The document discusses different software engineering process models including:
1. The waterfall model which is a linear sequential model where each phase must be completed before moving to the next.
2. Prototyping models which allow requirements to be refined through building prototypes.
3. RAD (Rapid Application Development) which emphasizes short development cycles through reuse and code generation.
4. Incremental models which deliver functionality in increments with early increments focusing on high priority requirements.
5. The spiral model which has multiple iterations of planning, risk analysis, engineering and evaluation phases.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
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
Risk management involves identifying potential problems, assessing their likelihood and impacts, and developing strategies to address them. There are two main risk strategies - reactive, which addresses risks after issues arise, and proactive, which plans ahead. Key steps in proactive risk management include identifying risks through checklists, estimating their probability and impacts, developing mitigation plans, monitoring risks and mitigation effectiveness, and adjusting plans as needed. Common risk categories include project risks, technical risks, and business risks.
The document discusses staffing level estimation over the course of a software development project. It describes how the number of personnel needed varies at different stages: a small group is needed for planning and analysis, a larger group for architectural design, and the largest number for implementation and system testing. It also references models like the Rayleigh curve and Putnam's interpretation that estimate personnel levels over time. Tables show estimates for the distribution of effort, schedule, and personnel across activities for different project sizes. The key idea is that staffing requirements fluctuate throughout the software life cycle, with peaks during implementation and testing phases.
The document discusses requirements analysis and specification in software engineering. It defines what requirements are and explains the typical activities involved - requirements gathering, analysis, and specification. The importance of documenting requirements in a Software Requirements Specification (SRS) document is explained. Key sections of an SRS like stakeholders, types of requirements (functional and non-functional), and examples are covered. Special attention is given to requirements for critical systems and importance of non-functional requirements.
The document discusses the software design process. It begins by explaining that software design is an iterative process that translates requirements into a blueprint for constructing the software. It then describes the main steps and outputs of the design process, which include transforming specifications into design models, reviewing designs for quality, and producing a design document. The document also covers key concepts in software design like abstraction, architecture, patterns, modularity, and information hiding.
The document discusses the spiral model of software development. The spiral model is an iterative approach that combines prototyping and aspects of the waterfall model. It was defined by Barry Boehm in 1988 as a way to address risks through iterative evaluation and improvement of prototypes. The spiral model is best for medium to high risk projects where requirements are complex or expected to change. It involves evaluating prototypes, defining new prototypes based on learnings, and repeating this process until the final product is delivered.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
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
Risk management involves identifying potential problems, assessing their likelihood and impacts, and developing strategies to address them. There are two main risk strategies - reactive, which addresses risks after issues arise, and proactive, which plans ahead. Key steps in proactive risk management include identifying risks through checklists, estimating their probability and impacts, developing mitigation plans, monitoring risks and mitigation effectiveness, and adjusting plans as needed. Common risk categories include project risks, technical risks, and business risks.
The document discusses staffing level estimation over the course of a software development project. It describes how the number of personnel needed varies at different stages: a small group is needed for planning and analysis, a larger group for architectural design, and the largest number for implementation and system testing. It also references models like the Rayleigh curve and Putnam's interpretation that estimate personnel levels over time. Tables show estimates for the distribution of effort, schedule, and personnel across activities for different project sizes. The key idea is that staffing requirements fluctuate throughout the software life cycle, with peaks during implementation and testing phases.
The document discusses requirements analysis and specification in software engineering. It defines what requirements are and explains the typical activities involved - requirements gathering, analysis, and specification. The importance of documenting requirements in a Software Requirements Specification (SRS) document is explained. Key sections of an SRS like stakeholders, types of requirements (functional and non-functional), and examples are covered. Special attention is given to requirements for critical systems and importance of non-functional requirements.
The document discusses the software design process. It begins by explaining that software design is an iterative process that translates requirements into a blueprint for constructing the software. It then describes the main steps and outputs of the design process, which include transforming specifications into design models, reviewing designs for quality, and producing a design document. The document also covers key concepts in software design like abstraction, architecture, patterns, modularity, and information hiding.
The document discusses the spiral model of software development. The spiral model is an iterative approach that combines prototyping and aspects of the waterfall model. It was defined by Barry Boehm in 1988 as a way to address risks through iterative evaluation and improvement of prototypes. The spiral model is best for medium to high risk projects where requirements are complex or expected to change. It involves evaluating prototypes, defining new prototypes based on learnings, and repeating this process until the final product is delivered.
This document discusses several software design techniques: stepwise refinement, levels of abstraction, structured design, integrated top-down development, and Jackson structured programming. Stepwise refinement is a top-down technique that decomposes a system into more elementary levels. Levels of abstraction designs systems as layers with each level performing services for the next higher level. Structured design converts data flow diagrams into structure charts using design heuristics. Integrated top-down development integrates design, implementation, and testing with a hierarchical structure. Jackson structured programming maps a problem's input/output structures and operations into a program structure to solve the problem.
This document discusses common myths held by software managers, developers, and customers. It describes myths such as believing formal standards and procedures are sufficient, thinking new hardware means high quality development, adding people to late projects will help catch up, and outsourcing means relaxing oversight. Realities discussed include standards not being used effectively, tools being more important than hardware, adding people making projects later, and needing management and control of outsourced projects. Developer myths like thinking the job is done once code runs and quality can't be assessed until code runs are addressed. The document emphasizes the importance of requirements, documentation, quality processes, and addressing change impacts.
Software development process models
Rapid Application Development (RAD) Model
Evolutionary Process Models
Spiral Model
THE FORMAL METHODS MODEL
Specialized Process Models
The Concurrent Development Model
The document defines the software development life cycle (SDLC) and its phases. It discusses several SDLC models including waterfall, prototype, iterative enhancement, and spiral. The waterfall model follows sequential phases from requirements to maintenance with no overlap. The prototype model involves building prototypes for user feedback. The iterative enhancement model develops software incrementally. The spiral model is divided into risk analysis, engineering, construction, and evaluation cycles. The document also covers software requirements, elicitation through interviews and use cases, analysis through data, behavioral and functional modeling, and documentation in a software requirements specification.
Agile development focuses on effective communication, customer collaboration, and incremental delivery of working software. The key principles of agile development according to the Agile Alliance include satisfying customers, welcoming changing requirements, frequent delivery, collaboration between business and development teams, and self-organizing teams. Extreme Programming (XP) is an agile process model that emphasizes planning with user stories, simple design, pair programming, unit testing, and frequent integration and testing.
This document discusses various topics related to software design including design principles, concepts, modeling, and architecture. It provides examples of class/data design, architectural design, interface design, and component design. Some key points discussed include:
- Software design creates representations and models that provide details on architecture, data structures, interfaces, and components needed to implement the system.
- Design concepts like abstraction, modularity, encapsulation, and information hiding are important to reduce complexity and improve design.
- Different types of design models include data/class design, architectural design, interface design, and component-level design.
- Good software architecture and design lead to systems that are more understandable, maintainable, and of higher quality.
The document discusses software requirements and requirements engineering. It introduces concepts like user requirements, system requirements, functional requirements, and non-functional requirements. It explains how requirements can be organized in a requirements document and the different types of stakeholders who read requirements. The document also discusses challenges in writing requirements precisely and provides examples of requirements specification for a library system called LIBSYS.
The document discusses context models and their use in system modeling. Context models illustrate the operational context of a system by showing what lies outside its boundaries, including other systems in the environment. They help define a system's boundaries and show how IT applications fit into the context of people and organizations. Two examples are provided: (1) a Mental Health Care Patient Management System (MHC-PMS) and its connections to other clinical systems; (2) an Automated Teller Machine (ATM) and its links to banking systems. Context models on their own do not show relationships between external systems, so additional models are needed.
Black-box testing is a method of software testing that examines the functionality of an application based on the specifications.
White box testing is a testing technique, that examines the program structure and derives test data from the program logic/code
Following presentation answers:
- Why do we need evolution?
- What happens if we do not evolve the software?
- What are the types of software evolution?
- What are Lehman's laws
- What are the strategies for evolution?
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.
Evolutionary process models allow developers to iteratively create increasingly complete versions of software. Examples include the prototyping paradigm, spiral model, and concurrent development model. The prototyping paradigm uses prototypes to elicit requirements from customers. The spiral model couples iterative prototyping with controlled development, dividing the project into framework activities. The concurrent development model concurrently develops components with defined interfaces to enable integration. These evolutionary models allow flexibility and accommodate changes but require strong communication and updated requirements.
This document discusses agile software development methods. It outlines the agile manifesto which values individuals and interactions over processes, working software over documentation, and customer collaboration over contract negotiation. Some key agile principles include customer satisfaction, welcome changing requirements, and frequent delivery of working software. Common agile methods like extreme programming and scrum are also summarized. Advantages include improved customer satisfaction and responsiveness to change, while disadvantages include potential lack of documentation.
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.
What is Software project management?? , What is a Project?, What is a Product?, What is Project Management?, What is Software Project Life Cycle?, What is a Product Life Cycle?, Software Project, Software Triple Constraints, Software Project Manager, Project Planning,
software engineering notes for cse/it fifth semesterrajesh199155
The document provides an overview of software engineering principles and practices. It discusses:
1) The scope and necessity of software engineering to systematically develop large, complex software products. Without principles, developing large programs would be difficult and error-prone.
2) The "software crisis" caused by ineffective development leading to cost overruns and inefficient resource usage. Proper use of principles can help solve this.
3) The difference between a program developed by an individual and a commercial software product developed by a team for multiple users, requiring careful design, documentation and adherence to principles.
4) How early exploratory development styles focused on error correction after coding, while modern styles emphasize error prevention through defined stages like
System Models in Software Engineering SE7koolkampus
The document discusses various types of system models used in requirements engineering including context models, behavioral models, data models, object models, and how CASE workbenches support system modeling. It describes behavioral models like data flow diagrams and state machine models, data models like entity-relationship diagrams, and object models using the Unified Modeling Language. CASE tools can support modeling through features like diagram editors, repositories, and code generation.
This document discusses several software design techniques: stepwise refinement, levels of abstraction, structured design, integrated top-down development, and Jackson structured programming. Stepwise refinement is a top-down technique that decomposes a system into more elementary levels. Levels of abstraction designs systems as layers with each level performing services for the next higher level. Structured design converts data flow diagrams into structure charts using design heuristics. Integrated top-down development integrates design, implementation, and testing with a hierarchical structure. Jackson structured programming maps a problem's input/output structures and operations into a program structure to solve the problem.
This document discusses common myths held by software managers, developers, and customers. It describes myths such as believing formal standards and procedures are sufficient, thinking new hardware means high quality development, adding people to late projects will help catch up, and outsourcing means relaxing oversight. Realities discussed include standards not being used effectively, tools being more important than hardware, adding people making projects later, and needing management and control of outsourced projects. Developer myths like thinking the job is done once code runs and quality can't be assessed until code runs are addressed. The document emphasizes the importance of requirements, documentation, quality processes, and addressing change impacts.
Software development process models
Rapid Application Development (RAD) Model
Evolutionary Process Models
Spiral Model
THE FORMAL METHODS MODEL
Specialized Process Models
The Concurrent Development Model
The document defines the software development life cycle (SDLC) and its phases. It discusses several SDLC models including waterfall, prototype, iterative enhancement, and spiral. The waterfall model follows sequential phases from requirements to maintenance with no overlap. The prototype model involves building prototypes for user feedback. The iterative enhancement model develops software incrementally. The spiral model is divided into risk analysis, engineering, construction, and evaluation cycles. The document also covers software requirements, elicitation through interviews and use cases, analysis through data, behavioral and functional modeling, and documentation in a software requirements specification.
Agile development focuses on effective communication, customer collaboration, and incremental delivery of working software. The key principles of agile development according to the Agile Alliance include satisfying customers, welcoming changing requirements, frequent delivery, collaboration between business and development teams, and self-organizing teams. Extreme Programming (XP) is an agile process model that emphasizes planning with user stories, simple design, pair programming, unit testing, and frequent integration and testing.
This document discusses various topics related to software design including design principles, concepts, modeling, and architecture. It provides examples of class/data design, architectural design, interface design, and component design. Some key points discussed include:
- Software design creates representations and models that provide details on architecture, data structures, interfaces, and components needed to implement the system.
- Design concepts like abstraction, modularity, encapsulation, and information hiding are important to reduce complexity and improve design.
- Different types of design models include data/class design, architectural design, interface design, and component-level design.
- Good software architecture and design lead to systems that are more understandable, maintainable, and of higher quality.
