements from incident detection and emergency response, increased productivity from traffic management, and reduced environmental impacts from optimized traffic flow.
The document provides instructions for a virtual RPA training workshop. It outlines:
1. There will be an instructor and TAs to provide help. A separate troubleshooting meeting will be hosted for hands-on help.
2. Polls will be used to track lab completion status in real time. Participants should vote after completing each lab.
3. Questions that can wait should be typed in the chat. Immediate questions should be raised by unmuting.
4. The agenda includes an introduction to RPA, creating first desktop flows, advanced topics like unattended flows, and a closing Q&A session. Participants are asked to follow rules like muting and not sharing the meeting link.
Clinical decision support systems (CDSS) provide health professionals with patient-specific advice and recommendations to help with clinical decision-making. CDSS can generate alerts, aid with diagnosis, and assist with treatment planning. They utilize medical knowledge combined with individual patient data to produce customized assessments or advice. Early systems included MYCIN and INTERNIST-I, while successful current CDS systems are DXplain and QMR. CDSS can benefit healthcare by improving processes and outcomes given limited resources and increasing demand, though they may also change the physician-patient relationship or have legal implications.
Data mining involves using machine learning and statistical methods to discover patterns in large datasets and is useful in bioinformatics for analyzing biological data. Bioinformatics analyzes data from sequences, molecules, gene expressions, and pathways. Data mining can help understand these rapidly growing biological datasets. Common data mining tools in bioinformatics include BLAST for sequence comparisons, Entrez for integrated database searching, and ORF Finder for identifying open reading frames. Data mining approaches are well-suited to the enormous volumes of data in bioinformatics databases.
The document discusses RNA-seq analysis. It begins with an introduction to Mikael Huss, a bioinformatics scientist, and provides an overview of how genomics, RNA profiles, protein profiles, and interactomics relate within systems biology. The document then discusses how gene expression analysis can provide insights into basic research questions regarding tissue and cell identity, as well as insights into diseases by identifying genes that are over- or under-expressed in patients. Finally, it provides a brief overview of the typical workflow for RNA-seq analysis, which involves mapping RNA sequencing reads to a reference genome or transcriptome.
Why it’s Needed?
Traffic congestion-insufficient road development-growing number of vehicles.
Low speed, increased accident rates, increased fuel consumption, and increased pollution.
Impossible to build enough new roads or to meet the demand.
These explore the concepts that treat highway systems and the vehicles that use them as integrated system. Among them is the concept of Intelligent Transportation Systems.
The goal of I T S is to improve the transportation system to make it more efficient and safer by use of information, communications and control technologies.
India is going through a period of drastic change in the transportation area due to:
Rapidly growing economy.
Insufficient and inadequate public transportation system.
Rising vehicle ownership levels.
ITS PARTS
I T S ARCHITECTURE
· Framework for planning, defining, and integrating intelligent transportation systems.
Benefits of Architecture
Reduces time and resources required to integrate the technologies to local needs
Helps identify agencies and jurisdictions & seeks their participation
COMMUNICATION SYSTEMS
Effective and efficient operation of transit systems relies on a communications infrastructure and vehicle-based communications technologies.
Communications systems are used to transmit voice and data between transit vehicles and operation centers, and to transmit commands between operators and technologies.
Transit communications systems are comprised mostly of wireless technologies and applications.
FLEET MANAGEMENT AND OPERATIONS
These includes separate technologies often are combined in various software packages, which allow for the integration of many different transit functions.
GIS allows transit agencies to accurately track where demand is located in their service area.
APPLICATIONS OF I T S
ELECTRONIC TOLL COLLECTION(E T C)
GLOBAL POSITIONING SYSTEM(G P S)
ADVANCED TRAVELLER INFORMATION SYSTEM(ATIS)
IN-VEHICLE TRANSIT INFORMATION SYSTEM
AUTOMATIC PASSENGER COUNTER
ADVANTAGES OF I T S
Improved safety
Better traffic flow
Lower travel cost
Better environmental quality
Increased business activity
Greater user acceptance
Better travel information
Better planning information
DISADVANTAGES OF I T S
Difficult to use in mixed traffic
Preliminary difficulties in understanding
ITS equipments costly
The control system software could be hacked by hackers
www.wikipedia.com
www.answers.com
www.howstuffworks.com
www.tech-faq.com
www.thetravelinsider.info
http://www.itsoverview.its.dot.
http://www.transport systems.com
http://www.mountain-plains.org
The document discusses the Architecture Business Cycle (ABC), which describes the relationships between a system's architecture, its environment, and the factors that influence both. The ABC is a cycle of influences between the architecture and various technical, business, and social environments. It shows how architectures are shaped by stakeholders, the developing organization, the architect's experience, and the technical environment. In turn, architectures influence the organization's structure and goals, customer requirements, and the architect's experience on subsequent systems. The cycle represents how organizational goals and requirements inform the architecture, which then informs the developed systems and feeds back to influence the organization.
Architecture design in software engineeringPreeti Mishra
The document discusses software architectural design. It defines architecture as the structure of a system's components, their relationships, and properties. An architectural design model is transferable across different systems. The architecture enables analysis of design requirements and consideration of alternatives early in development. It represents the system in an intellectually graspable way. Common architectural styles structure systems and their components in different ways, such as data-centered, data flow, and call-and-return styles.
This document discusses software architecture from both a management and technical perspective. From a management perspective, it defines an architecture as the design concept, an architecture baseline as tangible artifacts that satisfy stakeholders, and an architecture description as a human-readable representation of the design. It also notes that mature processes, clear requirements, and a demonstrable architecture are important for predictable project planning. Technically, it describes Philippe Kruchten's model of software architecture, which includes use case, design, process, component, and deployment views that model different aspects of realizing a system's design.
