Download or read book Artificial Neural Network Applications for Software Reliability Prediction written by Manjubala Bisi and published by John Wiley & Sons. This book was released on 2017-09-21 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Prediction of software reliability using neural networks written by N. Karunanithi and published by . This book was released on 1990 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Prediction of Software Reliability Using Neural Network and Fuzzy Logic written by Sultan Hamadi Aljahdali and published by . This book was released on 2003 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Software Reliability Assessment with OR Applications written by P.K. Kapur and published by Springer Science & Business Media. This book was released on 2013-05-09 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Reliability Assessment with OR Applications is a comprehensive guide to software reliability measurement, prediction, and control. It provides a thorough understanding of the field and gives solutions to the decision-making problems that concern software developers, engineers, practitioners, scientists, and researchers. Using operations research techniques, readers will learn how to solve problems under constraints such as cost, budget and schedules to achieve the highest possible quality level. Software Reliability Assessment with OR Applications is a comprehensive text on software engineering and applied statistics, state-of-the art software reliability modeling, techniques and methods for reliability assessment, and related optimization problems. It addresses various topics, including: unification methodologies in software reliability assessment; application of neural networks to software reliability assessment; software reliability growth modeling using stochastic differential equations; software release time and resource allocation problems; and optimum component selection and reliability analysis for fault tolerant systems. Software Reliability Assessment with OR Applications is designed to cater to the needs of software engineering practitioners, developers, security or risk managers, and statisticians. It can also be used as a textbook for advanced undergraduate or postgraduate courses in software reliability, industrial engineering, and operations research and management.
Download or read book Evidence Based Decision Making Using Neural Networks for Software App written by Kuppusamy Karnavel and published by LAP Lambert Academic Publishing. This book was released on 2016-01-04 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence Based Decision Making using Neural Networks for Software Applications The Bayesian Networks use Conditional Probability Tables for predicting the Cause and Effect Relationship. Bayesian Networks can be replaced by Neural networks which improves the effectiveness of expert knowledge by analysing the data sets. Neural Networks are created by connecting processing elements. Neural Networks replaces the Bayesian Networks because of its ability to solve a problem in software without defining and describing the method of solving such problems and even without any case of personal knowledge about the solved problems. This study focuses on predicting the reliability of any software project depending upon their project characteristics using Neural Networks.
Download or read book Developing Assessment Models for Software Reliability at Late Design Phase written by Bhagyashri Deshpande and published by GRIN Verlag. This book was released on 2022-06-03 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doctoral Thesis / Dissertation from the year 2021 in the subject Computer Science - Software, Savitribai Phule Pune University, formerly University of Pune (Department of Computer Science), course: Ph.D, language: English, abstract: In this thesis report the pertinence of the models (Neural Network model and Hellinger Net model) for better software reliability prediction considering the parameters and software metrics affecting the software design in a real environment is described. And a method of software defect detection and software reliability assessment using NN model and Intelligent Water Drop (IWD) Technique is presented. Built on a Neural Network (NN), two models are developed which predicts the software reliability in a more accurate manner. There are two kinds of hybrid models developed. One uses IWD with NN and another is IWD with Spiking Neural Network (SNN). For both, the modelling feature selection technique and learning algorithm is implemented and the data representation methods and some metrics associated with software reliability models are discussed. Various datasets containing metrics values with software failures are applied to the proposed models. These datasets are acquired from variety of software projects.
Download or read book Artificial Neural Network Applications for Software Reliability Prediction written by Manjubala Bisi and published by John Wiley & Sons. This book was released on 2017-09-18 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Software Reliability Growth Models written by David D. Hanagal and published by Springer Nature. This book was released on 2021-02-26 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basic concepts of software reliability growth models (SRGMs), ranging from fundamental to advanced level. It discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability engineering. These models consider the debugging process as a counting process characterized by its mean value function. Model parameters have been estimated by using either the maximum likelihood method or regression. NHPP SRGMs based on inverse Weibull, generalized inverse Weibull, extended inverse Weibull, generalized extended inverse Weibull, and delayed S-shaped have been focused upon. Review of literature on SRGM has been included from the scratch to recent developments, applicable in artificial neural networks, machine learning, artificial intelligence, data-driven approaches, fault-detection, fault-correction processes, and also in random environmental conditions. This book is designed for practitioners and researchers at all levels of competency, and also targets groups who need information on software reliability engineering.