The document discusses software requirements and requirements engineering. It introduces concepts like user requirements, system requirements, functional requirements, and non-functional requirements. It explains how requirements can be organized in a requirements document and the different types of stakeholders who read requirements. The document also discusses challenges in writing requirements precisely and provides examples of requirements specification for a library system called LIBSYS.
The document discusses context models and their use in system modeling. Context models illustrate the operational context of a system by showing what lies outside its boundaries, including other systems in the environment. They help define a system's boundaries and show how IT applications fit into the context of people and organizations. Two examples are provided: (1) a Mental Health Care Patient Management System (MHC-PMS) and its connections to other clinical systems; (2) an Automated Teller Machine (ATM) and its links to banking systems. Context models on their own do not show relationships between external systems, so additional models are needed.
Black-box testing is a method of software testing that examines the functionality of an application based on the specifications.
White box testing is a testing technique, that examines the program structure and derives test data from the program logic/code
Following presentation answers:
- Why do we need evolution?
- What happens if we do not evolve the software?
- What are the types of software evolution?
- What are Lehman's laws
- What are the strategies for evolution?
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.
Evolutionary process models allow developers to iteratively create increasingly complete versions of software. Examples include the prototyping paradigm, spiral model, and concurrent development model. The prototyping paradigm uses prototypes to elicit requirements from customers. The spiral model couples iterative prototyping with controlled development, dividing the project into framework activities. The concurrent development model concurrently develops components with defined interfaces to enable integration. These evolutionary models allow flexibility and accommodate changes but require strong communication and updated requirements.
This document discusses agile software development methods. It outlines the agile manifesto which values individuals and interactions over processes, working software over documentation, and customer collaboration over contract negotiation. Some key agile principles include customer satisfaction, welcome changing requirements, and frequent delivery of working software. Common agile methods like extreme programming and scrum are also summarized. Advantages include improved customer satisfaction and responsiveness to change, while disadvantages include potential lack of documentation.
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.
What is Software project management?? , What is a Project?, What is a Product?, What is Project Management?, What is Software Project Life Cycle?, What is a Product Life Cycle?, Software Project, Software Triple Constraints, Software Project Manager, Project Planning,
software engineering notes for cse/it fifth semesterrajesh199155
The document provides an overview of software engineering principles and practices. It discusses:
1) The scope and necessity of software engineering to systematically develop large, complex software products. Without principles, developing large programs would be difficult and error-prone.
2) The "software crisis" caused by ineffective development leading to cost overruns and inefficient resource usage. Proper use of principles can help solve this.
3) The difference between a program developed by an individual and a commercial software product developed by a team for multiple users, requiring careful design, documentation and adherence to principles.
4) How early exploratory development styles focused on error correction after coding, while modern styles emphasize error prevention through defined stages like
System Models in Software Engineering SE7koolkampus
The document discusses various types of system models used in requirements engineering including context models, behavioral models, data models, object models, and how CASE workbenches support system modeling. It describes behavioral models like data flow diagrams and state machine models, data models like entity-relationship diagrams, and object models using the Unified Modeling Language. CASE tools can support modeling through features like diagram editors, repositories, and code generation.
Software engineering Questions and AnswersBala Ganesh
1. Risk management is the process of identifying, addressing, and eliminating potential problems that could threaten the success of a project before they cause damage. This includes issues that could impact cost, schedule, technical success, product quality, or team morale.
2. HIPO (Hierarchical Input Process Output) diagrams were developed at IBM as a design representation and documentation aid. They contain a visual table of contents, overview diagrams, and detailed diagrams.
3. Software maintenance is any work done to modify software after it is operational, such as fixing errors, adding capabilities, removing obsolete code, or optimizing performance. It aims to preserve the software's value over time as requirements, users, and technology change. M
The document discusses state machine diagrams and state modeling in object-oriented software design. It defines states as abstractions of an object's attribute values and links that affect its behavior. State machine diagrams show an entity's different states and how it responds to events by transitioning between states. The characteristics of states and various state modeling concepts and notations in UML like composite states, submachine states, history states, and transitions are explained.
This document provides an overview of object oriented software modeling and design patterns. It discusses the purpose of design patterns in providing common solutions to recurring problems in software design. The document outlines different types of patterns (creational, structural, behavioral) and provides examples of specific patterns like factory pattern, singleton pattern, facade pattern, MVC pattern, observer pattern, and chain of responsibility pattern. It explains the problem each pattern addresses and the elements that make up the design solution.
The document discusses object oriented software modeling using the Unified Modeling Language (UML). It provides an overview of UML and describes several types of UML diagrams including use case diagrams, activity diagrams, class diagrams, interaction diagrams, and state diagrams. It also discusses UML concepts such as classes, objects, relationships between classes including generalization, association, aggregation and composition.
This document discusses dynamic analysis techniques for object-oriented software modeling and design. It describes three main steps: 1) Modeling external system behaviors by mapping use case scenarios to sequence diagrams. 2) Modeling communication among subsystems by organizing objects into subsystems and developing subsystem-level sequence diagrams. 3) Developing a reusable model-view-controller framework by creating detailed sequence diagrams involving boundary, control, and entity objects. The document provides examples and tips for applying these dynamic analysis techniques.
The document discusses developing a use case model for object oriented software modeling and design. It provides guidance on documenting use cases, including describing use case templates and formats. It also outlines steps for developing an initial use case model, including developing a problem statement, identifying actors and use cases, creating an initial use case diagram, and describing use cases briefly with initial descriptions.
This document discusses interaction diagrams in object-oriented modeling, specifically sequence diagrams and collaboration diagrams. It describes how these diagrams are used to model the interaction and collaboration between objects by showing the messages passed between objects. The document provides examples and notation for constructing sequence diagrams and collaboration diagrams.
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.
This document discusses requirements engineering processes and activities. It describes the key activities in requirements engineering as requirements elicitation, analysis, validation, and management. These activities involve discovering requirements through interviews and scenarios, analyzing requirements from different stakeholder viewpoints, validating requirements, and managing an evolving set of requirements. The document provides examples and details of each activity, such as how to conduct interviews, define viewpoints and scenarios, and iterate on requirements through a spiral process.
This document summarizes key concepts from the first chapter of Ian Sommerville's Software Engineering textbook. It introduces software engineering as an engineering discipline concerned with all aspects of software production. It discusses the objectives of software engineering, topics covered like frequently asked questions and professional responsibility. It also summarizes concepts like the software development process, methods, costs and challenges in the field.
This document summarizes key topics from Chapter 4 of Ian Sommerville's Software Engineering textbook, including software process models, generic process models like waterfall, evolutionary development and component-based development, process activities like requirements engineering, design, implementation, validation and evolution. It also describes the Rational Unified Process model and the role of computer-aided software engineering tools in supporting software processes.
The document discusses software requirements and requirements engineering. It covers topics like functional and non-functional requirements, user requirements, system requirements, and how requirements can be organized in a requirements document. It describes different types of requirements like functional, non-functional, and domain requirements. It also discusses issues with natural language requirements specifications and alternatives like structured natural language, graphical notations, and mathematical specifications.
The COCOMO model is a widely used software cost estimation model developed by Barry Boehm in 1981. It predicts effort, schedule, and staffing needs based on project size and characteristics. The Basic COCOMO model uses three development modes (Organic, Semidetached, Embedded) and a simple formula to estimate effort and schedule based on thousands of delivered source instructions. However, its accuracy is limited as it does not account for various project attributes known to influence costs. Function Point Analysis is an alternative size measurement that counts different types of system functions and complexity factors to estimate effort and cost.
The document provides information about software engineering for the second semester of the second year B.Tech IT course, including the syllabus, textbooks, and an index of process model lecture topics and slides. Process models covered include waterfall, incremental, RAD, evolutionary prototypes, spiral, and unified process. Software requirements topics such as functional and non-functional requirements are also outlined.
The document discusses different types of system models used in requirements engineering, including context models, behavioral models, data models, and object models. It provides examples of each type of model, such as a data flow diagram of an order processing system and a state diagram for a microwave oven. The objectives are to explain why system context should be modeled, describe different modeling notations and perspectives, and discuss how computer-aided software engineering tools can support system modeling.
The importance of software since there is were the motivation for software engineering lies and then and introduction to software engineering mentioning the concept and stages of development and working in teams
The document describes an online railway reservation system project submitted by students. It discusses software engineering principles and methods used to develop the system. It includes UML diagrams like use case, class, sequence, and activity diagrams that were created as part of the analysis and design of the system. It also describes testing done on the project in the form of alpha testing.
1. The document discusses various software engineering process models including waterfall, prototyping, RAD, incremental, and spiral models. It describes the key phases and advantages/disadvantages of each.
2. It also covers system engineering and how software engineering occurs as part of developing larger systems. Business process engineering and product engineering are introduced for developing information systems and products respectively.
3. Key aspects of developing computer-based systems are outlined including the elements of software, hardware, people, databases, documentation and procedures.
The document discusses various software process models including prescriptive models like waterfall model and incremental process model. It also covers evolutionary models like prototyping and spiral process model. Specialized models covered are component based development, formal methods model, aspect oriented development and unified process model. The key highlights are that different models are suited for different situations based on project needs and each model has advantages and disadvantages to consider.
SE_Unit 2.pdf it is a process model of it studentRAVALCHIRAG1
The document discusses various process models for software engineering including waterfall, incremental, RAD, evolutionary (prototyping and spiral), concurrent, component-based, aspect-oriented, and reuse-oriented models. It also covers project metrics, software measurement approaches including size-oriented metrics like lines of code and function-oriented metrics like function points. Key aspects of each model are defined along with their applicability and limitations.
This document discusses various process models for software engineering:
- The waterfall model defines sequential phases of requirements, design, implementation, testing, and maintenance. It is inflexible to change.
- Iterative models allow repetition of phases to incrementally develop software. The incremental model delivers functionality in increments.
- Evolutionary models like prototyping and spiral development use iterative evaluation and refinement of prototypes to evolve requirements and manage risk.
- Other models include component-based development, formal methods, aspect-oriented development, and the Unified Process with iterative development of use cases. Personal and team software processes focus on self-directed teams, planning, metrics, and process improvement.
Lect-4: Software Development Life Cycle Model - SPMMubashir Ali
This document provides an overview of several software development life cycle (SDLC) models, including Waterfall, V-Shaped, Prototyping, Incremental, Spiral, and Agile models. It describes the key phases and characteristics of each model, and provides guidance on when each model is best applied based on factors like requirements stability, technology maturity, and risk level. The document aims to help readers understand the different SDLC options and choose the model that is most suitable for their specific project needs and context.
The document discusses several software process models:
- The Linear Sequential (Waterfall) Model is a simple, systematic approach where each phase must be completed before moving to the next. It is best for small, well-defined projects.
- The Incremental Model applies the Linear Sequential Model iteratively to increments, delivering working software in stages. This allows for early delivery and flexibility.
- The Prototyping Model involves building prototypes to refine requirements through client feedback in iterations. This helps establish clear objectives.
- Rapid Application Development (RAD) is a fast version of the Linear Sequential Model using a component-based approach to accelerate delivery of fully functional projects.
This document provides an overview of various software development life cycle (SDLC) models including Waterfall, V-Shaped, Prototyping, Rapid Application Development (RAD), Incremental, Spiral, and Agile methods. Key aspects of each model are described such as typical phases, when each model is best suited, strengths, and weaknesses. Tailoring SDLC models to best fit individual projects is also discussed. The document concludes with a brief section on quality assurance and elements that should be considered in a quality assurance plan.
This document provides information on various software development life cycle (SDLC) models, including:
- The Capability Maturity Model (CMM) which defines 5 levels of process maturity for software development organizations.
- The Waterfall model which is a linear sequential flow process that is easy to understand but lacks flexibility.
- The V-Shaped model which is a variant of the Waterfall model that emphasizes verification and validation in parallel with development phases.
- Evolutionary Prototyping which builds prototypes to get early user feedback to refine requirements before final development.
- Rapid Application Development (RAD) which uses automated tools to accelerate the development cycle through close user involvement.
- Incremental development which priorit
This document outlines the topics covered in five units of a Software Engineering course. Unit I introduces software engineering paradigms like waterfall and spiral models. Unit II covers software design concepts like abstraction and modularity. Unit III discusses software testing and maintenance. Unit IV covers software metrics and quality assurance. Unit V focuses on software configuration management. Key concepts covered include software development lifecycles, risk analysis, requirements engineering, and project planning techniques.