The document discusses architectural design for software systems. It covers topics such as software architecture, data design, architectural styles, analyzing architectural alternatives, and mapping requirements to architectural designs. The key aspects are:
1) Architectural design represents the structure of data and program components to build a computer system. It begins with data design and derives architectural representations.
2) Software architecture allows analysis of design effectiveness and consideration of alternatives to reduce risks.
3) Common architectural styles include data-centered, data flow, call-and-return, object-oriented, and layered styles.
4) Requirements are mapped to architectural designs through techniques like transform mapping and transaction mapping. The resulting design is then refined.
Architectural Design in Software Engineering SE10koolkampus
The document introduces architectural design and discusses its importance in establishing the overall structure of a software system. It explains that multiple models are required to document a software architecture and describes common types of architectural models, including static, dynamic, interface, relationships, and domain-specific models. The document also discusses advantages of explicit architecture, the architectural design process, subsystems and modules, architectural styles, and attributes like performance, security, safety, availability, and maintainability.
This ppt covers the following topics
Software quality
A framework for product metrics
A product metrics taxonomy
Metrics for the analysis model
Metrics for the design model
Metrics for maintenance
The document discusses key concepts in software design including abstraction, architecture, patterns, modularity, information hiding, and functional independence. It explains that software design is an iterative process that transforms requirements into a blueprint for constructing the software through design models, data structures, system architecture, interfaces, and components. Good software design exhibits qualities like being bug-free, suitable for its intended purpose, and a pleasurable user experience.
The document discusses five parameters for improving software economics: reducing complexity, improving processes, using skilled personnel, using better tools, and adjusting quality thresholds. It focuses on reducing size through components, reuse, languages, and modeling. Improving processes involves optimizing activities at the meta, macro, and micro levels. Using skilled personnel and effective teams is important. Automation through tools can improve productivity by 20-40%. Achieving quality involves requirements management, architecture, configuration control, and testing.
The document discusses software architecture, where it comes from, and what it is. Architectures are influenced by system stakeholders and their requirements, the developing organization, and the architects' experience. An architecture defines elements, their relationships, and properties. It is important because it represents early design decisions, dictates implementation, organizational structure, and quality attributes. Architectural patterns, reference models, and reference architectures capture common architectural elements but are not full architectures themselves.
This Presentation contains all the topics in design concept of software engineering. This is much more helpful in designing new product. You have to consider some of the design concepts that are given in the ppt
Unit 5- Architectural Design in software engineering arvind pandey
This document provides an overview of architectural design for software systems. It discusses topics like system organization, decomposition styles, and control styles. The key aspects covered are:
1. Architectural design identifies the subsystems, framework for control/communication, and is described in a software architecture.
2. Common decisions include system structure, distribution, styles, decomposition, and control strategy. Models are used to document the design.
3. Organization styles include repository (shared data), client-server (shared services), and layered (abstract machines). Decomposition can be through objects or pipelines. Control can be centralized or event-based.
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.
This document provides an overview of software maintenance. It discusses that software maintenance is an important phase of the software life cycle that accounts for 40-70% of total costs. Maintenance includes error correction, enhancements, deletions of obsolete capabilities, and optimizations. The document categorizes maintenance into corrective, adaptive, perfective and preventive types. It also discusses the need for maintenance to adapt to changing user requirements and environments. The document describes approaches to software maintenance including program understanding, generating maintenance proposals, accounting for ripple effects, and modified program testing. It discusses challenges like lack of documentation and high staff turnover. The document also introduces concepts of reengineering and reverse engineering to make legacy systems more maintainable.
This document provides an overview of the Cost Benefit Analysis Method (CBAM) for analyzing architectural decisions. CBAM considers both the technical impacts of decisions as well as the associated costs and financial benefits. It involves stakeholders prioritizing scenarios, assigning utility values to quality attributes, developing architectural strategies to address scenarios, and calculating the costs and benefits of strategies to determine the highest return on investment. The process is iterative, with the second iteration incorporating uncertainty through risk assessment. CBAM aims to help organizations optimally allocate resources by selecting strategies that maximize financial gains and minimize risks.
The document discusses factors related to software project size and effort. It provides the following key points:
1) Software development and maintenance can account for a significant portion of economic activity, with estimates that it will account for 12.5% of the US GDP by 1990.
2) Most effort is spent on maintenance rather than development, with estimates that maintenance accounts for 60-90% of total effort.
3) Software project size is categorized based on factors like number of programmers, duration, lines of code, and interactions/complexity. These range from trivial single-programmer projects to extremely large projects involving thousands of programmers over 5-10 years.
4) A 1964 study found that programmers only spent
SE_Lec 05_System Modelling and Context ModelAmr E. Mohamed
System modeling is the process of developing abstract models of a system using graphical notations like the Unified Modeling Language (UML) to represent different views of a system. Models help analysts understand system functionality and communicate with customers. Models of existing and new systems are used during requirements engineering to clarify current systems, discuss strengths/weaknesses, and explain proposed requirements.
The document discusses several prescriptive software process models including:
1) The waterfall model which follows sequential phases from requirements to deployment but lacks iteration.
2) The incremental model which delivers functionality in increments with each phase repeated.
3) Prototyping which focuses on visible aspects to refine requirements through iterative prototypes and feedback.
4) The RAD (Rapid Application Development) model which emphasizes very short development cycles of 60-90 days using parallel teams and automated tools. The document provides descriptions and diagrams of each model.
Object-oriented analysis and design (OOAD) is a popular approach for analyzing, designing, and developing applications using the object-oriented paradigm. It involves modeling a system as a group of interacting objects at various levels of abstraction. Key concepts in OOAD include objects, classes, attributes, methods, encapsulation, inheritance, polymorphism, and relationships like association, aggregation, and composition. Common OOAD techniques include use case diagrams, which show interactions between actors and the system, and class diagrams, which describe the structure and behavior of system objects and their relationships.
