Software Architecture and Design for Reliability Predictability

Software Architecture and Design for Reliability Predictability

Author: Assefa D. Semegn

Publisher: Cambridge Scholars Publishing

Published: 2011-09-22

Total Pages: 410

ISBN-13: 1443834157

DOWNLOAD EBOOK

Reliability prediction of a software product is complex due to interdependence and interactions among components and the difficulty of representing this behavior with tractable models. Models developed by making simplifying assumptions about the software structure may be easy to use, but their result may be far from what happens in reality. Making assumptions closer to the reality, which allows complex interactions and interdependences among components, results in models that are too complex to use. Their results may also be too difficult to interpret. The reliability prediction problem is worsened by the lack of precise information on the behavior of components and their interactions, information that is relevant for reliability modeling. Usually, the interactions are not known precisely because of subtle undocumented side effects. Without accurate precise information, even mathematically correct models will not yield accurate reliability predictions. Deriving the necessary information from program code is not practical if not impossible. This is because the code contains too much implementation detail to be useful in creating a tractable model. It is also difficult to analyze system reliability completely based on the program code. This book documents the resulting novel approach of designing, specifying, and describing the behavior of software systems in a way that helps to predict their reliability from the reliability of the components and their interactions. The design approach is named design for reliability predictability (DRP). It integrates design for change, precise behavioral documentation and structure based reliability prediction to achieve improved reliability prediction of software systems. The specification and documentation approach builds upon precise behavioral specification of interfaces using the trace function method (TFM). It also introduces a number of structure functions or connection documents. These functions capture both the static and dynamic behaviors of component based software systems. They are used as a basis for a novel document driven structure based reliability prediction model. System reliability assessment is studied in at least three levels: component reliability, which is assumed to be known; interaction reliability, a novel approach to studying software reliability; and service reliability, whose estimation is the primary objective of reliability assessment. System reliability can be expressed as a function of service reliability. A mobile streaming system, designed and developed by the author as an industrial product, is used as a case study to demonstrate the application of the approach.


Integrated Software Architecture-Based Reliability Prediction for IT Systems

Integrated Software Architecture-Based Reliability Prediction for IT Systems

Author: Franz Brosch

Publisher: KIT Scientific Publishing

Published: 2014-07-29

Total Pages: 368

ISBN-13: 3866448597

DOWNLOAD EBOOK

With the increasing importance of reliability in business and industrial IT systems, new techniques for architecture-based software reliability prediction are becoming an integral part of the development process. This dissertation thesis introduces a novel reliability modelling and prediction technique that considers the software architecture with its component structure, control and data flow, recovery mechanisms, its deployment to distributed hardware resources and the system�s usage profile.


Artificial Neural Network Applications for Software Reliability Prediction

Artificial Neural Network Applications for Software Reliability Prediction

Author: Manjubala Bisi

Publisher: John Wiley & Sons

Published: 2017-09-18

Total Pages: 225

ISBN-13: 111922392X

DOWNLOAD EBOOK

This book provides a starting point for software professionals to apply artificial neural networks for software reliability prediction without having analyst capability and expertise in various ANN architectures and their optimization. Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process are presented. Applications of artificial neural network for the above purposes are discussed with experimental results in this book so that practitioners can easily use ANN models for predicting software reliability indicators.


Design of Biomedical Devices and Systems Second edition

Design of Biomedical Devices and Systems Second edition

Author: Paul H. King

Publisher: CRC Press

Published: 2008-08-22

Total Pages: 424

ISBN-13: 1439878072

DOWNLOAD EBOOK

The design and functional complexity of medical devices and systems has increased during the past half century, evolving from the level of cardiac pacemakers to magnetic resonance imaging devices. Such life-saving advancements are monumentally advantageous, but with so much at stake, a step-by-step manual for biomedical engineers is essential. This


Industry 4.0

Industry 4.0

Author: Aydin Azizi

Publisher: Springer Nature

Published: 2022-12-07

Total Pages: 268

ISBN-13: 9811920125

DOWNLOAD EBOOK

This book presents Industry 4.0 enabler technologies and tools. It also highlights some of the existing empirical applications in the context of manufacturing. The book elucidates innovative thematic concepts of Industry 4.0 and its perspectives. It establishes routes to empirically utilize Industry 4.0 standards for manufacturing companies. The book can be used as a reference for professionals/engineers, researchers, and students.


Reliability Growth

Reliability Growth

Author: Panel on Reliability Growth Methods for Defense Systems

Publisher: National Academy Press

Published: 2015-03-01

Total Pages: 235

ISBN-13: 9780309314749

DOWNLOAD EBOOK

A high percentage of defense systems fail to meet their reliability requirements. This is a serious problem for the U.S. Department of Defense (DOD), as well as the nation. Those systems are not only less likely to successfully carry out their intended missions, but they also could endanger the lives of the operators. Furthermore, reliability failures discovered after deployment can result in costly and strategic delays and the need for expensive redesign, which often limits the tactical situations in which the system can be used. Finally, systems that fail to meet their reliability requirements are much more likely to need additional scheduled and unscheduled maintenance and to need more spare parts and possibly replacement systems, all of which can substantially increase the life-cycle costs of a system. Beginning in 2008, DOD undertook a concerted effort to raise the priority of reliability through greater use of design for reliability techniques, reliability growth testing, and formal reliability growth modeling, by both the contractors and DOD units. To this end, handbooks, guidances, and formal memoranda were revised or newly issued to reduce the frequency of reliability deficiencies for defense systems in operational testing and the effects of those deficiencies. "Reliability Growth" evaluates these recent changes and, more generally, assesses how current DOD principles and practices could be modified to increase the likelihood that defense systems will satisfy their reliability requirements. This report examines changes to the reliability requirements for proposed systems; defines modern design and testing for reliability; discusses the contractor's role in reliability testing; and summarizes the current state of formal reliability growth modeling. The recommendations of "Reliability Growth" will improve the reliability of defense systems and protect the health of the valuable personnel who operate them.