Software life cycle model: The descriptive and diagrammatic representation of the software life cycle
It represent all the activities performed on software product from the inception to retirement
It also depicts the order in which these activities are to be undertaken
More than one activity can be carried out in a single phase
The primary advantage of adhering to a life cycle model is that it encourages development of software in a systematic and disciplined manner
When a program is developed by a single programmer ,he has the freedom to decide the exact steps through which he will develop the program
Iterative Linear Sequential Model
The document discusses several software development life cycle (SDLC) models including the Capability Maturity Model (CMM), Waterfall model, V-shaped model, Rapid Application Development (RAD) model, Incremental model, and Spiral model. It provides an overview of the key stages and characteristics of each model as well as their strengths and weaknesses to help determine when each model is best applied.
The document discusses various software development life cycle (SDLC) models including waterfall, V-shaped, prototyping, rapid application development (RAD), incremental, spiral, and agile models. For each model, the key steps or phases are described along with strengths and weaknesses. When each model is most applicable is also discussed. The document then covers quality assurance planning and activities that should be included like defect tracking, testing at various levels, and technical reviews.
The document discusses several software development life cycle (SDLC) models including the Capability Maturity Model (CMM), Waterfall model, V-shaped model, Rapid Application Development (RAD) model, Incremental model, and Spiral model. It provides an overview of the key stages and characteristics of each model as well as their strengths and weaknesses to help determine when each model is best applied.
The document discusses several software development life cycle (SDLC) models including the Capability Maturity Model (CMM), Waterfall model, V-shaped model, Rapid Application Development (RAD) model, Incremental model, and Spiral model. It provides an overview of the key stages and characteristics of each model as well as their strengths and weaknesses to help determine when each model is best applied.
The document discusses various software development life cycle (SDLC) models including waterfall, V-shaped, prototyping, rapid application development (RAD), incremental, spiral, and agile models. For each model, the key steps or phases are described along with strengths and weaknesses. When each model is most applicable is also discussed. The document then covers quality assurance planning and activities that should be included like defect tracking, testing at various levels, and technical reviews.
The document discusses various software development life cycle (SDLC) models including waterfall, V-shaped, prototyping, rapid application development (RAD), incremental, spiral, and agile models. For each model, the key steps or phases are described along with strengths and weaknesses. When each model is most applicable is also discussed. The document then covers quality assurance and the importance of having a quality assurance plan that includes elements like defect tracking, testing at various stages of development, and code reviews.
The document discusses several software development life cycle (SDLC) models including the Capability Maturity Model (CMM), Waterfall model, V-shaped model, Rapid Application Development (RAD) model, Incremental model, and Spiral model. It provides details on the key steps and phases in each model as well as their strengths and weaknesses. The models range from traditional plan-driven approaches like Waterfall to more iterative approaches like RAD and Spiral that allow for user feedback and adjustments throughout the process.
The document discusses various software development life cycle (SDLC) models including waterfall, V-shaped, prototyping, rapid application development (RAD), incremental, spiral, and agile models. For each model, the key steps or phases are described along with strengths and weaknesses. When each model is most applicable is also discussed. The document then covers quality assurance planning and activities that should be included like defect tracking, testing at various levels, and technical reviews.
The document discusses various software development life cycle (SDLC) models including waterfall, V-shaped, prototyping, rapid application development (RAD), incremental, spiral, and agile models. For each model, the key steps or phases are described along with strengths and weaknesses. When each model is most applicable is also discussed. The document then covers quality assurance planning and activities that should be included like defect tracking, testing at various levels, and technical reviews.
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Software engineering lecture notes
1. Tnlearners and webexpo
CS51 SOFTWARE ENGINEERING
UNIT I
SOFTWARE PRODUCT AND PROCESS
Software engineering paradigm:
• The framework activities will always be applied on every project ... BUT the tasks (and
degree of rigor) for each activity will vary based on:
– the type of project
– characteristics of the project
– common sense judgment; concurrence of the project team
The software process:
• A structured set of activities required to develop a software system
– Specification;
– Design;
– Validation;
– Evolution.
• A software process model is an abstract representation of a process. It presents a
description of a process from some particular perspective.
Waterfall model/Linear Sequential Model/classic life cycle :
• Systems Engineering
– Software as part of larger system, determine requirements for all system
elements, allocate requirements to software.
• Software Requirements Analysis
– Develop understanding of problem domain, user needs, function, performance,
interfaces, ...
– Software Design
– Multi-step process to determine architecture, interfaces, data structures,
functional detail. Produces (high-level) form that can be checked for quality,
conformance before coding.
• Coding
– Produce machine readable and executable form, match HW, OS and design needs.
• Testing
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– Confirm that components, subsystems and complete products meet requirements,
specifications and quality, find and fix defects.
• Maintenance
– Incrementally, evolve software to fix defects, add features, adapt to new
condition. Often 80% of effort spent here!
Waterfall model phases:
• Requirements analysis and definition
• System and software design
• Implementation and unit testing
• Integration and system testing
• Operation and maintenance
• The main drawback of the waterfall model is the difficulty of accommodating change
after the process is underway. One phase has to be complete before moving onto the next
phase.
• Each phase terminates only when the documents are complete and approved by the SQA
group.
• Maintenance begins when the client reports an error after having accepted the product. It
could also begin due to a change in requirements after the client has accepted the product
Waterfall model: Advantages:
• Disciplined approach
• Careful checking by the Software Quality Assurance Group at the end of each phase.
• Testing in each phase.
• Documentation available at the end of each phase.
Waterfall model problems:
• It is difficult to respond to changing customer requirements.
• Therefore, this model is only appropriate when the requirements are well-understood and
changes will be fairly limited during the design process.
• Few business systems have stable requirements.
• The waterfall model is mostly used for large systems engineering projects where a system
is developed at several sites.
• The customer must have patience. A working version of the program will not be available
until late in the project time-span
• Feedback from one phase to another might be too late and hence expensive.
The Prototyping Models:
• Often, a customer defines a set of general objectives for software but does not identify
detailed input, processing, or output requirements.
• In other cases, the developer may be unsure of the efficiency of an algorithm, the
adaptability of an operating system, or the form that human –machine interaction should
take
• In this case prototyping paradigm may offer the best approach
• Requirements gathering
• Quick design
• Prototype building
• Prototype evaluation by customers
• Prototype may be refined
3. Tnlearners and webexpo
• Prototype thrown away and software developed using formal process{ it is used to define
the requirement} Prototyping
Strengths:
• Requirements can be set earlier and more reliably
• Customer sees results very quickly.
• Customer is educated in what is possible helping to refine requirements.
• Requirements can be communicated more clearly and completely
• Between developers and clients Requirements and design options can be
investigated quickly and Cheaply
Weaknesses:
– Requires a rapid prototyping tool and expertise in using it–a cost for the
development organisation
– Smoke and mirrors - looks like a working version, but it is not.
The RAD Model:
• Rapid Application Development is a linear sequential software development process
model that emphasizes an extremely short development cycle
• Rapid application achieved by using a component based construction approach
• If requirements are well understood and project scope is constrained the RAD process
enables a development team to create a ―fully functional system‖
Team # n
M o d e lin g
business m odeling
data m odeling
process m odeling
Communicat ion
Planning
Team # 2
Modeling
business m odeling
dat a m odeling
process m odeling
Co n st ru ct io n
com ponent reuse
autom atic code
generation
testing
Team # 1
Modeling
business modeling
dat a modeling
process modeling
Const ruct ion
com ponent reuse
aut om at ic code
generat ion
t est ing
Deployment
int egrat ion
delivery
feedback
Const ruct ion
component reuse
aut omat ic code
generat ion
t est ing
60 - 90 days
RAD phases :
• Business modeling
• Data modeling
• Process modeling
4. Tnlearners and webexpo
• Application generation
• Testing and turnover
Business modeling:
• What information drives the business process?
• What information is generated?
• Who generates it?
Data Modeling:
• The information flow defined as part of the business modeling phase is refined into a set
of data objects that are needed to support the business.
• The characteristics ( called attributes) of each object are identified and the relationships
between these objects are defined
Process modeling:
• The data modeling phase are transformed to achieve the information flow necessary to
implement a business function.
• Processing descriptions are created for adding , modifying, deleting, or retrieving a data
object
Application generation:
• RAD assumes the use of 4 generation techniques.
• Rather than creating software using conventional 3 generation programming languages,
the RAD process works to reuse existing program components (when possible) or created
reusable components (when necessary)
Testing and Turnover:
• Since the RAD process emphasizes reuse, many of the program components have already
been testing.
• This reduces over all testing time.
• However, new components must be tested and all interfaces must be fully exercised
Advantages &Disadvantages of RAD:
Advantages
• Extremely short development time.
• Uses component-based construction and emphasises reuse and code generation
Disadvantages
• Large human resource requirements (to create all of the teams).
• Requires strong commitment between developers and customers for “rapid-fire”
activities.
• High performance requirements maybe can’t be met (requires tuning the components).
The Incremental Model
increment # n
C o m m u n i c a t i o n
P l a n n i n g
M o d e l i n g
a n a l y s i s
d e s i g n
C o n s t r u c t i o n
c o d e t
e s t
D e p l o y m e n t
d e l i v e r y
f e e d b a c k
increment # 2
deliv ery of
nt h increment
C o m m u n i c a t i o n
P l a n n i n g
M o d e l i n g
a n a l y s i s C o n s t r u c t i o n
increment # 1
d e s i g n c o d e t
e s t
D e p l o y m e n t
d e l i v e r y
f e e d b a c k
deliv ery of
2nd increment
C o m m u n i c a t i o n
P l a n n i n g
M o d e l i n g
a n a l y s i s C o n s t r u c t i o n
d e s i g n c o d e t
e s t
D e p l o y m e n t
d e l i v e r y
f e e d b a c k
deliv ery of
1st increment
project calendar t ime :
5. Tnlearners and webexpo
The Incremental development
• Combination of linear + prototype
• Rather than deliver the system as a single delivery, the development and delivery is
broken down into increments with each increment delivering part of the required
functionality
• User requirements are prioritised and the highest priority requirements are included in
early increments
• Once the development of an increment is started, the requirements are frozen though
requirements for later increments can continue to evolve
Incremental development advantages:
• The customer is able to do some useful work after release
• Lower risk of overall project failure
• The highest priority system services tend to receive the most testing
Spiral Model:
Spiral model sectors:
• Customer communication
Tasks required to establish effective communication between developer and
customer
• Planning
The tasks required to define recourses, timelines, and project is reviewed and the
next phase of the spiral is planned
• Risk analysis
– Risks are assessed and activities put in place to reduce the key
• Risks engineering
– Tasks required to build one or more representations of the application
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• Construction & release
– Tasks required to construct, test, install and provide user support (e.g
documentation and training)
• Customer evaluation
– Customer feedback collected every stage
Spiral Model Advantages:
• Focuses attention on reuse options.
• Focuses attention on early error elimination.
• Puts quality objectives up front.
• Integrates development and maintenance.
• Provides a framework for hardware/software Development.
System Engineering
• Software engineering occurs as a consequence of a process called system engineering.
• Instead of concentrating solely on software, system engineering focuses on a variety of
elements, analyzing, designing, and organizing those elements into a system that can be a
product, a service, or a technology for the transformation of information or control.
7. Tnlearners and webexpo
• The system engineering process usually begins with a ―world view.‖ That is, the entire
business or product domain is examined to ensure that the proper business or technology
context can be established.
• The world view is refined to focus more fully on specific domain of interest. Within a
specific domain, the need for targeted system elements (e.g., data, software, hardware,
people) is analyzed. Finally, the analysis, design, and construction of a targeted system
element is initiated.
• At the top of the hierarchy, a very broad context is established and, at the bottom, detailed
technical activities, performed by the relevant engineering discipline (e.g., hardware or
software engineering), are conducted.
• Stated in a slightly more formal manner, the world view (WV) is composed of a set of
domains (Di), which can each be a system or system of systems in its own right.
WV = {D1, D2, D3, . . . , Dn}
• Each domain is composed of specific elements (Ej) each of which serves some role in
accomplishing the objective and goals of the domain or component:
Di = {E1, E2, E3, . . . , Em}
• Finally, each element is implemented by specifying the technical components (Ck) that
achieve the necessary function for an element:
Ej = {C1, C2, C3, . . . , Ck}
Computer Based System
• computer-based system as A set or arrangement of elements that are organized to accomplish
some predefined goal by processing information.
• The goal may be to support some business function or to develop a product that can be sold
to generate business revenue.