Component-based software engineering (CBSE) is a process that emphasizes designing and building computer systems using reusable software components. It focuses on integrating existing components rather than developing everything from scratch. A key benefit of CBSE is reducing development time and costs by leveraging reusable components. The CBSE process involves requirements specification, component analysis, system design using existing components, development and integration of components, and system validation. CBSE aims to increase quality, productivity, and shorten development time by facilitating reuse of well-tested components.
This document provides an overview of distributed systems and distributed computing paradigms. It defines distributed systems as a collection of independent computers that can communicate with each other over a network. It discusses several distributed computing paradigms including message passing, client-server, peer-to-peer, publish/subscribe, remote procedure call (RPC), collaborative applications, and mobile agents. For each paradigm, it provides examples and explanations of how the paradigm works.
This document provides an overview of a lab on software architecture. It includes slides on introductory concepts of software architecture, architectural styles, analysis methods, and modeling notations. It also presents a case study on designing an architecture for a fire detection and response system and discusses views, decisions, requirements, and quality attributes to consider.
The document discusses the Architecture Business Cycle (ABC), which describes the relationships between a system's architecture, its environment, and the factors that influence both. The ABC is a cycle of influences between the architecture and various technical, business, and social environments. It shows how architectures are shaped by stakeholders, the developing organization, the architect's experience, and the technical environment. In turn, architectures influence the organization's structure and goals, customer requirements, and the architect's experience on subsequent systems. The cycle represents how organizational goals and requirements inform the architecture, which then informs the developed systems and feeds back to influence the organization.
Architecture design in software engineeringPreeti Mishra
The document discusses software architectural design. It defines architecture as the structure of a system's components, their relationships, and properties. An architectural design model is transferable across different systems. The architecture enables analysis of design requirements and consideration of alternatives early in development. It represents the system in an intellectually graspable way. Common architectural styles structure systems and their components in different ways, such as data-centered, data flow, and call-and-return styles.
This document discusses software architecture from both a management and technical perspective. From a management perspective, it defines an architecture as the design concept, an architecture baseline as tangible artifacts that satisfy stakeholders, and an architecture description as a human-readable representation of the design. It also notes that mature processes, clear requirements, and a demonstrable architecture are important for predictable project planning. Technically, it describes Philippe Kruchten's model of software architecture, which includes use case, design, process, component, and deployment views that model different aspects of realizing a system's design.
The document discusses architectural design for software systems. It covers topics such as software architecture, data design, architectural styles, analyzing architectural alternatives, and mapping requirements to architectural designs. The key aspects are:
1) Architectural design represents the structure of data and program components to build a computer system. It begins with data design and derives architectural representations.
2) Software architecture allows analysis of design effectiveness and consideration of alternatives to reduce risks.
3) Common architectural styles include data-centered, data flow, call-and-return, object-oriented, and layered styles.
4) Requirements are mapped to architectural designs through techniques like transform mapping and transaction mapping. The resulting design is then refined.
Architectural Design in Software Engineering SE10koolkampus
The document introduces architectural design and discusses its importance in establishing the overall structure of a software system. It explains that multiple models are required to document a software architecture and describes common types of architectural models, including static, dynamic, interface, relationships, and domain-specific models. The document also discusses advantages of explicit architecture, the architectural design process, subsystems and modules, architectural styles, and attributes like performance, security, safety, availability, and maintainability.
This ppt covers the following topics
Software quality
A framework for product metrics
A product metrics taxonomy
Metrics for the analysis model
Metrics for the design model
Metrics for maintenance
The document discusses key concepts in software design including abstraction, architecture, patterns, modularity, information hiding, and functional independence. It explains that software design is an iterative process that transforms requirements into a blueprint for constructing the software through design models, data structures, system architecture, interfaces, and components. Good software design exhibits qualities like being bug-free, suitable for its intended purpose, and a pleasurable user experience.
The document discusses five parameters for improving software economics: reducing complexity, improving processes, using skilled personnel, using better tools, and adjusting quality thresholds. It focuses on reducing size through components, reuse, languages, and modeling. Improving processes involves optimizing activities at the meta, macro, and micro levels. Using skilled personnel and effective teams is important. Automation through tools can improve productivity by 20-40%. Achieving quality involves requirements management, architecture, configuration control, and testing.
The document discusses software architecture, where it comes from, and what it is. Architectures are influenced by system stakeholders and their requirements, the developing organization, and the architects' experience. An architecture defines elements, their relationships, and properties. It is important because it represents early design decisions, dictates implementation, organizational structure, and quality attributes. Architectural patterns, reference models, and reference architectures capture common architectural elements but are not full architectures themselves.
This Presentation contains all the topics in design concept of software engineering. This is much more helpful in designing new product. You have to consider some of the design concepts that are given in the ppt
Unit 5- Architectural Design in software engineering arvind pandey
This document provides an overview of architectural design for software systems. It discusses topics like system organization, decomposition styles, and control styles. The key aspects covered are:
1. Architectural design identifies the subsystems, framework for control/communication, and is described in a software architecture.
2. Common decisions include system structure, distribution, styles, decomposition, and control strategy. Models are used to document the design.
3. Organization styles include repository (shared data), client-server (shared services), and layered (abstract machines). Decomposition can be through objects or pipelines. Control can be centralized or event-based.
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.
This document provides an overview of software maintenance. It discusses that software maintenance is an important phase of the software life cycle that accounts for 40-70% of total costs. Maintenance includes error correction, enhancements, deletions of obsolete capabilities, and optimizations. The document categorizes maintenance into corrective, adaptive, perfective and preventive types. It also discusses the need for maintenance to adapt to changing user requirements and environments. The document describes approaches to software maintenance including program understanding, generating maintenance proposals, accounting for ripple effects, and modified program testing. It discusses challenges like lack of documentation and high staff turnover. The document also introduces concepts of reengineering and reverse engineering to make legacy systems more maintainable.