Modern Software Engineering Concepts and Practices: Advanced Approaches

Modern Software Engineering Concepts and Practices: Advanced Approaches

Author: Dogru, Ali H.

Publisher: IGI Global

Published: 2010-12-31

Total Pages: 505

ISBN-13: 160960217X

DOWNLOAD EBOOK

Software engineering has advanced rapidly in recent years in parallel with the complexity and scale of software systems. New requirements in software systems yield innovative approaches that are developed either through introducing new paradigms or extending the capabilities of well-established approaches. Modern Software Engineering Concepts and Practices: Advanced Approaches provides emerging theoretical approaches and their practices. This book includes case studies and real-world practices and presents a range of advanced approaches to reflect various perspectives in the discipline.


New Trends in Software Methodologies, Tools and Techniques

New Trends in Software Methodologies, Tools and Techniques

Author: H. Fujita

Publisher: IOS Press

Published: 2016-08-30

Total Pages: 388

ISBN-13: 1614996741

DOWNLOAD EBOOK

Software has become an essential enabler for science and the economy. Not only does it create new markets and the possibility of a more reliable, flexible and robust society, it also empowers our exploration of the world in ever increasing depth. However software often falls short of our expectations, with current methodologies, tools and techniques remaining insufficiently robust and reliable for constantly changing and evolving needs. This book presents papers from the 15th International Conference on New Trends in Intelligent Software Methodology Tools and Techniques (SoMeT 16), held in Larnaca, Cyprus, in September 2016. The SoMeT conference focuses on exploring the innovations, controversies and challenges facing the software engineering community, bringing together theory and experience to propose and evaluate solutions to software engineering problems with an emphasis on human-centric software methodologies, end-user development techniques, and emotional reasoning, for an optimally harmonized performance between the design tool and the user. The book is divided into six chapters covering the following areas: decision support systems; software methodologies and tools; requirement engineering; software for biomedicine and bioinformatics; software engineering models, and formal techniques for software representation; and intelligent software development and social networking. The book explores new trends and theories which illuminate the direction of developments in the field, and will be of interest to all in the software science community.


ARTIFICIAL INTELLIGENCE

ARTIFICIAL INTELLIGENCE

Author: Chandra S.S., Vinod

Publisher: PHI Learning Pvt. Ltd.

Published: 2020-10-01

Total Pages: 428

ISBN-13: 938934784X

DOWNLOAD EBOOK

Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this textbook (earlier titled as Artificial Intelligence and Machine Learning), now in its second edition, bridges the gaps in knowledge of the seemingly difficult areas of artificial intelligence. This book promises to provide the most number of case studies and worked-out examples among the books of its genre. The text is written in a highly interactive manner which fulfils the curiosity of any reader. Moreover, the content takes off from the introduction to artificial intelligence, which is followed by explaining about intelligent agents. Various problem-solving strategies, knowledge representation schemes are also included with numerous case studies and applications. Different aspects of learning, nature-inspired learning, along with natural language processing are also explained in depth. The algorithms and pseudo codes for each topic make this book useful for students. Book also throws light into areas like planning, expert system and robotics. Book concludes with futuristic artificial intelligence, which explains the fascinating applications, that the world will witness in coming years. KEY FEATURES • Day-to-day examples and practical representations for deeper understanding of the subject. • Learners can easily implement the AI applications. • Effective and useful case studies and worked-out examples for AI problems. Target Audience • Students of B.E./B.Tech Computer Science Engineering • Students of M.E./M.Tech Computer Science Engineering


MACHINE LEARNING

MACHINE LEARNING

Author: Chandra S.S., Vinod

Publisher: PHI Learning Pvt. Ltd.

Published: 2021-01-01

Total Pages: 600

ISBN-13: 9389347475

DOWNLOAD EBOOK

The present book is primarily intended for undergraduate and postgraduate students of computer science and engineering, information technology, and electrical and electronics engineering. It bridges the gaps in knowledge of the seemingly difficult areas of machine learning and nature inspired computing. The text is written in a highly interactive manner, which satisfies the learning curiosity of any reader. Content of the text has been diligently organized to offer seamless learning experience. The text begins with introduction to machine learning, which is followed by explanation of different aspects of machine learning. Various supervised, unsupervised, reinforced and nature inspired learning techniques are included in the text book with numerous examples and case studies. Different aspects of new machine learning and nature inspired learning algorithms are explained in-depth. The well-explained algorithms and pseudo codes for each topic make this book useful for students. The book also throws light on areas like prediction and classification systems. Key Features • Day to day examples and pictorial representations for deeper understanding of the subject • Helps readers easily create programs/applications • Research oriented approach • More case studies and worked-out examples for each machine learning algorithm than any other book