• To accomplish the goal, a computer-based system makes use of a variety of system elements:
1. Software. Computer programs, data structures, and related documentation that serve to
effect the logical method, procedure, or control that is required.
2. Hardware. Electronic devices that provide computing capability, the interconnectivity
devices (e.g., network switches, telecommunications devices) that enable the flow of
data, and electromechanical devices (e.g., sensors, motors, pumps) that provide external
world function.
3. People. Users and operators of hardware and software.
4. Database. A large, organized collection of information that is accessed via software.
5. Documentation. Descriptive information (e.g., hardcopy manuals, on-line help files,
Web sites) that portrays the use and/or operation of the system.
6. Procedures. The steps that define the specific use of each system element or the
procedural context in which the system resides.
• The elements combine in a variety of ways to transform information. For example, a
marketing department transforms raw sales data into a profile of the typical purchaser of a
product; a robot transforms a command file containing specific instructions into a set of
control signals that cause some specific physical action.
• Creating an information system to assist the marketing department and control software to
support the robot both require system engineering.
8. Tnlearners and webexpo
• One complicating characteristic of computer-based systems is that the elements constituting
one system may also represent one macro element of a still larger system. The macro element
is a computer-based system that is one part of a larger computer-based system.
• As an example, we consider a "factory automation system" that is essentially a hierarchy of
systems. At the lowest level of the hierarchy we have a numerical control machine, robots,
and data entry devices.
• Each is a computerbased system in its own right. The elements of the numerical control
machine include electronic and electromechanical hardware (e.g., processor and memory,
motors, sensors), software (for communications, machine control, interpolation), people (the
machine operator), a database (the stored NC program), documentation, and procedures.
• A similar decomposition could be applied to the robot and data entry device. Each is a
computer-based system.
• At the next level in the hierarchy, a manufacturing cell is defined. The manufacturing cell is a
computer-based system that may have elements of its own (e.g., computers, mechanical
fixtures) and also integrates the macro elements that we have called numerical control
machine, robot, and data entry device.
Business Process Engineering Overview
• The goal of business process engineering (BPE) is to define architectures that will enable a
business to use information effectively.
• When taking a world view of a company‘s information technology needs, there is little doubt
that system engineering is required. Not only is the specification of the appropriate
computing architecture required, but the software architecture that populates the ―unique
configuration of heterogeneous computing resources‖ must be developed.
• Business process engineering is one approach for creating an overall plan for implementing
the computing architecture .
• Three different architectures must be analyzed and designed within the context of business
objectives and goals:
• data architecture
• applications architecture
• technology infrastructure
• The data architecture provides a framework for the information needs of a business or
business function. The individual building blocks of the architecture are the data objects that
are used by the business. A data object contains a set of attributes that define some aspect,
quality, characteristic, or descriptor of the data that are being described.
• The application architecture encompasses those elements of a system that transform objects
within the data architecture for some business purpose. In the context of this book, we
consider the application architecture to be the system of programs (software) that performs
this transformation. However, in a broader context, the application architecture might
incorporate the role of people (who are information transformers and users) and business
procedures that have not been automated.
• The technology infrastructure provides the foundation for the data and application
architectures. The infrastructure encompasses the hardware and software that are used to
support the application and data. This includes computers, operating systems, networks,
telecommunication links, storage technologies, and the architecture (e.g., client/server) that
has been designed to implement these technologies.
9. Tnlearners and webexpo
• The final BPE step—construction and integration focuses on implementation detail. The
architecture and infrastructure are implemented by constructing an appropriate database and
internal data structures, by building applications using software components, and by selecting
appropriate elements of a technology infrastructure to support the design created during
BSD. Each of these system components must then be integrated to form a complete
information system or application.
• The integration activity also places the new information system into the business area
context, performing all user training and logistics support to achieve a smooth transition.
Product Engineering Overview
• The goal of product engineering is to translate the customer‘s desire for a set of defined
capabilities into a working product. To achieve this goal, product engineering—like business
process engineering—must derive architecture and infrastructure.
• The architecture encompasses four distinct system components: software, hardware, data
(and databases), and people. A support infrastructure is established and includes the
technology required to tie the components together and the information (e.g., documents,CD-
ROM, video) that is used to support the components.
• The world view is achieved through requirements engineering. The overall requirements of
the product are elicited from the customer. These requirements encompass information and
control needs, product function and behavior, overall product performance, design and
interfacing constraints, and other special needs.
• Once these requirements are known, the job of requirements engineering is to allocate
function and behavior to each of the four components noted earlier. Once allocation has
occurred, system component engineering commences.
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• System component engineering is actually a set of concurrent activities that address each of
the system components separately: software engineering, hardware engineering, human
engineering, and database engineering.
• Each of these engineering disciplines takes a domain-specific view, but it is important to note
that the engineering disciplines must establish and maintain active communication with one
another. Part of the role of requirements engineering is to establish the interfacing
mechanisms that will enable this to happen.
• The element view for product engineering is the engineering discipline itself applied to the
allocated component. For software engineering, this means analysis and design modeling
activities (covered in detail in later chapters) and construction and integration activities that
encompass code generation, testing, and support steps.
• The analysis step models allocated requirements into representations of data, function, and
behavior. Design maps the analysis model into data, architectural, interface, and software
component-level designs.
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UNIT II SOFTWARE
REQUIREMENTS
• The process of establishing the services that the customer requires from a system and the
constraints under which it operates and is developed
• Requirements may be functional or non-functional
• Functional requirements describe system services or functions
• Non-functional requirements is a constraint on the system or on the development
process
Types of requirements
• User requirements
• Statements in natural language (NL) plus diagrams of the services the system
provides and its operational constraints. Written for customers
• System requirements
• A structured document setting out detailed descriptions of the system services.
Written as a contract between client and contractor
• Software specification
• A detailed software description which can serve as a basis for a design or
implementation. Written for developers
Functional and Non-Functional
Functional requirements
• Functionality or services that the system is expected to provide.
• Functional requirements may also explicitly state what the system shouldn‘t do.
• Functional requirements specification should be:
• Complete: All services required by the user should be defined
• Consistent: should not have contradictory definition (also avoid ambiguity
don‘t leave room for different interpretations)
Examples of functional requirements
• The LIBSYS system
• A library system that provides a single interface to a number of databases of articles in
different libraries.
• Users can search for, download and print these articles for personal study.
• The user shall be able to search either all of the initial set of databases or select a subset from
it.
• The system shall provide appropriate viewers for the user to read documents in the document
store.
• Every order shall be allocated a unique identifier (ORDER_ID) which the user shall be able
to copy to the account‘s permanent storage area.
Non-Functional requirements
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• Requirements that are not directly concerned with the specific functions delivered by the
system
• Typically relate to the system as a whole rather than the individual system features
• Often could be deciding factor on the survival of the system (e.g. reliability, cost, response
time)
Non-Functional requirements classifications:
Non-functional
requir ements
Product
requir ements
Organisational
requir ements
External
requir ements
Efficiency
requir ements
Reliability
requir ements
Portability
requir ements
Inter oper ability
requir ements
Ethical
requir ements
Usability
requir ements
Deli very
requir ements
Implementa tion
requir ements
Standar ds
requir ements
Leg islative
requir ements
Performance
requir ements
Space
requir ements
Pri vacy
requir ements
Safety
requir ements
Domain requirements
• Domain requirements are derived from the application domain of the system rather than from
the specific needs of the system users.
• May be new functional requirements, constrain existing requirements or set out how
particular computation must take place.
• Example: tolerance level of landing gear on an aircraft (different on dirt, asphalt, water), or
what happens to fiber optics line in case of sever weather during winter Olympics (Only
domain-area experts know)
Product requirements
• Specify the desired characteristics that a system or subsystem must possess.
• Most NFRs are concerned with specifying constraints on the behaviour of the executing
system.
Specifying product requirements
• Some product requirements can be formulated precisely, and thus easily quantified
• Performance
• Capacity
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• Others are more difficult to quantify and, consequently, are often stated informally
• Usability
Process requirements
• Process requirements are constraints placed upon the development process of the system
• Process requirements include:
• Requirements on development standards and methods which must be followed
• CASE tools which should be used
• The management reports which must be provided
Examples of process requirements
• The development process to be used must be explicitly defined and must be conformant with
ISO 9000 standards
• The system must be developed using the XYZ suite of CASE tools
• Management reports setting out the effort expended on each identified system component
must be produced every two weeks
• A disaster recovery plan for the system development must be specified
External requirements
• May be placed on both the product and the process
• Derived from the environment in which the system is developed
• External requirements are based on:
• application domain information
• organisational considerations
• the need for the system to work with other systems
• health and safety or data protection regulations
• or even basic natural laws such as the laws of physics
Examples of external requirements
• Medical data system The organisation‘s data protection officer must certify that all data is
maintained according to data protection legislation before the system is put into operation.
• Train protection system The time required to bring the train to a complete halt is computed
using the following function:
• The deceleration of the train shall be taken as:
gtrain = gcontrol + ggradient
where:
ggradient = 9.81 ms-2
* compensated gradient / alpha and where the values of 9.81 ms-2/
alpha are known for the different types of train.
gcontrol is initialised at 0.8 ms-2
- this value being parameterised in order to remain
adjustable. The illustrates an example of the train‘s deceleration by using the parabolas derived
from the above formula where there is a change in gradient before the (predicted) stopping point
of the train.
Software Document
• Should provide for communication among team members
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• Should act as an information repository to be used by maintenance engineers
• Should provide enough information to management to allow them to perform all program
management related activities
• Should describe to users how to operate and administer the system
• Specify external system behaviour
• Specify implementation constraints
• Easy to change
• Serve as reference tool for maintenance
• Record forethought about the life cycle of the system i.e. predict changes
• Characterise responses to unexpected events
Users of a requirements document
System customers
Specify the requirements and
read them to check that they
meet their needs. They
specify changes to the
requirements
Managers
Use the requirements
document to plan a bid for
the system and to plan the
system development process
System engineers
Use the requirements to
understand what system is to
be developed
System test
engineers
Use the requirements to
develop validation tests for
the system
System
maintenance
engineers
Use the requirements to help
understand the system and
the relationships between its
parts
Process Documentation
• Used to record and track the development process
• Planning documentation
• Cost, Schedule, Funding tracking
• Schedules
• Standards
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• This documentation is created to allow for successful management of a software product
• Has a relatively short lifespan
• Only important to internal development process
• Except in cases where the customer requires a view into this data
• Some items, such as papers that describe design decisions should be extracted and moved
into the product documentation category when they become implemented
• Product Documentation
• Describes the delivered product
• Must evolve with the development of the software product
• Two main categories:
• System Documentation
• User Documentation
Product Documentation
• System Documentation
• Describes how the system works, but not how to operate it
• Examples:
• Requirements Spec
• Architectural Design
• Detailed Design
• Commented Source Code
Including output such as JavaDoc
• Test Plans
Including test cases
• V&V plan and results
• List of Known Bugs
• User Documentation has two main types
• End User
• System Administrator
In some cases these are the same people
• The target audience must be well understood!
• There are five important areas that should be documented for a formal release of a software
application
• These do not necessarily each have to have their own document, but the topics should
be covered thoroughly
• Functional Description of the Software
• Installation Instructions
• Introductory Manual
• Reference Manual
• System Administrator‘s Guide
Document Quality
• Providing thorough and professional documentation is important for any size product
development team
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• The problem is that many software professionals lack the writing skills to create
professional level documents
Document Structure
• All documents for a given product should have a similar structure
• A good reason for product standards
• The IEEE Standard for User Documentation lists such a structure
• It is a superset of what most documents need
• The authors ―best practices‖ are:
• Put a cover page on all documents
• Divide documents into chapters with sections and subsections
• Add an index if there is lots of reference information
• Add a glossary to define ambiguous terms
Standards
• Standards play an important role in the development, maintenance and usefulness of
documentation
• Standards can act as a basis for quality documentation
• But are not good enough on their own
Usually define high level content and organization
• There are three types of documentation standards
1.Process Standards
• Define the approach that is to be used when creating the documentation
• Don‘t actually define any of the content of the documents
2. Product Standards
• Goal is to have all documents created for a specific product attain a consistent structure and
appearance
• Can be based on organizational or contractually required standards
• Four main types:
• Documentation Identification Standards
• Document Structure Standards
• Document Presentation Standards
• Document Update Standards
• One caveat:
• Documentation that will be viewed by end users should be created in a way that is
best consumed and is most attractive to them
• Internal development documentation generally does not meet this need
3. Interchange Standards
• Deals with the creation of documents in a format that allows others to effectively use
• PDF may be good for end users who don‘t need to edit
• Word may be good for text editing
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• Specialized CASE tools need to be considered
• This is usually not a problem within a single organization, but when sharing data between
organizations it can occur
• This same problem is faced all the time during software integration
Other Standards
• IEEE
• Has a published standard for user documentation
• Provides a structure and superset of content areas
• Many organizations probably won‘t create documents that completely match the
standard
• Writing Style
• Ten ―best practices‖ when writing are provided
• Author proposes that group edits of important documents should occur in a similar
fashion to software walkthroughs
Requirement Engineering Process
• The requirements engineering process includes a feasibility study, requirements elicitation
and analysis, requirements specification and requirements management
Feasibility
study
Feasibility
report
Requirements
elicitation and
analysis
System
models
Requir ements
specification
User and system
requirements
Requirements
validation
Requirements
document
Feasibility Studies
• A feasibility study decides whether or not the proposed system is worthwhile
• A short focused study that checks
• If the system contributes to organisational objectives
• If the system can be engineered using current technology and within budget
• If the system can be integrated with other systems that are used
• Based on information assessment (what is required), information collection and report
writing
• Questions for people in the organisation
• What if the system wasn‘t implemented?
