This document discusses software design principles and concepts. It covers key aspects of software design such as data design, architectural design, interface design, component design, abstraction, refinement, modularity, architecture, control hierarchy, structural partitioning, data structures, software procedures, and information hiding. The document emphasizes that software design is an iterative process that translates requirements into a blueprint for constructing software. Good design principles include traceability, reuse, and accommodating change. Modular design aims for functional independence, cohesion and low coupling between modules.
Library Management System Waterfall Modelmitwa1990
The document provides a summary of a team project to develop a Computerized Library Management System called Quick Access. It outlines the team members, topics to be covered which include objectives, competitive analysis, system functionality, non-functional requirements and future enhancements. It also discusses the project management approach including using a waterfall model, estimating time and costs using a work breakdown structure, and identifying risks.
Project Managing An Implementation Of A Library Management Systemianbays
The document provides guidance for project managing the implementation of a new library management system (LMS). It discusses planning all aspects of the project including timelines, resources, budgets, and testing. It emphasizes clear communication, addressing issues promptly, and maintaining positive relationships between all parties involved. The goal is to deliver the new system on time, on budget, and meeting all specifications while allowing for changes and unexpected challenges that may occur.
10 steps to successfully implement your new library softwareClaire Stokoe
A how to guide on how to implement library software into your current system. These slides take you through the basics of what to look out for, any pit falls and how to plan the process. Its a very easy to follow guide, illustrated with images to help you.
This document is a project report on a Library Management System created by Mahdeep Bisht and Himanshu Dumaga for their class XII computer science project. The report includes an introduction describing the project, objectives of creating a software for library management, a proposed system describing how such a system would work, phases of the system development life cycle used to create the project including planning, analysis, design, implementation, testing and deployment. It also includes contents, acknowledgements and screenshots of the output of the library management software created.
This document provides an overview of software engineering concepts related to software design. It discusses the definition and activities of software design, including preliminary and detailed design. It covers software design principles, considerations, and processes. It also describes various software design tools like data flow diagrams, structure charts, and entity-relationship models. Finally, it discusses object-oriented design, user interface design, data design, architectural design, interface design, and component-level design.
This document provides an overview of several common software architecture patterns: layered architecture, event-driven architecture, microkernel architecture, microservices architecture, and space-based architecture. Each pattern is described in terms of its components and characteristics. The patterns are then analyzed and rated on criteria such as agility, deployment ease, testability, performance, scalability, and development ease. Layered architecture is the most common pattern but scores low on many criteria, while event-driven architecture, microkernel architecture, and microservices architecture provide higher agility and scalability at the cost of lower testability and development ease. Space-based architecture is the most difficult to implement but provides high performance and scalability for applications with unpredictable concurrent user volumes
This document discusses different software design strategies, including top-down, bottom-up, and hybrid approaches. Top-down design starts with a generalized model and defines more specific parts, eventually composing the whole system. Bottom-up design starts with basic components and builds higher levels by composing lower levels until the desired system is evolved. A hybrid approach combines top-down and bottom-up methods. The document provides examples of when each strategy is typically used.
Requirement analysis and UML modelling in Software engineeringsnehalkulkarni74
Receptionist
Patient: Patient
Doctor: Doctor
- The vertical solid line represents the life of an
object.
- It runs from top to bottom.
Messages:-
- The arrow represents the message passing
between objects.
- The arrow head points to the receiver.
- The message name is written near arrow.
- Synchronous and asynchronous message
Receptionist
Patient
Doctor
makeAppointment()
checkAvailability()
scheduleAppointment()
confirmAppointment()
treatPatient()
billPatient()
- Sequence diagram shows the time sequence of
messages between objects.
- It emphasizes on
Library Management System Waterfall Modelmitwa1990
The document provides a summary of a team project to develop a Computerized Library Management System called Quick Access. It outlines the team members, topics to be covered which include objectives, competitive analysis, system functionality, non-functional requirements and future enhancements. It also discusses the project management approach including using a waterfall model, estimating time and costs using a work breakdown structure, and identifying risks.
Project Managing An Implementation Of A Library Management Systemianbays
The document provides guidance for project managing the implementation of a new library management system (LMS). It discusses planning all aspects of the project including timelines, resources, budgets, and testing. It emphasizes clear communication, addressing issues promptly, and maintaining positive relationships between all parties involved. The goal is to deliver the new system on time, on budget, and meeting all specifications while allowing for changes and unexpected challenges that may occur.
10 steps to successfully implement your new library softwareClaire Stokoe
A how to guide on how to implement library software into your current system. These slides take you through the basics of what to look out for, any pit falls and how to plan the process. Its a very easy to follow guide, illustrated with images to help you.
This document is a project report on a Library Management System created by Mahdeep Bisht and Himanshu Dumaga for their class XII computer science project. The report includes an introduction describing the project, objectives of creating a software for library management, a proposed system describing how such a system would work, phases of the system development life cycle used to create the project including planning, analysis, design, implementation, testing and deployment. It also includes contents, acknowledgements and screenshots of the output of the library management software created.
This document provides an overview of software engineering concepts related to software design. It discusses the definition and activities of software design, including preliminary and detailed design. It covers software design principles, considerations, and processes. It also describes various software design tools like data flow diagrams, structure charts, and entity-relationship models. Finally, it discusses object-oriented design, user interface design, data design, architectural design, interface design, and component-level design.