This document provides an overview of the Cost Benefit Analysis Method (CBAM) for analyzing architectural decisions. CBAM considers both the technical impacts of decisions as well as the associated costs and financial benefits. It involves stakeholders prioritizing scenarios, assigning utility values to quality attributes, developing architectural strategies to address scenarios, and calculating the costs and benefits of strategies to determine the highest return on investment. The process is iterative, with the second iteration incorporating uncertainty through risk assessment. CBAM aims to help organizations optimally allocate resources by selecting strategies that maximize financial gains and minimize risks.
The document discusses factors related to software project size and effort. It provides the following key points:
1) Software development and maintenance can account for a significant portion of economic activity, with estimates that it will account for 12.5% of the US GDP by 1990.
2) Most effort is spent on maintenance rather than development, with estimates that maintenance accounts for 60-90% of total effort.
3) Software project size is categorized based on factors like number of programmers, duration, lines of code, and interactions/complexity. These range from trivial single-programmer projects to extremely large projects involving thousands of programmers over 5-10 years.
4) A 1964 study found that programmers only spent
SE_Lec 05_System Modelling and Context ModelAmr E. Mohamed
System modeling is the process of developing abstract models of a system using graphical notations like the Unified Modeling Language (UML) to represent different views of a system. Models help analysts understand system functionality and communicate with customers. Models of existing and new systems are used during requirements engineering to clarify current systems, discuss strengths/weaknesses, and explain proposed requirements.
The document discusses several prescriptive software process models including:
1) The waterfall model which follows sequential phases from requirements to deployment but lacks iteration.
2) The incremental model which delivers functionality in increments with each phase repeated.
3) Prototyping which focuses on visible aspects to refine requirements through iterative prototypes and feedback.
4) The RAD (Rapid Application Development) model which emphasizes very short development cycles of 60-90 days using parallel teams and automated tools. The document provides descriptions and diagrams of each model.
Object-oriented analysis and design (OOAD) is a popular approach for analyzing, designing, and developing applications using the object-oriented paradigm. It involves modeling a system as a group of interacting objects at various levels of abstraction. Key concepts in OOAD include objects, classes, attributes, methods, encapsulation, inheritance, polymorphism, and relationships like association, aggregation, and composition. Common OOAD techniques include use case diagrams, which show interactions between actors and the system, and class diagrams, which describe the structure and behavior of system objects and their relationships.
Component-based software engineering (CBSE) is a process that emphasizes designing and building computer systems using reusable software components. It focuses on integrating existing components rather than developing everything from scratch. A key benefit of CBSE is reducing development time and costs by leveraging reusable components. The CBSE process involves requirements specification, component analysis, system design using existing components, development and integration of components, and system validation. CBSE aims to increase quality, productivity, and shorten development time by facilitating reuse of well-tested components.
This document provides an overview of distributed systems and distributed computing paradigms. It defines distributed systems as a collection of independent computers that can communicate with each other over a network. It discusses several distributed computing paradigms including message passing, client-server, peer-to-peer, publish/subscribe, remote procedure call (RPC), collaborative applications, and mobile agents. For each paradigm, it provides examples and explanations of how the paradigm works.
This document provides an overview of a lab on software architecture. It includes slides on introductory concepts of software architecture, architectural styles, analysis methods, and modeling notations. It also presents a case study on designing an architecture for a fire detection and response system and discusses views, decisions, requirements, and quality attributes to consider.
This document provides 20 examples of domain-specific modeling covering various target languages, design tasks, and users. It discusses how domain-specific modeling works by focusing on a narrow area of interest using modeling concepts familiar to users. Models operate at the right level of abstraction rather than visualizing code. Generators produce just the needed code from models to create efficient full applications without manual coding or round-tripping issues. Generators can link to existing code, libraries, and platforms while producing output in various languages.
This document provides a summary of key topics from Microsoft's Application Architecture Guide, including definitions of software architecture, its importance, goals and principles. It covers common architectural styles, inputs/outputs of the design process, guidelines for layered designs including presentation, business, data and service layers. It also summarizes common application archetypes like web, rich client, mobile and service-oriented applications, and provides considerations for designing each type.
Domain Driven Design (DDD) is a topic that's been gaining a lot of popularity in both the Java and .NET camps recently. Entities, value types, repositories, bounded contexts and anti-corruption layers -- find out what all the buzz is about, and how establishing a domain model can help you combat complexity in your code.
Richard Dingwall is a .NET developer and blogger with a passion for architecture and maintainable code.
He is currently working at Provoke Solutions as lead developer on a six-month project introducing test-driven development (TDD) and domain-driven design (DDD) to a large ASP.NET ERP system.
An hour-long talk given at Wellington .NET user group, Sept 23 2009.
Software Architecture Recovery: The 5 Questions You Always Asked Yourself Abo...mircea.lungu
The document discusses software architecture recovery (SAR), which involves uncovering a system's architecture from available information such as source code, documentation, and runtime behavior. It addresses common questions about SAR, including what it is, why it is important, how it works, who performs it, and future directions. SAR is described as an important process for understanding existing system architectures that may have eroded over time due to changes and evolution. Both bottom-up and top-down approaches to SAR are covered, along with specific tools that support each approach.
This document discusses architectural design and software architecture. It covers topics like architectural design decisions, system organization styles, decomposition styles, control styles, and reference architectures. The objectives are to introduce architectural design, explain important decisions, and discuss styles for organizing, decomposing, and controlling systems. Examples and characteristics of different architectural patterns are provided.
The document discusses different types of computer network architectures and topologies. It describes peer-to-peer networks and client/server networks, and notes advantages and disadvantages of each. The document also covers different network topologies like bus, star, ring, and mesh, and the pros and cons of each. Finally, it discusses the differences between workgroup and domain network models.