• What are current process problems?
• How will the proposed system help?
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• What will be the integration problems?
• Is new technology needed? What skills?
• What facilities must be supported by the proposed system?
Elicitation and analysis
• Sometimes called requirements elicitation or requirements discovery
• Involves technical staff working with customers to find out about
• the application domain
• the services that the system should provide
• the system‘s operational constraints
• May involve end-users, managers, engineers involved in maintenance, domain experts, trade
unions, etc.
• These are called stakeholders
Problems of requirements analysis
• Stakeholders don‘t know what they really want
• Stakeholders express requirements in their own terms
• Different stakeholders may have conflicting requirements
• Organisational and political factors may influence the system requirements
• The requirements change during the analysis process
• New stakeholders may emerge and the business environment change
System models
• Different models may be produced during the requirements analysis activity
• Requirements analysis may involve three structuring activities which result in these different
models
• Partitioning – Identifies the structural (part-of) relationships between entities
• Abstraction – Identifies generalities among entities
• Projection – Identifies different ways of looking at a problem
• System models will be covered on January 30
Scenarios
• Scenarios are descriptions of how a system is used in practice
• They are helpful in requirements elicitation as people can relate to these more readily than
abstract statement of what they require from a system
• Scenarios are particularly useful for adding detail to an outline requirements description
Ethnography
• A social scientists spends a considerable time observing and analysing how people actually
work
• People do not have to explain or articulate their work
• Social and organisational factors of importance may be observed
• Ethnographic studies have shown that work is usually richer and more complex than
suggested by simple system models
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Requirements validation
• Concerned with demonstrating that the requirements define the system that the customer
really wants
• Requirements error costs are high so validation is very important
• Fixing a requirements error after delivery may cost up to 100 times the cost of fixing
an implementation error
• Requirements checking
• Validity
• Consistency
• Completeness
• Realism
• Verifiability
Requirements validation techniques
• Reviews
• Systematic manual analysis of the requirements
• Prototyping
• Using an executable model of the system to check requirements.
• Test-case generation
• Developing tests for requirements to check testability
• Automated consistency analysis
• Checking the consistency of a structured requirements description
Requirements management
• Requirements management is the process of managing changing requirements during the
requirements engineering process and system development
• Requirements are inevitably incomplete and inconsistent
• New requirements emerge during the process as business needs change and a better
understanding of the system is developed
• Different viewpoints have different requirements and these are often contradictory
Software prototyping
Incomplete versions of the software program being developed. Prototyping can also be
used by end users to describe and prove requirements that developers have not considered
Benefits:
The software designer and implementer can obtain feedback from the users early in the
project. The client and the contractor can compare if the software made matches the software
specification, according to which the software program is built.
It also allows the software engineer some insight into the accuracy of initial project
estimates and whether the deadlines and milestones proposed can be successfully met.
Process of prototyping
1. Identify basic requirements
Determine basic requirements including the input and output information desired. Details,
such as security, can typically be ignored.
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2. Develop Initial Prototype
The initial prototype is developed that includes only user interfaces. (See Horizontal
Prototype, below)
3. Review
The customers, including end-users, examine the prototype and provide feedback on
additions or changes.
4. Revise and Enhance the Prototype
Using the feedback both the specifications and the prototype can be improved. Negotiation
about what is within the scope of the contract/product may be necessary. If changes are
introduced then a repeat of steps #3 and #4 may be needed.
Dimensions of prototypes
1. Horizontal Prototype
It provides a broad view of an entire system or subsystem, focusing on user interaction more
than low-level system functionality, such as database access. Horizontal prototypes are useful
for:
• Confirmation of user interface requirements and system scope
• Develop preliminary estimates of development time, cost and effort.
2 Vertical Prototypes
A vertical prototype is a more complete elaboration of a single subsystem or function. It is
useful for obtaining detailed requirements for a given function, with the following benefits:
• Refinement database design
• Obtain information on data volumes and system interface needs, for network sizing and
performance engineering
Types of prototyping
Software prototyping has many variants. However, all the methods are in some way
based on two major types of prototyping: Throwaway Prototyping and Evolutionary Prototyping.
1. Throwaway prototyping
Also called close ended prototyping. Throwaway refers to the creation of a model that
will eventually be discarded rather than becoming part of the final delivered software. After
preliminary requirements gathering is accomplished, a simple working model of the system is
constructed to visually show the users what their requirements may look like when they are
implemented into a finished system.
The most obvious reason for using Throwaway Prototyping is that it can be done quickly.
If the users can get quick feedback on their requirements, they may be able to refine them early
in the development of the software. Making changes early in the development lifecycle is
extremely cost effective since there is nothing at that point to redo. If a project is changed after a
considerable work has been done then small changes could require large efforts to implement
since software systems have many dependencies. Speed is crucial in implementing a throwaway
prototype, since with a limited budget of time and money little can be expended on a prototype
that will be discarded.
Strength of Throwaway Prototyping is its ability to construct interfaces that the users can
test. The user interface is what the user sees as the system, and by seeing it in front of them, it is
much easier to grasp how the system will work.
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2. Evolutionary prototyping
Evolutionary Prototyping (also known as breadboard prototyping) is quite different from
Throwaway Prototyping. The main goal when using Evolutionary Prototyping is to build a very
robust prototype in a structured manner and constantly refine it. "The reason for this is that the
Evolutionary prototype, when built, forms the heart of the new system, and the improvements
and further requirements will be built.
Evolutionary Prototypes have an advantage over Throwaway Prototypes in that they are
functional systems. Although they may not have all the features the users have planned, they
may be used on a temporary basis until the final system is delivered.
In Evolutionary Prototyping, developers can focus themselves to develop parts of the
system that they understand instead of working on developing a whole system. To minimize risk,
the developer does not implement poorly understood features. The partial system is sent to
customer sites. As users work with the system, they detect opportunities for new features and
give requests for these features to developers. Developers then take these enhancement requests
along with their own and use sound configuration-management practices to change the software-
requirements specification, update the design, recode and retest.
3. Incremental prototyping
The final product is built as separate prototypes. At the end the separate prototypes are
merged in an overall design.
4. Extreme prototyping
Extreme Prototyping as a development process is used especially for developing web
applications. Basically, it breaks down web development into three phases, each one based on
the preceding one. The first phase is a static prototype that consists mainly of HTML pages. In
the second phase, the screens are programmed and fully functional using a simulated services
layer. In the third phase the services are implemented. The process is called Extreme Prototyping
to draw attention to the second phase of the process, where a fully-functional UI is developed
with very little regard to the services other than their contract.
Advantages of prototyping
1. Reduced time and costs: Prototyping can improve the quality of requirements and
specifications provided to developers. Because changes cost exponentially more to implement as
they are detected later in development, the early determination of what the user really wants can
result in faster and less expensive software.
2. Improved and increased user involvement: Prototyping requires user involvement and
allows them to see and interact with a prototype allowing them to provide better and more
complete feedback and specifications. The presence of the prototype being examined by the user
prevents many misunderstandings and miscommunications that occur when each side believe the
other understands what they said. Since users know the problem domain better than anyone on
the development team does, increased interaction can result in final product that has greater
tangible and intangible quality. The final product is more likely to satisfy the users‘ desire for
look, feel and performance.
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Disadvantages of prototyping
1. Insufficient analysis: The focus on a limited prototype can distract developers from properly
analyzing the complete project. This can lead to overlooking better solutions, preparation of
incomplete specifications or the conversion of limited prototypes into poorly engineered final
projects that are hard to maintain. Further, since a prototype is limited in functionality it may not
scale well if the prototype is used as the basis of a final deliverable, which may not be noticed if
developers are too focused on building a prototype as a model.
2. User confusion of prototype and finished system: Users can begin to think that a prototype,
intended to be thrown away, is actually a final system that merely needs to be finished or
polished. (They are, for example, often unaware of the effort needed to add error-checking and
security features which a prototype may not have.) This can lead them to expect the prototype to
accurately model the performance of the final system when this is not the intent of the
developers. Users can also become attached to features that were included in a prototype for
consideration and then removed from the specification for a final system. If users are able to
require all proposed features be included in the final system this can lead to conflict.
3. Developer misunderstanding of user objectives: Developers may assume that users share
their objectives (e.g. to deliver core functionality on time and within budget), without
understanding wider commercial issues. For example, user representatives attending Enterprise
software (e.g. PeopleSoft) events may have seen demonstrations of "transaction auditing" (where
changes are logged and displayed in a difference grid view) without being told that this feature
demands additional coding and often requires more hardware to handle extra database accesses.
Users might believe they can demand auditing on every field, whereas developers might think
this is feature creep because they have made assumptions about the extent of user requirements.
If the developer has committed delivery before the user requirements were reviewed, developers
are between a rock and a hard place, particularly if user management derives some advantage
from their failure to implement requirements.
4. Developer attachment to prototype: Developers can also become attached to prototypes they
have spent a great deal of effort producing; this can lead to problems like attempting to convert a
limited prototype into a final system when it does not have an appropriate underlying
architecture. (This may suggest that throwaway prototyping, rather than evolutionary
prototyping, should be used.)
5. Excessive development time of the prototype: A key property to prototyping is the fact that
it is supposed to be done quickly. If the developers lose sight of this fact, they very well may try
to develop a prototype that is too complex. When the prototype is thrown away the precisely
developed requirements that it provides may not yield a sufficient increase in productivity to
make up for the time spent developing the prototype. Users can become stuck in debates over
details of the prototype, holding up the development team and delaying the final product.
6. Expense of implementing prototyping: the start up costs for building a development team
focused on prototyping may be high. Many companies have development methodologies in
place, and changing them can mean retraining, retooling, or both. Many companies tend to just
jump into the prototyping without bothering to retrain their workers as much as they should.
A common problem with adopting prototyping technology is high expectations for productivity
with insufficient effort behind the learning curve. In addition to training for the use of a
prototyping technique, there is an often overlooked need for developing corporate and project
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specific underlying structure to support the technology. When this underlying structure is
omitted, lower productivity can often result.
Best projects to use prototyping
It has been found that prototyping is very effective in the analysis and design of on-line
systems, especially for transaction processing, where the use of screen dialogs is much more in
evidence. The greater the interaction between the computer and the user, the greater the benefit is
that can be obtained from building a quick system and letting the user play with it.
Systems with little user interaction, such as batch processing or systems that mostly do
calculations, benefit little from prototyping. Sometimes, the coding needed to perform the system
functions may be too intensive and the potential gains that prototyping could provide are too
small.
Prototyping is especially good for designing good human-computer interfaces. "One of
the most productive uses of rapid prototyping to date has been as a tool for iterative user
requirements engineering and human-computer interface design.
Methods
There are few formal prototyping methodologies even though most Agile Methods rely
heavily upon prototyping techniques.
1. Dynamic systems development method
Dynamic Systems Development Method (DSDM) is a framework for delivering business
solutions that relies heavily upon prototyping as a core technique, and is itself ISO 9001
approved. It expands upon most understood definitions of a prototype. According to DSDM the
prototype may be a diagram, a business process, or even a system placed into production. DSDM
prototypes are intended to be incremental, evolving from simple forms into more comprehensive
ones.
DSDM prototypes may be throwaway or evolutionary. Evolutionary prototypes may be evolved
horizontally (breadth then depth) or vertically (each section is built in detail with additional
iterations detailing subsequent sections). Evolutionary prototypes can eventually evolve into
final systems.