This document provides an overview of several common software architecture patterns: layered architecture, event-driven architecture, microkernel architecture, microservices architecture, and space-based architecture. Each pattern is described in terms of its components and characteristics. The patterns are then analyzed and rated on criteria such as agility, deployment ease, testability, performance, scalability, and development ease. Layered architecture is the most common pattern but scores low on many criteria, while event-driven architecture, microkernel architecture, and microservices architecture provide higher agility and scalability at the cost of lower testability and development ease. Space-based architecture is the most difficult to implement but provides high performance and scalability for applications with unpredictable concurrent user volumes
This document discusses different software design strategies, including top-down, bottom-up, and hybrid approaches. Top-down design starts with a generalized model and defines more specific parts, eventually composing the whole system. Bottom-up design starts with basic components and builds higher levels by composing lower levels until the desired system is evolved. A hybrid approach combines top-down and bottom-up methods. The document provides examples of when each strategy is typically used.
Requirement analysis and UML modelling in Software engineeringsnehalkulkarni74
Receptionist
Patient: Patient
Doctor: Doctor
- The vertical solid line represents the life of an
object.
- It runs from top to bottom.
Messages:-
- The arrow represents the message passing
between objects.
- The arrow head points to the receiver.
- The message name is written near arrow.
- Synchronous and asynchronous message
Receptionist
Patient
Doctor
makeAppointment()
checkAvailability()
scheduleAppointment()
confirmAppointment()
treatPatient()
billPatient()
- Sequence diagram shows the time sequence of
messages between objects.
- It emphasizes on
This document discusses key concepts in software design engineering including analysis models, design models, the programmer's approach versus best practices, purposes of design, quality guidelines, design principles, fundamental concepts like abstraction and architecture, and specific design concepts like patterns, modularity, and information hiding. It emphasizes that design is important for translating requirements into a quality software solution before implementation begins.
The document discusses key aspects of the software design process including that design is iterative and represented at a high level of abstraction, guidelines for quality design include modularity, information hiding, and functional independence, and architectural design defines system context and archetypes that compose the system.
The document discusses key design concepts in software engineering including abstraction, architecture, patterns, separation of concerns, modularity, information hiding, refinement, functional independence, aspects, refactoring, object-oriented design concepts, and design classes. It provides details on each concept, their importance in software design, and how they lead to the development of high-quality software.
The document provides an overview of basic software design concepts including the design process, quality factors, techniques, methodologies, approaches, models, modularization, data design, guidelines, verification, and key issues. It discusses that software design is an iterative process of translating requirements into a system blueprint. The design process involves informal to more formal designs. Quality factors, architectures, technologies, styles, and decomposition are considered. Top-down and bottom-up approaches are described. Modularization, data design, and guidelines are covered. Verification ensures the design is valid before implementation. Key issues are areas most prone to mistakes.
The document discusses key concepts in software design, including:
- Mitch Kapor's "software design manifesto" emphasized good design exhibiting firmness, commodity, and delight.
- Design encompasses principles, concepts, and practices that lead to high quality systems, including data/class design, architectural design, interface design, and component-level design.
- Quality guidelines for design include modularity, distinct representations of elements, appropriate data structures, independent components, and reduced complexity interfaces.
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.
The document discusses the differences between analysis modeling and design engineering/modeling. Analysis involves understanding a problem, while design focuses on creating a solution. Models can be used to better understand problems in analysis or solutions in design. The key aspects of design engineering are then outlined, including translating requirements into a software blueprint, iterating on the design, and ensuring quality through guidelines such as modularity, information hiding, and functional independence. Common design concepts like abstraction, architecture, patterns, and classes are also explained.
This document provides an overview of key concepts in software design. It begins by listing topics to be covered, including abstraction, architecture, aspects, cohesion, and more. It then asks questions about what design is, who does it, why it's important, and defines software design as implementing software solutions to problems. The document outlines the design process as transforming requirements into a blueprint. It discusses qualities of good design like being firm, suitable for purpose, and pleasurable to use. It provides guidelines like modularity and using recognizable patterns. Fundamental concepts are defined, like abstraction, architecture, patterns, separation of concerns, and object-oriented design. The elements of the design model are covered, including data, architecture, interfaces
This ppt covers the following topics :-
Introduction
Design quality
Design concepts
The design model
Thus it covers design engineering in software engineering
The document discusses various aspects of software design including:
1. The differences between design and programming and the role of a design engineer.
2. The iterative software design process of translating requirements into a blueprint for building software.
3. Key attributes like functionality, efficiency, flexibility, and usability that software design should address.
4. Fundamental software design concepts such as abstraction, architecture, modularity, and information hiding.
The document discusses key concepts in design engineering for software. It covers principles like abstraction, refinement, modularity, architecture, and information hiding that are important for developing high quality software. It emphasizes that software design is an iterative process of translating requirements into lower levels of abstraction until implementation. The goals of design are to implement all requirements, provide an understandable guide for developers and testers, and give a complete picture of the software from an implementation perspective. Guidelines are provided for characteristics of good design like modularity, distinct representations, and deriving the design from requirements analysis.
The design model transforms requirements from the analysis model into a blueprint for constructing the software. It includes four main elements: the data/class design, architectural design, interface design, and component-level design. These elements are developed iteratively through increasing levels of abstraction, starting with high-level elements that are traced to requirements and refining into lower-level representations. The design model aims to implement requirements while considering quality guidelines around modularity, patterns, and other design concepts.
This document discusses key concepts and principles of software design. It explains that software design transforms analysis models into a design model through activities like architectural design, interface design, data design, and component-level design. Some key design concepts discussed include abstraction, refinement, modularity, architecture, procedures, and information hiding. The document also covers principles of effective modular design such as high cohesion and low coupling between modules. Different types of cohesion and coupling are defined. Overall, the document provides an overview of the software design process and some fundamental concepts involved.