Architectural styles and patterns provide abstract frameworks for structuring systems and solving common problems. [1] An architectural style defines rules for how components interact and is characterized by aspects like communication, deployment, structure, and domain. [2] Examples include service-oriented architecture, client/server, and layered architecture. [3] Similarly, architectural patterns are reusable solutions to recurring design problems documented with elements, relationships, constraints, and interaction mechanisms.
This is a lecture about Software Architecture Styles, part of the Advanced Software Engineering course, at the University of L'Aquila, Italy (www.di.univaq.it/muccini/SE+/2012)
The document defines distributed and parallel systems. A distributed system consists of independent computers that communicate over a network to collaborate on tasks. It has features like no common clock and increased reliability. Examples include telephone networks and the internet. Advantages are information sharing and scalability, while disadvantages include difficulty developing software and security issues. A parallel system uses multiple processors with shared memory to solve problems. Examples are supercomputers and server clusters. Advantages are concurrency and saving time, while the main disadvantage is lack of scalability between memory and CPUs.
This chapter introduces state diagrams and their components. It discusses how state diagrams describe the states of an object and transitions between states triggered by events. It covers initial and final states, actions, activities, and different types of events. The chapter also discusses transitions between states and the use of guard conditions. Finally, it introduces concepts like substates, concurrent state diagrams, and ways for orthogonal components to communicate in concurrent state models.
THIS PPT SHOWS A SHORT JIST ON HOW ARCHITECTURE STYLES HAS BEEN EVOLVED FROM PREHISTORIC TO MODERN CONCEPTS.THOUGH IT IS START UP WORK I THINK THIS WILL BE HELPFUL FOR STUDENTS WHO ARE IN THE FIELD.SUGGESTIONS ARE WELCOMED
This document provides an introduction to software architecture concepts. It defines key terms like software architecture, architectural styles, patterns, elements and stakeholders.
It describes software architecture as the set of principal design decisions about a system. The main elements are components, connectors and configuration. Architectural styles and patterns provide general and specific design decisions to organize systems. Models are used to capture architectural designs. Architecture influences various software development processes. Stakeholders in architecture include architects, developers, testers, managers and users.
The document provides an overview of managing information systems projects. It discusses the skills required to be an effective project manager and the key phases in project management: initiation, planning, execution, and closedown. During initiation, a project team is established and the scope and objectives are defined. Planning involves breaking the project into tasks, estimating resources and schedules, and developing communication plans. Execution refers to carrying out the planned tasks while monitoring progress. Closedown involves documentation, reviews, and closing out the project contract.
The three common software architecture styles commonly used in distributed systems and XML Web Services are compared and contrasted. In particular, the key differences between traditional SOAP and REST styles are explored. Guidelines are presented on which style is most applicable for certain application scenarios, and when a combination of styles is necessary.
A presentation on layered software architecture that goes through logical layering and physical layering, the difference between those two and a practical example.
Distributed systems allow independent computers to appear as a single coherent system by connecting them through a middleware layer. They provide advantages like increased reliability, scalability, and sharing of resources. Key goals of distributed systems include resource sharing, openness, transparency, and concurrency. Common types are distributed computing systems, distributed information systems, and distributed pervasive systems.
This document provides an overview of hacking, including its history, definitions, types, famous hackers, reasons for hacking, and advice on security and ethics. Hacking emerged in the 1960s at MIT and refers to attempting to gain unauthorized access to computer systems. It describes hackers as those who exploit weaknesses in computers. Different types of hacking are outlined such as website, network, password, and computer hacking. Advice is given around using strong unique passwords, backing up data, and contacting authorities if hacked. Both advantages like security testing and disadvantages like privacy harm are discussed.
The document discusses software architecture in the context of model-driven software development (MDSD). It defines key MDSD concepts like target architecture, domain architecture, and transformation architecture. It also covers what constitutes a sound architecture, how to arrive at one through patterns and styles, and important building blocks like frameworks, middleware, and components. The document discusses balancing the MDSD domain and platform, architecture conformance, viewpoints in modeling architectures, and implementing components. It relates MDSD concepts to service-oriented architecture (SOA) and business process management (BPM).
The document discusses key concepts in software design including the design process, design models, translating requirements to design, and quality attributes. It describes how design brings together requirements, business needs, and technical considerations to provide a blueprint for software construction. The design model includes data structures, architecture, interfaces, and components. Translating requirements involves creating class, architectural, interface, and component designs. Quality is assessed based on functionality, usability, reliability, performance, and other attributes.
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.
This document provides an introduction to software architecture. It discusses what software architecture is, popular architecture styles, quality attributes of a system, and architecture design guidelines. The key points are:
- Software architecture is the high-level design of a system that guides its construction and development. It defines the relationship between major structural elements.
- Popular architecture styles include layered, pipes and filters, and event-based. Each style has advantages and disadvantages for certain quality attributes.
- Quality attributes include implementation attributes like maintainability, runtime attributes like performance and availability, and business attributes like time to market. There are often tradeoffs between attributes.
- Architecture design guidelines include thinking about requirements before design, using abstraction, considering non-
software design is very crusial thing to manage therfore software 'software design is very crusial thing to manage therfore software software design is very crusial thing to manage therfore software software design is very crusial thing to manage therfore software
Software Archtecture.
Software design is a process to transform user requirements into some suitable form, which helps the programmer in software coding and implementation.
Software design is the important step in SDLC (Software Design Life Cycle), which moves the concentration from problem domain to solution domain. It tries to specify how to fulfill the requirements mentioned in SRS.