The four categories of prototypes as recommended by DSDM are:
• Business prototypes – used to design and demonstrate the business processes being
automated.
• Usability prototypes – used to define, refine, and demonstrate user interface design
usability, accessibility, look and feel.
• Performance and capacity prototypes - used to define, demonstrate, and predict how
systems will perform under peak loads as well as to demonstrate and evaluate other non-
functional aspects of the system (transaction rates, data storage volume, response time)
• Capability/technique prototypes – used to develop, demonstrate, and evaluate a design
approach or concept.
The DSDM lifecycle of a prototype is to:
1. Identify prototype
2. Agree to a plan
3. Create the prototype
4. Review the prototype
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2. Operational prototyping
Operational Prototyping was proposed by Alan Davis as a way to integrate throwaway and
evolutionary prototyping with conventional system development. "[It] offers the best of both the
quick-and-dirty and conventional-development worlds in a sensible manner. Designers develop
only well-understood features in building the evolutionary baseline, while using throwaway
prototyping to experiment with the poorly understood features."
Davis' belief is that to try to "retrofit quality onto a rapid prototype" is not the correct approach
when trying to combine the two approaches. His idea is to engage in an evolutionary prototyping
methodology and rapidly prototype the features of the system after each evolution.
The specific methodology follows these steps:
• An evolutionary prototype is constructed and made into a baseline using conventional
development strategies, specifying and implementing only the requirements that are well
understood.
• Copies of the baseline are sent to multiple customer sites along with a trained prototyper.
• At each site, the prototyper watches the user at the system.
• Whenever the user encounters a problem or thinks of a new feature or requirement, the
prototyper logs it. This frees the user from having to record the problem, and allows them
to continue working.
• After the user session is over, the prototyper constructs a throwaway prototype on top of
the baseline system.
• The user now uses the new system and evaluates. If the new changes aren't effective, the
prototyper removes them.
• If the user likes the changes, the prototyper writes feature-enhancement requests and
forwards them to the development team.
• The development team, with the change requests in hand from all the sites, then produce
a new evolutionary prototype using conventional methods.
Obviously, a key to this method is to have well trained prototypers available to go to the user
sites. The Operational Prototyping methodology has many benefits in systems that are complex
and have few known requirements in advance.
3. Evolutionary systems development
Evolutionary Systems Development is a class of methodologies that attempt to formally
implement Evolutionary Prototyping. One particular type, called Systems craft is described by
John Crinnion in his book: Evolutionary Systems Development.
Systemscraft was designed as a 'prototype' methodology that should be modified and
adapted to fit the specific environment in which it was implemented.
Systemscraft was not designed as a rigid 'cookbook' approach to the development
process. It is now generally recognised[sic] that a good methodology should be flexible enough
to be adjustable to suit all kinds of environment and situation…
The basis of Systemscraft, not unlike Evolutionary Prototyping, is to create a working system
from the initial requirements and build upon it in a series of revisions. Systemscraft places heavy
emphasis on traditional analysis being used throughout the development of the system.
4. Evolutionary rapid development
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Evolutionary Rapid Development (ERD) was developed by the Software Productivity
Consortium, a technology development and integration agent for the Information Technology
Office of the Defense Advanced Research Projects Agency (DARPA).
Fundamental to ERD is the concept of composing software systems based on the reuse of
components, the use of software templates and on an architectural template. Continuous
evolution of system capabilities in rapid response to changing user needs and technology is
highlighted by the evolvable architecture, representing a class of solutions. The process focuses
on the use of small artisan-based teams integrating software and systems engineering disciplines
working multiple, often parallel short-duration timeboxes with frequent customer interaction.
Key to the success of the ERD-based projects is parallel exploratory analysis and development of
features, infrastructures, and components with and adoption of leading edge technologies
enabling the quick reaction to changes in technologies, the marketplace, or customer
requirements.
To elicit customer/user input, frequent scheduled and ad hoc/impromptu meetings with the
stakeholders are held. Demonstrations of system capabilities are held to solicit feedback before
design/implementation decisions are solidified. Frequent releases (e.g., betas) are made available
for use to provide insight into how the system could better support user and customer needs. This
assures that the system evolves to satisfy existing user needs.
The design framework for the system is based on using existing published or de facto
standards. The system is organized to allow for evolving a set of capabilities that includes
considerations for performance, capacities, and functionality. The architecture is defined in terms
of abstract interfaces that encapsulate the services and their implementation (e.g., COTS
applications). The architecture serves as a template to be used for guiding development of more
than a single instance of the system. It allows for multiple application components to be used to
implement the services. A core set of functionality not likely to change is also identified and
established.
The ERD process is structured to use demonstrated functionality rather than paper
products as a way for stakeholders to communicate their needs and expectations. Central to this
goal of rapid delivery is the use of the "time box" method. Timeboxes are fixed periods of time
in which specific tasks (e.g., developing a set of functionality) must be performed. Rather than
allowing time to expand to satisfy some vague set of goals, the time is fixed (both in terms of
calendar weeks and person-hours) and a set of goals is defined that realistically can be achieved
within these constraints. To keep development from degenerating into a "random walk," long-
range plans are defined to guide the iterations. These plans provide a vision for the overall
system and set boundaries (e.g., constraints) for the project. Each iteration within the process is
conducted in the context of these long-range plans.
Once architecture is established, software is integrated and tested on a daily basis. This
allows the team to assess progress objectively and identify potential problems quickly. Since
small amounts of the system are integrated at one time, diagnosing and removing the defect is
rapid. User demonstrations can be held at short notice since the system is generally ready to
exercise at all times.
5. Scrum
Scrum is an agile method for project management. The approach was first described by
Takeuchi and Nonaka in "The New New Product Development Game" (Harvard Business
Review, Jan-Feb 1986).
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Tools
Efficiently using prototyping requires that an organization have proper tools and a staff
trained to use those tools. Tools used in prototyping can vary from individual tools like 4th
generation programming languages used for rapid prototyping to complex integrated CASE
tools. 4th generation programming languages like Visual Basic and ColdFusion are frequently
used since they are cheap, well known and relatively easy and fast to use. CASE tools are often
developed or selected by the military or large organizations. Users may prototype elements of an
application themselves in a spreadsheet.
1. Screen generators, design tools & Software Factories
Commonly used screen generating programs that enable prototypers to show users
systems that don't function, but show what the screens may look like. Developing Human
Computer Interfaces can sometimes be the critical part of the development effort, since to the
users the interface essentially is the system.
Software Factories are Code Generators that allow you to model the domain model and
then drag and drop the UI. Also they enable you to run the prototype and use basic database
functionality. This approach allows you to explore the domain model and make sure it is in sync
with the GUI prototype.
2. Application definition or simulation software
It enables users to rapidly build lightweight, animated simulations of another computer
program, without writing code. Application simulation software allows both technical and non-
technical users to experience, test, collaborate and validate the simulated program, and provides
reports such as annotations, screenshot and schematics. To simulate applications one can also use
software which simulate real-world software programs for computer based training,
demonstration, and customer support, such as screen casting software as those areas are closely
related.
3. Sketchflow
Sketch Flow, a feature of Microsoft Expression Studio Ultimate, gives the ability to quickly
and effectively map out and iterate the flow of an application UI, the layout of individual screens
and transition from one application state to another.
• Interactive Visual Tool
• Easy to learn
• Dynamic
• Provides enviroment to collect feedback
4. Visual Basic
One of the most popular tools for Rapid Prototyping is Visual Basic (VB). Microsoft Access,
which includes a Visual Basic extensibility module, is also a widely accepted prototyping tool
that is used by many non-technical business analysts. Although VB is a programming language it
has many features that facilitate using it to create prototypes, including:
• An interactive/visual user interface design tool.
• Easy connection of user interface components to underlying functional behavior.
• Modifications to the resulting software are easy to perform.
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5. Requirements Engineering Environment
It provides an integrated toolset for rapidly representing, building, and executing models
of critical aspects of complex systems.
It is currently used by the Air Force to develop systems. It is: an integrated set of tools
that allows systems analysts to rapidly build functional, user interface, and performance
prototype models of system components. These modeling activities are performed to gain a
greater understanding of complex systems and lessen the impact that inaccurate requirement
specifications have on cost and scheduling during the system development process.
REE is composed of three parts. The first, called proto is a CASE tool specifically
designed to support rapid prototyping. The second part is called the Rapid Interface Prototyping
System or RIP, which is a collection of tools that facilitate the creation of user interfaces. The
third part of REE is a user interface to RIP and proto that is graphical and intended to be easy to
use.
Rome Laboratory, the developer of REE, intended that to support their internal requirements
gathering methodology. Their method has three main parts:
• Elicitation from various sources which means u loose (users, interfaces to other systems),
specification, and consistency checking
• Analysis that the needs of diverse users taken together do not conflict and are technically
and economically feasible
• Validation that requirements so derived are an accurate reflection of user needs.
6. LYMB
LYMB is an object-oriented development environment aimed at developing applications
that require combining graphics-based user interfaces, visualization, and rapid prototyping.
7. Non-relational environments
Non-relational definition of data (e.g. using Cache or associative models can help make
end-user prototyping more productive by delaying or avoiding the need to normalize data at
every iteration of a simulation. This may yield earlier/greater clarity of business requirements,
though it does not specifically confirm that requirements are technically and economically
feasible in the target production system.
8. PSDL
PSDL is a prototype description language to describe real-time software.
Prototyping in the Software Process
System prototyping
• Prototyping is the rapid development of a system
• In the past, the developed system was normally thought of as inferior in some way to the
required system so further development was required
• Now, the boundary between prototyping and normal system development is blurred and
many systems are developed using an evolutionary approach
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Uses of system prototypes
• The principal use is to help customers and developers understand the requirements for the
system
• Requirements elicitation. Users can experiment with a prototype to see how the
system supports their work
• Requirements validation. The prototype can reveal errors and omissions in the
requirements
• Prototyping can be considered as a risk reduction activity which reduces requirements risks
Prototyping benefits
• Misunderstandings between software users and developers are exposed
• Missing services may be detected and confusing services may be identified
• A working system is available early in the process
• The prototype may serve as a basis for deriving a system specification
• The system can support user training and system testing
Prototyping process
Establish
prototype
objectives
Define
prototype
functionality
Develop
prototype
Evaluate
prototype
Prototyping
plan
Outline
definition
Executable
prototype
Evaluation
report
Prototyping in the software process
• Evolutionary prototyping
• An approach to system development where an initial prototype is produced and
refined through a number of stages to the final system
• Throw-away prototyping
• A prototype which is usually a practical implementation of the system is produced to
help discover requirements problems and then discarded. The system is then
developed using some other development process
Data Model
• Used to describe the logical structure of data processed by the system
• Entity-relation-attribute model sets out the entities in the system, the relationships between
these entities and the entity attributes
• Widely used in database design. Can readily be implemented using relational databases
• No specific notation provided in the UML but objects and associations can be used
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Behavioural Model
• Behavioural models are used to describe the overall behaviour of a system
• Two types of behavioural model are shown here
• Data processing models that show how data is processed as it moves through the system
• State machine models that show the systems response to events
• Both of these models are required for a description of the system‘s behaviour
1. Data-processing models
• Data flow diagrams are used to model the system‘s data processing
• These show the processing steps as data flows through a system
• Intrinsic part of many analysis methods
• Simple and intuitive notation that customers can understand
• Show end-to-end processing of data
Data flow diagrams
• DFDs model the system from a functional perspective
• Tracking and documenting how the data associated with a process is helpful to develop an
overall understanding of the system
• Data flow diagrams may also be used in showing the data exchange between a system and
other systems in its environment
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Order processing DFD
2. State machine models
• These model the behaviour of the system in response to external and internal events
• They show the system‘s responses to stimuli so are often used for modelling real-time
systems
• State machine models show system states as nodes and events as arcs between these nodes.
• When an event occurs, the system moves from one state to another
• Statecharts are an integral part of the UML
Microwave oven model
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Statecharts
• Allow the decomposition of a model into submodels
• A brief description of the actions is included following the ‗do‘ in each state
• Can be complemented by tables describing the states and the stimuli
Structured Analysis
• The data-flow approach is typified by the Structured Analysis method (SA)
• Two major strategies dominate structured analysis
• ‗Old‘ method popularised by DeMarco
• ‗Modern‘ approach by Yourdon
DeMarco
• A top-down approach
• The analyst maps the current physical system onto the current logical data-flow
model
• The approach can be summarised in four steps:
• Analysis of current physical system
• Derivation of logical model
• Derivation of proposed logical model
• Implementation of new physical system
Modern structured analysis
• Distinguishes between user‘s real needs and those requirements that represent the external
behaviour satisfying those needs
• Includes real-time extensions
• Other structured analysis approaches include:
• Structured Analysis and Design Technique (SADT)
• Structured Systems Analysis and Design Methodology (SSADM)
Method weaknesses
• They do not model non-functional system requirements.