The document discusses various aspects of design modeling for software engineering projects. It describes how the design model builds upon the analysis model by refining and adding more implementation details to elements like data design, architectural design, interface design, and component design. It also covers important design concepts like abstraction, architecture, patterns, modularity, information hiding, and functional independence. Quality guidelines for software design are provided along with principles of object-oriented design.
The document discusses key concepts in design modeling for software engineering projects, including:
- Data/class design transforms analysis models into design class structures and data structures.
- Architectural design defines relationships between major software elements and how they interact.
- Interface, component, and other designs further refine elements from analysis into implementation-specific details.
- Design principles include traceability to analysis, avoiding reinventing solutions, and structuring for change and graceful degradation.
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 interaction design and the design process for interactive systems. It covers identifying user requirements, conceptual and physical design, prototyping and evaluation. The design process involves requirements specification, architectural design, detailed design, coding, testing, and maintenance. Iterative design and user evaluation are important to develop an acceptable product. Capturing the design rationale helps communicate decisions and supports reuse.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, requirements engineering, object-oriented fundamentals, software design, and testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, testing, and project management over 5 units. Recommended textbooks and online references are also provided.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, formulating requirements engineering concepts, understanding object-oriented fundamentals, applying software design procedures, and finding errors with testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, and testing and management over 5 units. Recommended textbooks and online references are also provided.
Module 2_ Divide and Conquer Approach.pptxnikshaikh786
The document describes the divide and conquer approach and analyzes the complexity of several divide and conquer algorithms, including binary search, merge sort, quicksort, and finding minimum and maximum values. It explains the general divide and conquer method involves three steps: 1) divide the problem into subproblems, 2) solve the subproblems, and 3) combine the solutions to solve the original problem. It then provides detailed explanations and complexity analyses of specific divide and conquer algorithms.
The document provides an introduction to analyzing the performance of algorithms. It discusses time complexity and space complexity, which measure the running time and memory usage of algorithms. Common asymptotic notations like Big-O, Big-Omega, and Big-Theta are introduced to concisely represent the growth rates of algorithms. Specific algorithms like selection sort and insertion sort are analyzed using these metrics. Recursion and recurrence relations are also covered as methods to analyze algorithm efficiency.
This document discusses key concepts in software design engineering including analysis models, design models, the programmer's approach versus best practices, purposes of design, quality guidelines, design principles, fundamental concepts like abstraction and architecture, and specific design concepts like patterns, modularity, and information hiding. It emphasizes that design is important for translating requirements into a quality software solution before implementation begins.
The document discusses key aspects of the software design process including that design is iterative and represented at a high level of abstraction, guidelines for quality design include modularity, information hiding, and functional independence, and architectural design defines system context and archetypes that compose the system.
The document discusses key design concepts in software engineering including abstraction, architecture, patterns, separation of concerns, modularity, information hiding, refinement, functional independence, aspects, refactoring, object-oriented design concepts, and design classes. It provides details on each concept, their importance in software design, and how they lead to the development of high-quality software.
The document provides an overview of basic software design concepts including the design process, quality factors, techniques, methodologies, approaches, models, modularization, data design, guidelines, verification, and key issues. It discusses that software design is an iterative process of translating requirements into a system blueprint. The design process involves informal to more formal designs. Quality factors, architectures, technologies, styles, and decomposition are considered. Top-down and bottom-up approaches are described. Modularization, data design, and guidelines are covered. Verification ensures the design is valid before implementation. Key issues are areas most prone to mistakes.
The document discusses key concepts in software design, including:
- Mitch Kapor's "software design manifesto" emphasized good design exhibiting firmness, commodity, and delight.
- Design encompasses principles, concepts, and practices that lead to high quality systems, including data/class design, architectural design, interface design, and component-level design.
- Quality guidelines for design include modularity, distinct representations of elements, appropriate data structures, independent components, and reduced complexity interfaces.
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.
The document discusses the differences between analysis modeling and design engineering/modeling. Analysis involves understanding a problem, while design focuses on creating a solution. Models can be used to better understand problems in analysis or solutions in design. The key aspects of design engineering are then outlined, including translating requirements into a software blueprint, iterating on the design, and ensuring quality through guidelines such as modularity, information hiding, and functional independence. Common design concepts like abstraction, architecture, patterns, and classes are also explained.
This document provides an overview of key concepts in software design. It begins by listing topics to be covered, including abstraction, architecture, aspects, cohesion, and more. It then asks questions about what design is, who does it, why it's important, and defines software design as implementing software solutions to problems. The document outlines the design process as transforming requirements into a blueprint. It discusses qualities of good design like being firm, suitable for purpose, and pleasurable to use. It provides guidelines like modularity and using recognizable patterns. Fundamental concepts are defined, like abstraction, architecture, patterns, separation of concerns, and object-oriented design. The elements of the design model are covered, including data, architecture, interfaces
This ppt covers the following topics :-
Introduction
Design quality
Design concepts
The design model
Thus it covers design engineering in software engineering
The document discusses various aspects of software design including:
1. The differences between design and programming and the role of a design engineer.
2. The iterative software design process of translating requirements into a blueprint for building software.
3. Key attributes like functionality, efficiency, flexibility, and usability that software design should address.
4. Fundamental software design concepts such as abstraction, architecture, modularity, and information hiding.
The document discusses key concepts in design engineering for software. It covers principles like abstraction, refinement, modularity, architecture, and information hiding that are important for developing high quality software. It emphasizes that software design is an iterative process of translating requirements into lower levels of abstraction until implementation. The goals of design are to implement all requirements, provide an understandable guide for developers and testers, and give a complete picture of the software from an implementation perspective. Guidelines are provided for characteristics of good design like modularity, distinct representations, and deriving the design from requirements analysis.