Software design plays an important role in developing software: during software design, software engineers produce various models that form a kind of blueprint of the solution to be implemented
[2015/2016] Introduction to software architectureIvano Malavolta
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.infn.it/.
http://www.ivanomalavolta.com
Evolution of Modelling Techniques for Service Oriented ArchitectureIJERA Editor
Service-oriented architecture (SOA) is a software design and architecture design pattern based on independent pieces of software providing functionality as services to other applications. The benefit of SOA in the IT infrastructure is to allow parallel use and data exchange between programs which are services to the enterprise. Unified Modelling Language (UML) is a standardized general-purpose modelling language in the field of software engineering. The UML includes a set of graphic notation techniques to create visual models of object-oriented software systems. We want to make UML available for SOA as well. SoaML (Service oriented architecture Modelling Language) is an open source specification project from the Object Management Group (OMG), describing a UML profile and meta-model for the modelling and design of services within a service-oriented architecture. BPMN was also extended for SOA but there were few pitfalls. There is a need of a modelling framework which dedicated to SOA. Michael Bell authored a framework called Service Oriented Modelling Framework (SOMF) which is dedicated for SOA.
The document discusses software architecture, including its definition, types of architectures, views, and documentation. It defines software architecture as the fundamental organization of a system, including its components, relationships, and design principles. The document outlines different types of architectures like business, technical, and enterprise architectures. It also discusses common architecture views used in frameworks like RUP, RM-ODP, and DODAF. Finally, it covers architecture documentation and modeling techniques.
The document discusses key concepts in design modeling for software engineering projects, including:
- Data/class design transforms analysis models into design class structures and data structures.
- Architectural design defines relationships between major software elements and how they interact.
- Interface, component, and other designs further refine elements from analysis into implementation-specific details.
- Design principles include traceability to analysis, avoiding reinventing solutions, and structuring for change and graceful degradation.
The document discusses various aspects of design modeling for software engineering projects. It describes how the design model builds upon the analysis model by refining and adding more implementation details to elements like data design, architectural design, interface design, and component design. It also covers important design concepts like abstraction, architecture, patterns, modularity, information hiding, and functional independence. Quality guidelines for software design are provided along with principles of object-oriented design.
Presentation "Interface Management in Concurrent Engineering Facilities for Systems and Service Systems Engineering: A Model-‐based Approach" at CIISE 2014 -‐ Conferenza INCOSE Italia su Systems Engineering
Roma, 24 -‐ 25 Novembre 2014
This document provides an introduction to software architecture design. It discusses key concepts like the relationship between requirements and architecture, architecture styles, quality attributes, and tradeoff analysis. The document is divided into multiple parts that cover topics such as an overview of software architecture, common architecture styles, quality attributes, and some rules of thumb for architecture design.
The document discusses service-oriented computing concepts including service-oriented architecture (SOA), service-oriented analysis and design, SOA characteristics, and SOA certifications. It provides an overview of key SOA concepts such as loose coupling, reusability, and autonomy. It also summarizes SOA goals like increased agility, interoperability, and return on investment. Sample exam questions are included to help understand SOA fundamentals.
This document discusses software design principles and activities. It notes that requirements analysis should minimize design assumptions while ensuring consistency with technology. Analysis and design are interwoven. Design models refine analysis models with more implementation details. Design engineering starts with data/class design and includes architectural, interface, and component level design. The design must implement requirements and accommodate implicit needs while being understandable. A good design exhibits recognizable architecture and patterns, modularity, and distinct data, architecture, interface and component representations.
Lecture # 8 software design and architecture (SDA).pptesrabilgic2
This document provides an overview of software design and architecture. It discusses major areas of concern like data, architecture, interface, and component design. Good design is the foundation for quality software and should implement requirements, be readable, and provide a complete implementation picture. General guidelines include using design patterns and logically partitioning components. Key principles are avoiding tunnel vision and reviewing design. The design process transforms analysis models into data structures, program structure, interfaces, and procedural details through techniques like abstraction, modularity, hierarchy, and information hiding.
This document compares the J2EE and .NET platforms using a separation continuum model. It defines key terms related to J2EE, .NET, and distributed application architectures. The document outlines a logical tier model and a service-based architecture model for conceptualizing large distributed solutions. It aims to map the technologies provided by J2EE and .NET to the separation continuum for analysis and comparison.
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.infn.it/.
http://www.ivanomalavolta.com
"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...Infopitaara
A Boiler Feed Pump (BFP) is a critical component in thermal power plants. It supplies high-pressure water (feedwater) to the boiler, ensuring continuous steam generation.
⚙️ How a Boiler Feed Pump Works
Water Collection:
Feedwater is collected from the deaerator or feedwater tank.
Pressurization:
The pump increases water pressure using multiple impellers/stages in centrifugal types.
Discharge to Boiler:
Pressurized water is then supplied to the boiler drum or economizer section, depending on design.
🌀 Types of Boiler Feed Pumps
Centrifugal Pumps (most common):
Multistage for higher pressure.
Used in large thermal power stations.
Positive Displacement Pumps (less common):
For smaller or specific applications.
Precise flow control but less efficient for large volumes.
🛠️ Key Operations and Controls
Recirculation Line: Protects the pump from overheating at low flow.
Throttle Valve: Regulates flow based on boiler demand.
Control System: Often automated via DCS/PLC for variable load conditions.
Sealing & Cooling Systems: Prevent leakage and maintain pump health.
⚠️ Common BFP Issues
Cavitation due to low NPSH (Net Positive Suction Head).
Seal or bearing failure.
Overheating from improper flow or recirculation.
π0.5: a Vision-Language-Action Model with Open-World GeneralizationNABLAS株式会社
今回の資料「Transfusion / π0 / π0.5」は、画像・言語・アクションを統合するロボット基盤モデルについて紹介しています。
拡散×自己回帰を融合したTransformerをベースに、π0.5ではオープンワールドでの推論・計画も可能に。
This presentation introduces robot foundation models that integrate vision, language, and action.
Built on a Transformer combining diffusion and autoregression, π0.5 enables reasoning and planning in open-world settings.