• They do not usually include information about whether a method is appropriate for a given
problem.
• The may produce too much documentation.
• The system models are sometimes too detailed and difficult for users to understand.
CASE workbenches
• A coherent set of tools that is designed to support related software process activities such as
analysis, design or testing.
• Analysis and design workbenches support system modelling during both requirements
engineering and system design.
• These workbenches may support a specific design method or may provide support for a
creating several different types of system model.
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An analysis and design workbench
Data
dictionary
Structur ed
diag ram m ing
tools
Repor t
gener ation
facilities
Code
gener ator
Centr al
infor mation
repository
Query
langua ge
facilities
Forms
cr ea tion
tools
Design, anal y sis
and checking
tools
Im port/e xpor t
facilities
Analysis workbench components
• Diagram editors
• Model analysis and checking tools
• Repository and associated query language
• Data dictionary
• Report definition and generation tools
• Forms definition tools
• Import/export translators
• Code generation tools
Data Dictionary
• Data dictionaries are lists of all of the names used in the system models. Descriptions of the
entities, relationships and attributes are also included
• Advantages
• Support name management and avoid duplication
• Store of organisational knowledge linking analysis, design and implementation
• Many CASE workbenches support data dictionaries
Data dictionary entries
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UNIT III
ANALYSIS, DESIGN CONCEPTS AND PRINCIPLES
Design Concepts and Principles:
• Map the information from the analysis model to the design representations - data design,
architectural design, interface design, procedural design
Analysis to Design:
Design Models – 1:
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• Data Design
– created by transforming the data dictionary and ERD into implementation data
structures
– requires as much attention as algorithm design
• Architectural Design
– derived from the analysis model and the subsystem interactions defined in the
DFD
• Interface Design
– derived from DFD and CFD
– describes software elements communication with
• other software elements
• other systems
• human users
Design Models – 2 :
• Procedure-level design
– created by transforming the structural elements defined by the software
architecture into procedural descriptions of software components
– Derived from information in the PSPEC, CSPEC, and STD
Design Principles – 1:
• Process should not suffer from tunnel vision – consider alternative approaches
• Design should be traceable to analysis model
• Do not try to reinvent the wheel
- use design patterns ie reusable components
• Design should exhibit both uniformity and integration
• Should be structured to accommodate changes
Design Principles – 2 :
• Design is not coding and coding is not design
• Should be structured to degrade gently, when bad data, events, or operating conditions
are encountered
• Needs to be assessed for quality as it is being created
• Needs to be reviewed to minimize conceptual (semantic) errors
Design Concepts -1 :
• Abstraction
– allows designers to focus on solving a problem without being concerned about
irrelevant lower level details
Procedural abstraction is a named sequence of instructions that has a specific and limited
function
e.g open a door
Open implies a long sequence of procedural steps
data abstraction is collection of data that describes a data object
e.g door type, opening mech, weight,dimen
Design Concepts -2 :
• Design Patterns
– description of a design structure that solves a particular design problem within a
specific context and its impact when applied
Design Concepts -3 :
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• Software Architecture
– overall structure of the software components and the ways in which that structure
– provides conceptual integrity for a system
Design Concepts -4 :
• Information Hiding
– information (data and procedure) contained within a module is inaccessible to
modules that have no need for such information
• Functional Independence
– achieved by developing modules with single-minded purpose and an aversion to
excessive interaction with other models
Refactoring – Design concepts :
• Fowler [FOW99] defines refactoring in the following manner:
– "Refactoring is the process of changing a software system in such a way that it
does not alter the external behavior of the code [design] yet improves its internal
structure.‖
• When software is refectories, the existing design is examined for
– redundancy
– unused design elements
– inefficient or unnecessary algorithms
– poorly constructed or inappropriate data structures
– or any other design failure that can be corrected to yield a better design.
Design Concepts – 4 :
• Objects
– encapsulate both data and data manipulation procedures needed to describe the
content and behavior of a real world entity
• Class
– generalized description (template or pattern) that describes a collection of similar
objects
• Inheritance
– provides a means for allowing subclasses to reuse existing superclass data and
procedures; also provides mechanism for propagating changes
Design Concepts – 5:
• Messages
– the means by which objects exchange information with one another
• Polymorphism
– a mechanism that allows several objects in an class hierarchy to have different
methods with the same name
– instances of each subclass will be free to respond to messages by calling their own
version of the method
Modular Design Methodology Evaluation – 1:
Modularity
– the degree to which software can be understood by examining its components
independently of one another
• Modular decomposability
– provides systematic means for breaking problem into sub problems
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• Modular compos ability
– supports reuse of existing modules in new systems
• Modular understandability
– module can be understood as a stand-alone unit
Modular Design Methodology Evaluation – 2:
• Modular continuity
– module change side-effects minimized
• Modular protection
– processing error side-effects minimized
Effective Modular Design:
• Functional independence
– modules have high cohesion and low coupling
• Cohesion
– qualitative indication of the degree to which a module focuses on just one thing
• Coupling
– qualitative indication of the degree to which a module is connected to other
modules and to the outside world
Architectural Design:
Why Architecture?
The architecture is not the operational software. Rather, it is a representation that enables a
software engineer to:
(1) analyze the effectiveness of the design in meeting its stated requirements,
(2) consider architectural alternatives at a stage when making design changes is still relatively
easy, and
(3) reduce the risks associated with the construction of the software.
Importance :
• Software architecture representations enable communications among stakeholders
• Architecture highlights early design decisions that will have a profound impact on the
ultimate success of the system as an operational entity
• The architecture constitutes an intellectually graspable model of how the system is
structured and how its components work together
Architectural Styles – 1:
• Data centered
– file or database lies at the center of this architecture and is accessed frequently by
other components that modify data
Architectural Styles – 2:
• Data flow
– input data is transformed by a series of computational components into output
data
– Pipe and filter pattern has a set of components called filters, connected by pipes
that transmit data from one component to the next.
– If the data flow degenerates into a single line of transforms, it is termed batch
sequential
• Object-oriented
– components of system encapsulate data and operations, communication between
components is by message passing
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• Layered
– several layers are defined
– each layer performs operations that become closer to the machine instruction set
in the lower layers
Architectural Styles – 3:
Call and return
– program structure decomposes function into control hierarchy with main program
invoking several subprograms
Software Architecture Design – 1:
• Software to be developed must be put into context
– model external entities and define interfaces
• Identify architectural archetypes
– collection of abstractions that must be modeled if the system is to be constructed
Object oriented Architecture :
• The components of a system encapsulate data and the operations that must be applied to
manipulate the data. Communication and coordination between components is
accomplished via message passing
Software Architecture Design – 2:
• Specify structure of the system
– define and refine the software components needed to implement each archetype
• Continue the process iteratively until a complete architectural structure has been derived
Layered Architecture:
• Number of different layers are defined, each accomplishing operations that progressively
become closer to the machine instruction set
• At the outer layer –components service user interface operations.
• At the inner layer – components perform operating system interfacing.
• Intermediate layers provide utility services and application software function
Architecture Tradeoff Analysis – 1:
1. Collect scenarios
2. Elicit requirements, constraints, and environmental description
3. Describe architectural styles/patterns chosen to address scenarios and requirements
• module view
• process view
• data flow view
Architecture Tradeoff Analysis – 2:
4. Evaluate quality attributes independently (e.g. reliability, performance, security,
maintainability, flexibility, testability, portability, reusability, interoperability)
5. Identify sensitivity points for architecture
• any attributes significantly affected by changing in the architecture
Refining Architectural Design:
• Processing narrative developed for each module
• Interface description provided for each module
• Local and global data structures are defined
• Design restrictions/limitations noted
• Design reviews conducted
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• Refinement considered if required and justified
Architectural Design
• An early stage of the system design process.
• Represents the link between specification and design processes.
• Often carried out in parallel with some specification activities.
• It involves identifying major system components and their communications.
Advantages of explicit architecture
• Stakeholder communication
- Architecture may be used as a focus of discussion by system stakeholders.
• System analysis
- Means that analysis of whether the system can meet its non-functional requirements is
possible.
• Large-scale reuse
- The architecture may be reusable across a range of systems.
Architecture and system characteristics
• Performance
- Localise critical operations and minimise communications. Use large rather than fine-
grain components.
• Security
- Use a layered architecture with critical assets in the inner layers.
• Safety
- Localise safety-critical features in a small number of sub-systems.
• Availability
- Include redundant components and mechanisms for fault tolerance.
• Maintainability
- Use fine-grain, replaceable components.
Architectural conflicts
• Using large-grain components improves performance but reduces maintainability.
• Introducing redundant data improves availability but makes security more difficult.
• Localising safety-related features usually means more communication so degraded
performance.
System structuring
• Concerned with decomposing the system into interacting sub-systems.
• The architectural design is normally expressed as a block diagram presenting an overview of
the system structure.
• More specific models showing how sub-systems share data, are distributed and interface with
each other may also be developed.
Packing robot control system
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Box and line diagrams
• Very abstract - they do not show the nature of component relationships nor the externally
visible properties of the sub-systems.
• However, useful for communication with stakeholders and for project planning.
Architectural design decisions
• Architectural design is a creative process so the process differs depending on the type of
system being developed.
• However, a number of common decisions span all design processes.
• Is there a generic application architecture that can be used?
• How will the system be distributed?
• What architectural styles are appropriate?
• What approach will be used to structure the system?
• How will the system be decomposed into modules?
• What control strategy should be used?
• How will the architectural design be evaluated?
• How should the architecture be documented?
Architecture reuse
• Systems in the same domain often have similar architectures that reflect domain concepts.
• Application product lines are built around a core architecture with variants that satisfy
particular customer requirements.
Architectural styles
• The architectural model of a system may conform to a generic architectural model or style.
• An awareness of these styles can simplify the problem of defining system architectures.
• However, most large systems are heterogeneous and do not follow a single architectural
style.
Architectural models
• Used to document an architectural design.
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• Static structural model that shows the major system components.
• Dynamic process model that shows the process structure of the system.
• Interface model that defines sub-system interfaces.
• Relationships model such as a data-flow model that shows sub-system relationships.
• Distribution model that shows how sub-systems are distributed across computers.
System organisation
• Reflects the basic strategy that is used to structure a system.
• Three organisational styles are widely used:
• A shared data repository style;
• A shared services and servers style;
• An abstract machine or layered style.
The repository model
• Sub-systems must exchange data. This may be done in two ways:
• Shared data is held in a central database or repository and may be accessed by all sub-
systems;
• Each sub-system maintains its own database and passes data explicitly to other sub-
systems.
• When large amounts of data are to be shared, the repository model of sharing is most
commonly used.
CASE toolset architecture
Repository model characteristics
Advantages
• Efficient way to share large amounts of data;
• Sub-systems need not be concerned with how data is produced Centralised management
e.g. backup, security, etc.
• Sharing model is published as the repository schema.
Disadvantages
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• Sub-systems must agree on a repository data model. Inevitably a compromise;
• Data evolution is difficult and expensive;
• No scope for specific management policies;
• Difficult to distribute efficiently.
Client-server model
• Distributed system model which shows how data and processing is distributed across a range
of components.
• Set of stand-alone servers which provide specific services such as printing, data management,
etc.
• Set of clients which call on these services.
• Network which allows clients to access servers.
Client-server characteristics
Advantages
• Distribution of data is straightforward;
• Makes effective use of networked systems. May require cheaper hardware;
• Easy to add new servers or upgrade existing servers.
Disadvantages
• No shared data model so sub-systems use different data organisation. Data
interchange may be inefficient;
• Redundant management in each server;
• No central register of names and services - it may be hard to find out what servers
and services are available.
Abstract machine (layered) model
• Used to model the interfacing of sub-systems.
• Organises the system into a set of layers (or abstract machines) each of which provide a set
of services.
• Supports the incremental development of sub-systems in different layers. When a layer
interface changes, only the adjacent layer is affected.
• However, often artificial to structure systems in this way.
Modular decomposition styles
• Styles of decomposing sub-systems into modules.
• No rigid distinction between system organisation and modular decomposition.
Sub-systems and modules
• A sub-system is a system in its own right whose operation is independent of the services
provided by other sub-systems.