The design model transforms requirements from the analysis model into a blueprint for constructing the software. It includes four main elements: the data/class design, architectural design, interface design, and component-level design. These elements are developed iteratively through increasing levels of abstraction, starting with high-level elements that are traced to requirements and refining into lower-level representations. The design model aims to implement requirements while considering quality guidelines around modularity, patterns, and other design concepts.
This document discusses key concepts and principles of software design. It explains that software design transforms analysis models into a design model through activities like architectural design, interface design, data design, and component-level design. Some key design concepts discussed include abstraction, refinement, modularity, architecture, procedures, and information hiding. The document also covers principles of effective modular design such as high cohesion and low coupling between modules. Different types of cohesion and coupling are defined. Overall, the document provides an overview of the software design process and some fundamental concepts involved.
The document discusses various aspects of design modeling for software engineering projects. It describes how the design model builds upon the analysis model by refining and adding more implementation details to elements like data design, architectural design, interface design, and component design. It also covers important design concepts like abstraction, architecture, patterns, modularity, information hiding, and functional independence. Quality guidelines for software design are provided along with principles of object-oriented design.
The document discusses key concepts in design modeling for software engineering projects, including:
- Data/class design transforms analysis models into design class structures and data structures.
- Architectural design defines relationships between major software elements and how they interact.
- Interface, component, and other designs further refine elements from analysis into implementation-specific details.
- Design principles include traceability to analysis, avoiding reinventing solutions, and structuring for change and graceful degradation.
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 interaction design and the design process for interactive systems. It covers identifying user requirements, conceptual and physical design, prototyping and evaluation. The design process involves requirements specification, architectural design, detailed design, coding, testing, and maintenance. Iterative design and user evaluation are important to develop an acceptable product. Capturing the design rationale helps communicate decisions and supports reuse.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, requirements engineering, object-oriented fundamentals, software design, and testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, testing, and project management over 5 units. Recommended textbooks and online references are also provided.
The document provides information on a course titled "Software Engineering" taught by Dr. P. Visu at Velammal Engineering College. It includes the course objectives, outcomes, syllabus, and learning resources. The objectives are to understand software project phases, requirements engineering, object-oriented concepts, enterprise integration, and testing techniques. The outcomes cover comparing process models, formulating requirements engineering concepts, understanding object-oriented fundamentals, applying software design procedures, and finding errors with testing techniques. The syllabus covers topics like software processes, requirements analysis, object-oriented concepts, software design, and testing and management over 5 units. Recommended textbooks and online references are also provided.
Module 2_ Divide and Conquer Approach.pptxnikshaikh786
The document describes the divide and conquer approach and analyzes the complexity of several divide and conquer algorithms, including binary search, merge sort, quicksort, and finding minimum and maximum values. It explains the general divide and conquer method involves three steps: 1) divide the problem into subproblems, 2) solve the subproblems, and 3) combine the solutions to solve the original problem. It then provides detailed explanations and complexity analyses of specific divide and conquer algorithms.
The document provides an introduction to analyzing the performance of algorithms. It discusses time complexity and space complexity, which measure the running time and memory usage of algorithms. Common asymptotic notations like Big-O, Big-Omega, and Big-Theta are introduced to concisely represent the growth rates of algorithms. Specific algorithms like selection sort and insertion sort are analyzed using these metrics. Recursion and recurrence relations are also covered as methods to analyze algorithm efficiency.
Module 1_ Introduction to Mobile Computing.pptxnikshaikh786
Module 1 provides an introduction to mobile computing. The key concepts covered include mobile communication, mobile hardware, and mobile software. Mobile communication allows devices to communicate wirelessly and consists of infrastructure like protocols and services. Mobile hardware includes devices like smartphones and laptops that can access wireless networks. Mobile software provides the operating systems that allow mobile devices to operate portably and wirelessly. The module also discusses the electromagnetic spectrum, signal propagation effects, digital modulation techniques, and multiplexing methods like frequency division multiplexing and time division multiplexing.
This document provides an overview of module 2 which focuses on GSM mobile services and cellular architecture. It discusses the basic concepts and principles of computing and cellular infrastructure including system architecture, radio interface, protocols, localization, calling, handover and security. It provides details on the GSM system infrastructure, components, protocols and interfaces. It also discusses GPRS system and protocol architecture, UTRAN, UMTS core network and improvements to the core network.
Clustering is an unsupervised learning technique used to group unlabeled data points into clusters based on similarity. It is widely used in data mining applications. The k-means algorithm is one of the simplest clustering algorithms that partitions data into k predefined clusters, where each data point belongs to the cluster with the nearest mean. It works by assigning data points to their closest cluster centroid and recalculating the centroids until clusters stabilize. The k-medoids algorithm is similar but uses actual data points as centroids instead of means, making it more robust to outliers.
MODULE 5 _ Mining frequent patterns and associations.pptxnikshaikh786
1. The FP-Growth algorithm constructs an FP-tree to store transaction data, with frequent items listed in descending order of frequency.
2. It then uses a divide-and-conquer strategy to mine the conditional pattern base of each frequent item prefix, extracting combinations of frequent items.
3. This recursively mines the frequent patterns from the conditional FP-tree for each prefix path, without generating a large number of candidate itemsets.