We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefly present the key mathematical tools on the basis of GP modeling (a.k.a. Kriging), as well as the associated theoretical and computational framework. We then provide an extensive overview of the available features of the software and demonstrate its flexibility and user-friendliness. Finally, we showcase the usage and the performance of the software on several applications borrowed from different fields of engineering. These include a basic surrogate of a well-known analytical benchmark function; a hierarchical Kriging example applied to wind turbine aero-servo-elastic simulations and a more complex geotechnical example that requires a non-stationary, user-defined correlation function. The GP-module, like the rest of the scientific code that is shipped with UQLab, is open source (BSD license).
Fluid mechanics is the branch of physics concerned with the mechanics of fluids (liquids, gases, and plasmas) and the forces on them. Originally applied to water (hydromechanics), it found applications in a wide range of disciplines, including mechanical, aerospace, civil, chemical, and biomedical engineering, as well as geophysics, oceanography, meteorology, astrophysics, and biology.
It can be divided into fluid statics, the study of various fluids at rest, and fluid dynamics.
Fluid statics, also known as hydrostatics, is the study of fluids at rest, specifically when there's no relative motion between fluid particles. It focuses on the conditions under which fluids are in stable equilibrium and doesn't involve fluid motion.
Fluid kinematics is the branch of fluid mechanics that focuses on describing and analyzing the motion of fluids, such as liquids and gases, without considering the forces that cause the motion. It deals with the geometrical and temporal aspects of fluid flow, including velocity and acceleration. Fluid dynamics, on the other hand, considers the forces acting on the fluid.
Fluid dynamics is the study of the effect of forces on fluid motion. It is a branch of continuum mechanics, a subject which models matter without using the information that it is made out of atoms; that is, it models matter from a macroscopic viewpoint rather than from microscopic.
Fluid mechanics, especially fluid dynamics, is an active field of research, typically mathematically complex. Many problems are partly or wholly unsolved and are best addressed by numerical methods, typically using computers. A modern discipline, called computational fluid dynamics (CFD), is devoted to this approach. Particle image velocimetry, an experimental method for visualizing and analyzing fluid flow, also takes advantage of the highly visual nature of fluid flow.
Fundamentally, every fluid mechanical system is assumed to obey the basic laws :
Conservation of mass
Conservation of energy
Conservation of momentum
The continuum assumption
For example, the assumption that mass is conserved means that for any fixed control volume (for example, a spherical volume)—enclosed by a control surface—the rate of change of the mass contained in that volume is equal to the rate at which mass is passing through the surface from outside to inside, minus the rate at which mass is passing from inside to outside. This can be expressed as an equation in integral form over the control volume.
The continuum assumption is an idealization of continuum mechanics under which fluids can be treated as continuous, even though, on a microscopic scale, they are composed of molecules. Under the continuum assumption, macroscopic (observed/measurable) properties such as density, pressure, temperature, and bulk velocity are taken to be well-defined at "infinitesimal" volume elements—small in comparison to the characteristic length scale of the system, but large in comparison to molecular length scale
ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai
With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to
understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes
the answer to interpreting the decision-making process that AI malware analysis models use to determine
malicious benign samples to gain trust that in a production environment, the system is able to catch
malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI
as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in
many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to
conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to
balance explainability with security. Following this framework, designing a machine with an AI malware
detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its
decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on
choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique,
implementing AdvXAI defensive measures, and continually evaluating the model. This framework will
significantly contribute to automated malware detection and XAI efforts allowing for secure systems that
are resilient to adversarial attacks.
Concept of Problem Solving, Introduction to Algorithms, Characteristics of Algorithms, Introduction to Data Structure, Data Structure Classification (Linear and Non-linear, Static and Dynamic, Persistent and Ephemeral data structures), Time complexity and Space complexity, Asymptotic Notation - The Big-O, Omega and Theta notation, Algorithmic upper bounds, lower bounds, Best, Worst and Average case analysis of an Algorithm, Abstract Data Types (ADT)
Lidar for Autonomous Driving, LiDAR Mapping for Driverless Cars.pptxRishavKumar530754
LiDAR-Based System for Autonomous Cars
Autonomous Driving with LiDAR Tech
LiDAR Integration in Self-Driving Cars
Self-Driving Vehicles Using LiDAR
LiDAR Mapping for Driverless Cars
This paper proposes a shoulder inverse kinematics (IK) technique. Shoulder complex is comprised of the sternum, clavicle, ribs, scapula, humerus, and four joints.
The role of the lexical analyzer
Specification of tokens
Finite state machines
From a regular expressions to an NFA
Convert NFA to DFA
Transforming grammars and regular expressions
Transforming automata to grammars
Language for specifying lexical analyzers
In tube drawing process, a tube is pulled out through a die and a plug to reduce its diameter and thickness as per the requirement. Dimensional accuracy of cold drawn tubes plays a vital role in the further quality of end products and controlling rejection in manufacturing processes of these end products. Springback phenomenon is the elastic strain recovery after removal of forming loads, causes geometrical inaccuracies in drawn tubes. Further, this leads to difficulty in achieving close dimensional tolerances. In the present work springback of EN 8 D tube material is studied for various cold drawing parameters. The process parameters in this work include die semi-angle, land width and drawing speed. The experimentation is done using Taguchi’s L36 orthogonal array, and then optimization is done in data analysis software Minitab 17. The results of ANOVA shows that 15 degrees die semi-angle,5 mm land width and 6 m/min drawing speed yields least springback. Furthermore, optimization algorithms named Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithm (GA) are applied which shows that 15 degrees die semi-angle, 10 mm land width and 8 m/min drawing speed results in minimal springback with almost 10.5 % improvement. Finally, the results of experimentation are validated with Finite Element Analysis technique using ANSYS.
15th International Conference on Computer Science, Engineering and Applicatio...IJCSES Journal
Domain specific Software Architecture
2. INTRODUCTION TO DSSA
DSSA is basically ‘Software Architecture focused on a
particular domain.’