• A module is a system component that provides services to other components but would not
normally be considered as a separate system.
• Modular decomposition
• Another structural level where sub-systems are decomposed into modules.
• Two modular decomposition models covered
• An object model where the system is decomposed into interacting object;
• A pipeline or data-flow model where the system is decomposed into functional
modules which transform inputs to outputs.
• If possible, decisions about concurrency should be delayed until modules are implemented.
Object models
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• Structure the system into a set of loosely coupled objects with well-defined interfaces.
• Object-oriented decomposition is concerned with identifying object classes, their attributes
and operations.
• When implemented, objects are created from these classes and some control model used to
coordinate object operations.
Invoice processing system
Object model advantages
• Objects are loosely coupled so their implementation can be modified without affecting other
objects.
• The objects may reflect real-world entities.
• OO implementation languages are widely used.
• However, object interface changes may cause problems and complex entities may be hard to
represent as objects.
Function-oriented pipelining
• Functional transformations process their inputs to produce outputs.
• May be referred to as a pipe and filter model (as in UNIX shell).
• Variants of this approach are very common. When transformations are sequential, this is a
batch sequential model which is extensively used in data processing systems.
• Not really suitable for interactive systems.
User interface design
• Designing effective interfaces for software systems
• System users often judge a system by its interface rather than its functionality
• A poorly designed interface can cause a user to make catastrophic errors
• Poor user interface design is the reason why so many software systems are never used
• Most users of business systems interact with these systems through graphical user interfaces
(GUIs)
• In some cases, legacy text-based interfaces are still used
User interface design process
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Analyse and
understand user
activities
Produce paper-
based des ign
prototype
Evaluate design
wi th end-users
Design
prototype
Produce
dynamic design
prototype
Eval uate design
with end-users
UI design principles
• User familiarity
Executable
prototype
Implement
final user
int erface
• The interface should be based on user-oriented terms and concepts rather than
computer concepts
• E.g., an office system should use concepts such as letters, documents, folders etc.
rather than directories, file identifiers, etc.
• Consistency
• The system should display an appropriate level of consistency
• Commands and menus should have the same format, command punctuation should be
similar, etc.
• Minimal surprise
• If a command operates in a known way, the user should be able to predict the
operation of comparable commands
• Recoverability
• The system should provide some interface to user errors and allow the user to recover
from errors
• User guidance
• Some user guidance such as help systems, on-line manuals, etc. should be supplied
• User diversity
• Interaction facilities for different types of user should be supported
• E.g., some users have seeing difficulties and so larger text should be available
User-system interaction
• Two problems must be addressed in interactive systems design
• How should information from the user be provided to the computer system?
• How should information from the computer system be presented to the user?
Interaction styles
• Direct manipulation
• Easiest to grasp with immediate feedback
• Difficult to program
• Menu selection
• User effort and errors minimized
• Large numbers and combinations of choices a problem
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!
• Form fill-in
• Ease of use, simple data entry
• Tedious, takes a lot of screen space
• Natural language
• Great for casual users
• Tedious for expert users
Information presentation
• Information presentation is concerned with presenting system information to system users
• The information may be presented directly or may be transformed in some way for
presentation
• The Model-View-Controller approach is a way of supporting multiple presentations of data
Information display
1
0 10 20
4 2
3
Dial with needle Pie chart Thermometer Horizontal bar
Displaying relative values
Pressure Temperature
0 100 200 300 400 0 25 50 75 100
Textual highlighting
The filename you have chosen h as been
used. Please choose an other name
Ch. 16 User interface design
OK Cancel
Data visualisation
• Concerned with techniques for displaying large amounts of information
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• Visualisation can reveal relationships between entities and trends in the data
• Possible data visualisations are:
• Weather information
• State of a telephone network
• Chemical plant pressures and temperatures
• A model of a molecule
Colour displays
• Colour adds an extra dimension to an interface and can help the user understand complex
information structures
• Can be used to highlight exceptional events
• The use of colour to communicate meaning
Error messages
• Error message design is critically important. Poor error messages can mean that a user
rejects rather than accepts a system
• Messages should be polite, concise, consistent and constructive
• The background and experience of users should be the determining factor in message
design
User interface evaluation
• Some evaluation of a user interface design should be carried out to assess its suitability
• Full scale evaluation is very expensive and impractical for most systems
• Ideally, an interface should be evaluated against req
• However, it is rare for such specifications to be produced
Real Time Software Design
• Systems which monitor and control their environment
• Inevitably associated with hardware devices
• Sensors: Collect data from the system environment
• Actuators: Change (in some way) the system's environment
• Time is critical. Real-time systems MUST respond within specified times
• A real-time system is a software system where the correct functioning of the system depends
on the results produced by the system and the time at which these results are produced
• A ‗soft‘ real-time system is a system whose operation is degraded if results are not produced
according to the specified timing requirements
• A ‗hard‘ real-time system is a system whose operation is incorrect if results are not produced
according to the timing specification
Stimulus/Response Systems
• Given a stimulus, the system must produce a response within a specified time
• 2 classes
• Periodic stimuli. Stimuli which occur at predictable time intervals
• For example, a temperature sensor may be polled 10 times per second
• Aperiodic stimuli. Stimuli which occur at unpredictable times
• For example, a system power failure may trigger an interrupt which must be
processed by the system
Architectural considerations
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• Because of the need to respond to timing demands made by different stimuli / responses, the
system architecture must allow for fast switching between stimulus handlers
• Timing demands of different stimuli are different so a simple sequential loop is not usually
adequate
Real –Time Software Design:
• Designing embedded software systems whose behaviour is subject to timing constraints
• To explain the concept of a real-time system and why these systems are usually
implemented as concurrent processes
• To describe a design process for real-time systems
• To explain the role of a real-time executive
• To introduce generic architectures for monitoring and control and data acquisition
systems
Real-time systems:
• Systems which monitor and control their environment
• Inevitably associated with hardware devices
– Sensors: Collect data from the system environment
– Actuators: Change (in some way) the system's
environment
• Time is critical. Real-time systems MUST respond within specified times
Definition:
• A real-time system is a software system where the correct functioning of the system
depends on the results produced by the system and the time at which these results are
produced
• A ‗soft‘ real-time system is a system whose operation is degraded if results are not
produced according to the specified timing requirements
• A ‗hard‘ real-time system is a system whose operation is incorrect if results are not
produced according to the timing specification
Stimulus/Response Systems:
• Given a stimulus, the system must produce a esponse within a specified time
• Periodic stimuli. Stimuli which occur at predictable time intervals
– For example, a temperature sensor may be polled 10 times per second
• Aperiodic stimuli. Stimuli which occur at unpredictable times
– For example, a system power failure may trigger an interrupt which must be
processed by the system
Architectural considerations:
• Because of the need to respond to timing demands made by different stimuli/responses,
the system architecture must allow for fast switching between stimulus handlers
• Timing demands of different stimuli are different so a simple sequential loop is not
usually adequate
• Real-time systems are usually designed as cooperating processes with a real-time
executive controlling these processes
A real-time system model:
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Sensor Sensor Sensor Sensor Sensor Sensor
Real-time con
trol system
Actuator Actuator Actuator Actuator
System elements:
• Sensors control processes
– Collect information from sensors. May buffer information collected in response to
a sensor stimulus
• Data processor
– Carries out processing of collected information and computes the system response
• Actuator control
– Generates control signals for the actuator
R-T systems design process:
• Identify the stimuli to be processed and the required responses to these stimuli
• For each stimulus and response, identify the timing constraints
• Aggregate the stimulus and response processing into concurrent processes. A process
may be associated with each class of stimulus and response
• Design algorithms to process each class of stimulus and response. These must meet the
given timing requirements
• Design a scheduling system which will ensure that processes are started in time to meet
their deadlines
• Integrate using a real-time executive or operating system
Timing constraints:
• May require extensive simulation and experiment to ensure that these are met by the
system
• May mean that certain design strategies such as object-oriented design cannot be used
because of the additional overhead involved
• May mean that low-level programming language features have to be used for
performance reasons
Real-time programming:
• Hard-real time systems may have to programmed in assembly language to ensure that
deadlines are met
• Languages such as C allow efficient programs to be written but do not have constructs to
support concurrency or shared resource management
• Ada as a language designed to support real-time systems design so includes a general
purpose concurrency mechanism
Non-stop system components:
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• Configuration manager
– Responsible for the dynamic reconfiguration of the system
software and hardware. Hardware modules may be replaced and software
upgraded without stopping the systems
• Fault manager
– Responsible for detecting software and hardware faults and
taking appropriate actions (e.g. switching to backup disks) to ensure that the
system continues in operation
Burglar alarm system e.g
• A system is required to monitor sensors on doors and windows to detect the presence of
intruders in a building
• When a sensor indicates a break-in, the system switches on lights around the area and
calls police automatically
• The system should include provision for operation without a mains power supply
• Sensors
• Movement detectors, window sensors, door sensors.
• 50 window sensors, 30 door sensors and 200 movement detectors
• Voltage drop sensor
• Actions
• When an intruder is detected, police are called automatically.
• Lights are switched on in rooms with active sensors.
• An audible alarm is switched on.
• The system switches automatically to backup power when a voltage drop is
detected.
The R-T system design process:
• Identify stimuli and associated responses
• Define the timing constraints associated with each stimulus and response
• Allocate system functions to concurrent processes
• Design algorithms for stimulus processing and response generation
• Design a scheduling system which ensures that processes will always be scheduled to
meet their deadlines
Control systems:
• A burglar alarm system is primarily a monitoring system. It collects data from sensors but
no real-time actuator control
• Control systems are similar but, in response to sensor values, the system sends control
signals to actuators
• An example of a monitoring and control system is a system which monitors temperature
and switches heaters on and off
Data acquisition systems:
• Collect data from sensors for subsequent processing and analysis.
• Data collection processes and processing processes may have different periods and
deadlines.
• Data collection may be faster than processing e.g. collecting information about an
explosion.
• Circular or ring buffers are a mechanism for smoothing speed differences.
49. Tnlearners and webexpo
A temperature control system:
500Hz
Sensor
process
500Hz
Sensor
values
Thermostat
process
500Hz
Switch command
Room number Thermostat process
Heater control
process
Furnace
control process
Reactor data collection:
• A system collects data from a set of sensors monitoring the neutron flux from a nuclear
reactor.
• Flux data is placed in a ring buffer for later processing.
• The ring buffer is itself implemented as a concurrent process so that the collection and
processing processes may be synchronized.
Reactor flux monitoring:
Sensors (each data flow is a sensor value)
Sensor
identifier and
value
Processed
flux level
Sensor
process
Sensor data
buffer
Process
data
Display
Mutual exclusion:
• Producer processes collect data and add it to the buffer. Consumer processes take data
from the buffer and make elements available
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• Producer and consumer processes must be mutually excluded from accessing the same
element.
The buffer must stop producer processes adding information to a full buffer and consumer
processes trying to take information from an empty buffer
System Design
• Design both the hardware and the software associated with system. Partition functions to
either hardware or software
• Design decisions should be made on the basis on non-functional system requirements
• Hardware delivers better performance but potentially longer development and less scope for
change
System elements
• Sensors control processes
• Collect information from sensors. May buffer information collected in response to a
sensor stimulus
• Data processor
• Carries out processing of collected information and computes the system response
• Actuator control
• Generates control signals for the actuator
Sensor/actuator processes
Senso r Actuat or
St imulus Response
Sensor
control
Data
p ro ces so r
Actuat or
control
Hardware and software design
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Establishsystem
requirements
Partition requ
irements
Software
requir ements
Hardware
requirements
Software
design
Hardware
design
R-T systems design process
• Identify the stimuli to be processed and the required responses to these stimuli
• For each stimulus and response, identify the timing constraints
• Aggregate the stimulus and response processing into concurrent processes. A process may be
associated with each class of stimulus and response
• Design algorithms to process each class of stimulus and response. These must meet the given
timing requirements
• Design a scheduling system which will ensure that processes are started in time to meet their
deadlines
• Integrate using a real-time executive or operating system
Timing constraints
• For aperiodic stimuli, designers make assumptions about probability of occurrence of stimuli.
• May mean that certain design strategies such as object-oriented design cannot be used
because of the additional overhead involved
State machine modelling
• The effect of a stimulus in a real-time system may trigger a transition from one state to
another.
• Finite state machines can be used for modelling real-time systems.
• However, FSM models lack structure. Even simple systems can have a complex model.
• The UML includes notations for defining state machine models
Microwave oven state machine