This document discusses web mining and divides it into three categories: web content mining, web structure mining, and web usage mining. Web content mining examines the actual content of web pages and can utilize techniques like keyword searching, classification, clustering, and natural language processing. Web structure mining analyzes the hyperlink structure between pages. Web usage mining examines log files that record how users interact with and move between websites. The document provides examples of how these different types of web mining can be applied, such as for targeted advertising.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
This document discusses various classification and regression techniques for data mining, including decision trees, naive Bayesian classification, and linear regression. It covers evaluating classifier performance using measures like accuracy, precision, recall, and the confusion matrix. Cross-validation and bootstrap techniques for evaluating accuracy are introduced, along with the ROC curve and area under the curve for comprehensive evaluation. Holdout method and random subsampling for accuracy estimation are also summarized.
Module 2_ Introduction to Data Mining, Data Exploration and Data Pre-processi...nikshaikh786
The document discusses data mining architecture, tasks, and data exploration and preprocessing techniques. It describes the KDD process and issues in data mining. It also covers data types, attributes, statistical descriptions of data, and various data visualization techniques like histograms, boxplots, scatter plots and quantile plots to explore patterns in data. Data preprocessing steps discussed are data cleaning, integration, transformation, reduction and discretization.
The document provides information about data warehousing fundamentals. It discusses key concepts such as data warehouse architectures, dimensional modeling, fact and dimension tables, and metadata. The three common data warehouse architectures described are the basic architecture, architecture with a staging area, and architecture with staging area and data marts. Dimensional modeling is optimized for data retrieval and uses facts, dimensions, and attributes. Metadata provides information about the data in the warehouse.
This document discusses various cybercrimes and security issues related to mobile and wireless devices. It describes how criminals plan cyber attacks using techniques like social engineering, malware distribution, and exploiting vulnerabilities. Specific cybercrimes addressed include phishing, cyber stalking, crimes at cyber cafes, and the use of botnets. The document also covers attack vectors, the proliferation of mobile devices, and security challenges they pose like data leakage and malware. Recommendations are provided for protecting devices and networks from these threats.
Module 1- Introduction to Cybercrime.pptxnikshaikh786
Cybercrime involves illegal activities carried out using digital technology, often with criminal intent. Information security focuses on protecting systems and data from cyber threats. The Indian IT Act defines cybercrimes like hacking, data theft, and cyberbullying and prescribes penalties. It has undergone amendments to address new technologies. Other countries also have their own laws regulating electronic transactions, data protection, and cybersecurity.
The document discusses exploratory data analysis using R. It describes useful R functions for exploring and summarizing data frames, including dim(), nrow(), ncol(), head(), tail(), names(), str(), levels(), summary(), and fivenum(). These functions are demonstrated on the built-in InsectSprays data set to explore the categorical and continuous variables. The document also discusses measures of central tendency, dispersion, quantiles, and the three basic indexing operators in R.
This document provides an overview of text analysis and mining. It discusses key concepts like text pre-processing, representation, shallow parsing, stop words, stemming and lemmatization. Specific techniques covered include tokenization, part-of-speech tagging, Porter stemming algorithm. Applications mentioned are sentiment analysis, document similarity, cluster analysis. The document also provides a multi-step example of text analysis involving collecting raw text, representing text, computing TF-IDF, categorizing documents by topics, determining sentiments and gaining insights.
This document provides an overview of time series analysis and the Box-Jenkins methodology. Time series analysis attempts to model observations over time and identify patterns. The goals are to identify the structure of the time series and forecast future values. The Box-Jenkins methodology involves conditioning the data, selecting a model, estimating parameters, and assessing the model. Autocorrelation (ACF) and partial autocorrelation (PACF) plots are used to identify autoregressive (AR), moving average (MA), and autoregressive integrated moving average (ARIMA) models.
This document provides an overview of regression models and analysis techniques. It introduces simple and multiple linear regression, as well as logistic regression. It discusses assessing regression models, cross-validation, model selection, and using regression models for prediction. Additionally, it covers the similarities and differences between linear and logistic regression, and assessing correlation without inferring causation. Scatter plots, correlation coefficients, and computing regression equations are also summarized.
MODULE 1_Introduction to Data analytics and life cycle..pptxnikshaikh786
The document provides an overview of the data analytics lifecycle and its key phases. It discusses the 6 phases: discovery, data preparation, model planning, model building, communicating results, and operationalizing. For each phase, it describes the main activities and considerations. It also discusses roles, tools, and best practices for ensuring a successful analytics project.
This document provides an overview of various data analytics tools and frameworks for IoT, including Apache Hadoop, Apache Spark, Apache Storm, and NETCONF-YANG. It discusses using Hadoop MapReduce for batch data analysis, Apache Oozie for workflow scheduling, Apache Spark for fast processing, and Apache Storm for real-time streaming data analysis. Tools for deploying IoT systems like Chef and Puppet are also mentioned. Case studies and structural health monitoring are provided as examples of applying these technologies.
This document contains questions about Flutter, Dart, Progressive Web Apps (PWA), Firebase, and data types in Dart. Some of the topics covered include:
1. What Flutter is and its advantages
2. The Flutter architecture and important features
3. Build modes, widgets, and their importance in Flutter
4. What Dart is and its importance
5. The difference between runApp() and main()
6. Packages, plugins, and editors used for Flutter development
7. How Firebase works and its features for building web and mobile applications.
Online train ticket booking system project.pdfKamal Acharya
Rail transport is one of the important modes of transport in India. Now a days we
see that there are railways that are present for the long as well as short distance
travelling which makes the life of the people easier. When compared to other
means of transport, a railway is the cheapest means of transport. The maintenance
of the railway database also plays a major role in the smooth running of this
system. The Online Train Ticket Management System will help in reserving the
tickets of the railways to travel from a particular source to the destination.