Why is it focused to a particular domain?
a) To constraint the problem space
b) Facilitate focused development
DSSA is a collection of structures of the system which
comprise of:
a) Software elements
b) Externally visible properties of those elements
c) Relationship among those components
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
3. Applications of DSSA
The process of
developing and
implementing
a DSSA is
called domain
engineering.
The process of
developing an
application
based on a
DSSA is called
application
engineering.
D
S
S
A
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
4. Problem Space & Solution Space
.
.
..
.
Problem Space
General Solution Space
Problem Space
divided as per the domain
.
.
.
.
?
General Solution Space
divided as per the domain
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
5. DSSA Components
(Classification of requirements)
Domain Model
• Defines the behaviour of applications in the system.
• Standardizes the domain terminologies & provides the system data flow.
• Provides standardized descriptions of problems to be solved in the domain.
Reference
Requirements
• Supports the design of the reference architecture.
• Divides the customers requirement into functional and non-functional
components.
• The requirements may be mandatory, optional or variable.
Reference
Architecture
• Describes a general computational framework.
• Represents a set of principal design decisions simultaneously applicable to
multiple related systems.
• Includes explicitly defined points of variation.
(Collect info. about the domain)
(Develop a generalized framework)
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
8. Main Advantages of DSSA
• The overall cost is minimized as the
assets can be reused.
• The market share of the
organization can be increased by
developing related applications for
different users.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
10. Domain Model
Before the requirements can be determined, it is
necessary to understand the characteristics of the
system.
Domain model:
Defines the behaviour of applications in the
system
Standardizes the domain terminologies &
provides the system data flow.
Provides standardized descriptions of problems
to be solved in the domain.
Provides the vocabulary to formulate the
reference requirements.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
11. Components of the Domain Model
Scenarios
Domain Dictionary
Context/Block Diagram
Entity-Relationship Diagram
Object Model
Data Flow Model
State Transition Models
Information
model
Operational
model
Feature model
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
12. Scenario
Scenarios are a list of events which are helpful in
eliciting the requirements from the customer in an
informal manner.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
13. Domain Dictionary
It consists of the explanation of the terms used in
the scenarios and the customer needs statement.
Example:
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
14. Context Information Diagram
It describes the high-level data flow between
the major components in the system.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
16. Object diagram
An object-oriented approach is followed to identify
the objects which are mentioned along with their
attributes and operations.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
17. Data-Flow Diagram
It focuses on the data exchanged within the
system, with no notion of control.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
18. State-Transition Diagram
It describes the events and states that take
place in the domain.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
20. Reference Requirements
Reference requirements are responsible for identifying
the portion of solution space that the domain model
(problem space) will map into.
Reference Requirements:
Support the design of the reference architecture.
Divides the customers requirement into functional
and non-functional components.
The requirements may be mandatory, optional or
variable.
Constrains the architecture and the implementation.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
27. Reference Architecture Perquisites
There are no predefined standards for designing the
reference architecture
• This is one of the reasons, that it is supported by an extensive
documentation.
Architecture does not define implementation
• The architecture establishes constraints on downstream activities,
and those activities must produce finer-grained designs and code
that are compliant with the architecture.
Architecture is design but not all design is architecture
• There are many design decisions that are left unbound by the
architecture, and are happily left to the discretion and good
judgment of downstream designers and implementers.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
28. Reference Architecture Perquisites
‘Design’ is a general term, don’t confuse it
with ‘System Design’ , which refers to the in-
depth view of the structure of the system.
An ‘architecture’ is a reusable design and a
‘reference architecture’ is a reusable design
for a family of systems in a particular domain.
Reference Architecture Model can also be
called as the architectural style of the system
which may be layered, pipe and filter etc.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
29. Reference Architecture
It is a generic architecture focused on
fundamental abstractions of the domain.
• Describes a general computational
framework based on the chosen
architectural style.
• Represents a set of principal design
decisions simultaneously applicable to
multiple related systems.
• Includes explicitly defined points of
variation.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
30. Architecture Hierarchy
Reference
Architecture
• First, a
generalized
architecture
is selected.
Application
Specific
Architecture
• Using the reference architecture,
an application specific
architecture is created.
Implementation
• The
implementation
of the
architecture is
carried out.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
31. Components of Reference Architecture
Reference Architecture Model
Configuration Decision Tree
Architecture Schema
Dependency Diagram
Component Interface Description
Constraints
Rationale
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
32. Reference Architecture Model
All designs start out with some simple
abstraction based on the architecture style.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
33. Configuration Decision Tree
A subset of reference requirements is chosen and
a configuration decision tree is made accordingly.
Configuration is done at reference architecture
instantiation time.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
34. Architecture Schema
Name/Type
Description
Reference
requirements satisfied
Data flow and control
flow diagrams
Design rationale
Interface and architecture
specifications and
dependencies
It is a collection point for knowledge about the components that
make up a DSSA.
All such details
are to be listed
for every
component
involved.GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
35. Dependency Diagram
The reference architecture dependency diagram reveals
component connections at a level of granularity reflecting
the architectural style chosen by the system architect.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
36. Component Interface Description
The focus is on, how elements interact with their environments, not on how
elements are implemented. An Interface Description Language(IDL) is used
to describe the interface as per the syntax of the language chosen.
Ex: LILENNA
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
37. Constraints
Constraints are the ranges of parameter
values, relationships between parameter
values or components etc. which have to be
considered throughout the development of
a system.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]
38. Rationale
Rationales capture the motivation behind various
decisions, such as the partitioning of the system
into discrete elements and the formation of the
architecture in terms of connecting elements.
Rationales are inferences that can be structured as
an argument with the design decision being the
conclusion.
GNDU, Amritsar [M.Tech. Software Systems 2012-2014 batch]