Covid Management System Project Report.pdfKamal Acharya
CoVID-19 sprang up in Wuhan China in November 2019 and was declared a pandemic by the in January 2020 World Health Organization (WHO). Like the Spanish flu of 1918 that claimed millions of lives, the COVID-19 has caused the demise of thousands with China, Italy, Spain, USA and India having the highest statistics on infection and mortality rates. Regardless of existing sophisticated technologies and medical science, the spread has continued to surge high. With this COVID-19 Management System, organizations can respond virtually to the COVID-19 pandemic and protect, educate and care for citizens in the community in a quick and effective manner. This comprehensive solution not only helps in containing the virus but also proactively empowers both citizens and care providers to minimize the spread of the virus through targeted strategies and education.
Data Communication and Computer Networks Management System Project Report.pdfKamal Acharya
Networking is a telecommunications network that allows computers to exchange data. In
computer networks, networked computing devices pass data to each other along data
connections. Data is transferred in the form of packets. The connections between nodes are
established using either cable media or wireless media.
This is an overview of my current metallic design and engineering knowledge base built up over my professional career and two MSc degrees : - MSc in Advanced Manufacturing Technology University of Portsmouth graduated 1st May 1998, and MSc in Aircraft Engineering Cranfield University graduated 8th June 2007.
Cricket management system ptoject report.pdfKamal Acharya
The aim of this project is to provide the complete information of the National and
International statistics. The information is available country wise and player wise. By
entering the data of eachmatch, we can get all type of reports instantly, which will be
useful to call back history of each player. Also the team performance in each match can
be obtained. We can get a report on number of matches, wins and lost.
2. Design Engineering
• It covers the set of principles, concepts, and practices that lead to
the development of a high quality system or product.
• Goal of design engineering is to produce a model or representation
that depict:
• Firmness – program should not have any bug that inhibits its functions.
• Commodity – suitable to its intended use.
• Delight - pleasurable to use
• The design model provides detail about software data structures,
architecture, interfaces, and components that are necessary to
implement the system.
5. • Data/class design - Created by transforming the analysis model class-
based elements into classes and data structures required to implement the
software
• Architectural design - defines the relationships among the major
structural elements of the software, it is derived from the class-based
elements and flow-oriented elements of the analysis model
• Interface design - describes how the software elements, hardware
elements, and end-users communicate with one another, it is derived
from the analysis model scenario-based elements, flow-oriented
elements, and behavioral elements
• Component-level design - created by transforming the structural
elements defined by the software architecture into a procedural
description of the software components using information obtained from
the analysis model class-based elements, flow-oriented elements, and
behavioral elements
6. Why design is so important?
• It is place where quality is fostered.
• It provides us with representation of software that can be
assessed for quality.
• Only way that can accurately translate a customer’s
requirements into a finished software product.
• It serves as foundation for all software engineering
activities.
• Without design difficult to assess:
• Risk
• Test
• Quality
7. Design Process and Design Quality
• S/w design is an iterative process through which
requirements are translated into a “blueprint” for
constructing the s/w.
• As design iteration occur, subsequent refinement
leads to design representation at much lower levels
of abstraction.
8. Goal of design process
• The design must implement all of the explicit
requirements contained in the analysis model, and it
must accommodate all of the implicit requirements
desired by the customer.
• The design must be a readable, understandable guide for
those who generate code and for those who test and
subsequently support the software.
• The design should provide a complete picture of the
software, addressing the data, functional, and behavioral
domains from an implementation perspective.
9. Quality Guidelines
Characteristics of good design
• A design should exhibit an architecture that
• as been created using recognizable architectural styles or patterns,
• is composed of components that exhibit good design characteristics
and
• can be implemented in an evolutionary fashion
• A design should be modular; that is, the software should be logically
partitioned into elements or subsystems
• A design should contain distinct representations of data, architecture,
interfaces, and components.
• A design should lead to data structures that are appropriate for the
classes to be implemented and are drawn from recognizable data
patterns.
• A design should lead to components that exhibit independent functional
characteristics
10. Quality Guidelines (contd.)
• A design should lead to interfaces that reduce the
complexity of connections between components and with
the external environment.
• A design should be derived using a repeatable method that
is driven by information obtained during software
requirements analysis.
• A design should be represented using a notation that
effectively communicates its meaning.
11. Design Principles
• S/W design is both a process and a model.
• Design process - sequence of steps that enable the
designer to describe all aspects of the software to
be built.
• Design model - created for software provides a
variety of different views of the computer software
12. Design Principles
• The design process should not suffer from ‘tunnel vision.’ -
Designer should consider alternative approaches.
• The design should be traceable to the analysis model - a single
element of the design model often traces to multiple
requirements, it is necessary to have a means for tracking how
requirements have been satisfied by the design model.
• The design should not reinvent the wheel- use already exists
design pattern because time is short and resource are limited.
• The design should “minimize the intellectual distance” between
the software and the problem as it exists in the real world. –
design should be self-explanatory
13. Design Principles
• The design should exhibit uniformity and integration – before
design work begins rules of styles and format should be defined
for a design team.
• The design should be structured to accommodate change
• The design should be structured to degrade gently, even when
unusual data, events, or operating conditions are encountered.
• Design is not coding, coding is not design.
• The design should be assessed for quality as it is being created,
not after the fact
• The design should be reviewed to minimize conceptual (semantic)
errors.
14. Design concepts
• Design concepts provide the necessary framework for “to get the thing on
right way”.
• Abstraction
• Refinement
• Modularity
• Architecture
• Control Hierarchy
• Structural Partitioning
• Data Structure
• Software Procedure
• Information Hiding
15. Abstraction
• At the highest level of abstraction – a solution is stated in broad terms
• At lower level of abstraction – a more detailed description of the solution is
provided.
• Two types of abstraction:
• Procedural abstraction: Sequence of instructions that have a specific and
limited function.
Ex. Open a door
open implies long sequence of activities (e.g. walk to the door, grasp knob,
turn knob and pull the door, etc).
• Data abstraction: collection of data that describes a data object.
Ex. Open a door. – door is data object.
• Data abstraction for door would encompass a set of attributes that describe
the door. (E.g. door type, swing direction, opening mechanism, etc.)
16. Refinement
• Refinement is actually a process of elaboration.
• begin with a statement of function (or description of information)
that is defined at a high level of abstraction.
• That is, the statement describes function or information
conceptually but provides no information about the internal
workings of the function or the internal structure of the information.
• Refinement causes the designer to elaborate on the original
statement, providing more and more detail as each successive
refinement (elaboration) occurs.
• Abstraction and refinement are complementary concepts.
Abstraction enables a designer to specify procedure and data and
yet suppress low-level details.
• Refinement helps the designer to expose low-level details as design
progresses.
17. Modularity
• Architecture and design pattern embody modularity.
• Software is divided into separately named and addressable
components, sometimes called modules, which are
integrated to satisfy problem requirement.
• modularity is the single attribute of software that allows a
program to be intellectually manageable
• It leads to a “divide and conquer” strategy. – it is easier to
solve a complex problem when you break into a
manageable pieces.
• Refer fig. that state that effort (cost) to develop an
individual software module does decrease if total number of
modules increase.
• However as the no. of modules grows, the effort (cost)
associated with integrating the modules also grows.
19. Modularity and software cost
• Undermodularity and overmodularity should be
avoided. But how do we know the vicinity of M?
• We modularize a design so that development can be
more easily planned.
• Software increments can be defined and delivered.
• Changes can be more easily accommodated.
• Testing and debugging can be conducted more
efficiently and long-term maintained can be conducted
without serious side effects.
20. Architecture
• Software architecture suggest “ the overall structure of the
software and the ways in which that structure provides
conceptual integrity for a system.
• No. of different models can use to represent architecture.
• Structural Model- represent architecture as an organized
collection of components
• Framework model – Increase level of design abstraction by
identifying repeatable architectural design framework.
• Dynamic model – address behavior of the program
architecture and indicating how system or structure
configuration may change as a function.
• Process Model – focus on design of the business or technical
process that the system must accommodate.
• Functional models – used to represent the functional
hierarchy of a system.
21. Control Hierarchy
• Control hierarchy, represents the organization of
program components (modules) and implies a
hierarchy of control.
• Different notations are used to represent control
hierarchy for those architectural styles that are
amenable to this representation.
• The most common is the treelike diagram that
represents hierarchical control for call and return
architectures.
23. Control Hierarchy
• In fig. depth and width provide an indication of the number
of levels of control and overall span of control.
• Fan-out is a measure of the number of modules that are
directly controlled by another module. Fan-in indicates how
many modules directly control a given module.
• A module that controls another module is said to be
superordinate to it, and conversely, a module controlled by
another is said to be subordinate to the controller.
Ex. Module M is superordinate to modules a, b, and c.
Module h is subordinate to module e
25. Structure partitioning
• Two types of Structure partitioning:
• Horizontal Partitioning
• Vertical Partitioning
• Horizontal partitioning defines separate branches of the
modular hierarchy for each major program function.
• Control modules, represented in a darker shade are used to
coordinate communication & execution between its functions.
• Horizontal partitioning defines three partitions—input, data
transformation (often called processing) and output.
• Benefits of Horizontal partitioning:
• software that is easier to test
• software that is easier to maintain
• propagation of fewer side effects
• software that is easier to extend
26. Structure partitioning
• On the negative side (Drawback), horizontal partitioning
often causes more data to be passed across module
interfaces and can complicate the overall control of
program flow.
• Vertical partitioning, often called factoring, suggests
that control (decision making) and work should be
distributed top-down in the program structure.
• Top-level modules should perform control functions and
do little actual processing work.
• Modules that reside low in the structure should be the
workers, performing all input, computation, and output
tasks.
27. Structure partitioning
• A change in a control module (high in the structure)
will have a higher probability of propagating side
effects to modules that are subordinate to it.
• A change to a worker module, given its low level in
the structure, is less likely to cause the propagation of
side effects.
• For this reason vertically partitioned structures are
less likely to be susceptible to side effects when
changes are made and will therefore be more
maintainable.
28. Data Structure
• Data structure is a representation of the logical relationship among
individual elements of data
• A scalar item is the simplest of all data structures. It represents a single
element of information that may be addressed by an identifier.
• When scalar items are organized as a list or contiguous group, a
sequential vector is formed.
• When the sequential vector is extended to two, three, and ultimately,
an arbitrary number of dimensions, an n-dimensional space is created.
Most common n-dimensional space is the two-dimensional matrix
• A linked list is a data structure that organizes contiguous scalar items,
vectors, or spaces in a manner (called nodes) that enables them to be
processed as a list.
• A hierarchical data structure is implemented using multilinked lists that
contain scalar items, vectors, and possibly, n-dimensional spaces.
29. Software Procedure
• Software procedure focuses on the processing
details of each module individually.
• Procedure must provide a precise specification of
processing, including sequence of events, exact
decision points, repetitive operations, and even
data organization and structure.
30. Information Hiding
• The principle of information hiding suggests that modules
be "characterized by design decisions that (each) hides from
all others modules.“
• In other words, modules should be specified and designed
so that information (algorithm and data) contained within a
module is inaccessible to other modules that have no need
for such information.
• The intent of information hiding is to hide the details of data
structure and procedural processing behind a module
interface.
• It gives benefits when modifications are required during
testing and maintenance because data and procedure are
hiding from other parts of software, unintentional errors
introduced during modification are less.
31. EFFECTIVE MODULAR DESIGN
• Effective modular design consist of three things:
• Functional Independence
• Cohesion
• Coupling
32. Functional Independence
• Functional independence is achieved by developing
modules with "single-minded“ function and an "aversion" to
excessive interaction with other modules.
• In other words - each module addresses a specific sub-
function of requirements and has a simple interface when
viewed from other parts of the program structure.
• Independence is important –
• Easier to develop
• Easier to Test and maintain
• Error propagation is reduced
• Reusable module.
33. Functional Independence
• To summarize, functional independence is a key to
good design, and design is the key to software
quality.
• To measure independence, have two qualitative
criteria: cohesion and coupling
• Cohesion is a measure of the relative functional
strength of a module.
• Coupling is a measure of the relative
interdependence among modules.
34. Cohesion
• Cohesion is a natural extension of the information hiding concept
• A cohesive module performs a single task within a software
procedure, requiring little interaction with procedures being
performed in other parts of a program
• Simply state, a cohesive module should (ideally) do just one thing.
• We always strive for high cohesion, although the mid-range of the
spectrum is often acceptable.
• Low-end cohesiveness is much "worse" than middle range, which is
nearly as "good" as high-end cohesion.
• So. designer should avoid low levels of cohesion when modules are
designed.
35. Cohesion
• When processing elements of a module are related
and must be executed in a specific order,
procedural cohesion exists.
• When all processing elements concentrate on one
area of a data structure, communicational cohesion
is present.
• High cohesion is characterized by a module that
performs one distinct procedural task.
36. Types of cohesion
• A module that performs tasks that are related
logically is logically cohesive.
• When a module contains tasks that are related by
the fact that all must be executed with the same
span of time, the module exhibits temporal
cohesion.
• At the low-end of the spectrum, a module that
performs a set of tasks that relate to each other
loosely, called coincidentally cohesive.
37. Coupling
• Coupling depends on the interface complexity between
modules, the point at which entry or reference is made to a
module, and what data pass across the interface
• In software design, we strive for lowest possible coupling.
Simple connectivity among modules results in software that
is easier to understand and less prone to a "ripple effect"
caused when errors occur at one location and propagate
through a system.
• It occur because of design decisions made when structure
was developed.
39. Coupling
• Coupling is characterized by passage of control between
modules.
• “Control flag” (a variable that controls decisions in a
subordinate or superordinate module) is passed between
modules d and e (called control coupling).
• Relatively high levels of coupling occur when modules are
communicate with external to software.
• External coupling is essential, but should be limited to a
small number of modules with a structure.
40. • High coupling also occurs when a number of modules
reference a global data area.
• Common coupling, no. of modules access a data item in a
global data area
• So it does not mean “use of global data is bad”. It does
mean that a software designer must be take care of this
thing.
41. Evolution of Software Design
• Early design work concentrated on criteria for the
development of modular programs and methods for refining
software structures in a top-down manner.
• Later work proposed methods for the translation of data
flow or data structure into a design definition.
• Today, the emphasis in software design has been on
software architecture and the design patterns that can be
used to implement software architectures.
42. Characteristics are common to all design
methods
• A mechanism for the translation of analysis model
into a design representation,
• A notation for representing functional components
and their interfaces.
• Heuristics for refinement and partitioning
• Guidelines for quality assessment.
44. • Functionality – is assessed by evaluating the feature set and
capabilities of the program.
• Functions that are delivered and security of the overall
system.
• Usability – assessed by considering human factors, consistency
& documentation.
• Reliability – evaluated by
• measuring the frequency and severity of failure.
• Accuracy of output results.
• Ability to recover from failure and predictability of the
program.
• Performance - measured by processing speed, response time,
resource consumption, efficiency.
• Supportability – combines the ability to extend the program
(extensibility), adaptability and serviceability.
Editor's Notes
As an example of low cohesion, consider a module that performs error processing for an engineering analysis package. The module is called when computed data exceed prespecified bounds. It performs the following tasks: (1) computes supplementary data based on original computed data, (2) produces an error report (with graphical content) on the user's workstation, (3) performs follow-up calculations requested by the user, (4) updates a database, and (5) enables menu selection for subsequent processing. Although the preceding tasks are loosely related, each is an independent functional entity that might best be performed as a separate module. Combining the functions into a single module can serve only to increase the likelihood of error propagation when a modification is made to one of its processing tasks.
Modules a and d are subordinate to different modules. Each is unrelated and therefore no direct coupling occurs. Module c is subordinate to module a and is accessed via a conventional argument list, through which data are passed. As long as a simple argument list is present (i.e., simple data are passed; a one-to-one correspondence of items exists), low coupling (called data coupling) is exhibited in this portion of structure. A
variation of data coupling, called stamp coupling, is found when a portion of a data structure (rather than simple arguments) is passed via a module interface. This occurs between modules b and a.
Common coupling --Module c initializes the item. Later module g recomputed and updates the item. Let's assume that an error
occurs and g updates the item incorrectly. Much later in processing module, k reads the item, attempts to process it, and fails, causing the software to abort. The apparent cause of abort is module k; the actual cause, module g. Diagnosing problems in structures with considerable common coupling is time consuming and difficult.