Download or read book Software Reliability Modelling and Identification written by Sergio Bittanti and published by Springer Science & Business Media. This book was released on 1988-12-21 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains five tutorial papers based on the lectures given at the intensive course on Software Reliability Modelling and Identification in Como (Italy) from September 2 to 4, 1987. The purpose of this volume is to present some important models used to forecast the reliability growth during the software testing process, and discuss the practical applicability of models in the management of software techniques for model identification from data (parameter estimation, complexity selection, validation, etc.). The basic reliability concepts are also introduced for those readers who are not familiar with the reliability ideas. Besides the basic models, a new family of models is introduced in the book. This family is flexible enough to describe a variety of different reliability trends. Particular attention is given to the problem of the provision of tools to assist the user in selecting an appropriate model in a particular situation.
Download or read book Multi Criteria Decision Models in Software Reliability written by Ashish Mishra and published by CRC Press. This book was released on 2022-11-30 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into contemporary issues and challenges in multi-criteria decision models. It is a useful guide for identifying, understanding and categorising multi-criteria decision models, and ultimately implementing the analysis for effective decision-making. The use of multi-criteria decision models in software reliability engineering is a relatively new field of study, and this book collects all the latest methodologies, tools and techniques in one single volume. It covers model selection, assessment, resource allocation, release management, up-grade planning, open-source systems, bug tracking system management and defect prediction. Multi-Criteria Decision Models in Software Reliability: Methods and Applications will cater to researchers, academicians, post-graduate students, software developers, software reliability engineers and IT managers.
Download or read book Computational Intelligence in Software Engineering written by Witold Pedrycz and published by World Scientific. This book was released on 1998 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume is the first publication on software engineering and computational intelligence (CI) viewed as a synergistic interplay of neurocomputing, granular computation (including fuzzy sets and rough sets), and evolutionary methods. It presents a unified view of CI in the context of software engineering. The book addresses a number of crucial issues: what is CI, what role does it play in software development, how are CI elements built into successive phases of the software life cycle, and what is the role played by CI in quantifying fundamental features of software artifacts? With contributions from leading researchers and practitioners, the book provides the reader with a wealth of new concepts and approaches, complete algorithms, in-depth case studies, and thought-provoking exercises. The topics coverage include neurocomputing, granular as well as evolutionary computing, object-oriented analysis and design in software engineering. There is also an extensive bibliography.
Download or read book System Reliability and Security written by Javaid Iqbal and published by CRC Press. This book was released on 2023-12-07 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the growing reliance on software, concerns are growing as to how reliable a system is before it is commissioned for use, how high the level of reliability is in the system, and how many vulnerabilities exist in the system before its operationalization. Equally pressing issues include how to secure the system from internal and external security threats that may exist in the face of resident vulnerabilities. These two problems are considered increasingly important because they necessitate the development of tools and techniques capable of analyzing dependability and security aspects of a system. These concerns become more pronounced in the cases of safety-critical and mission-critical systems. System Reliability and Security: Techniques and Methodologies focuses on the use of soft computing techniques and analytical techniques in the modeling and analysis of dependable and secure systems. It examines systems and applications having complex distributed or networked architectures in such fields as: Nuclear energy Ground transportation systems Air traffic control Healthcare and medicine Communications System reliability engineering is a multidisciplinary field that uses computational methods for estimating or predicting the reliability aspects of a system and analyzing failure data obtained from real-world projects. System security is a related field that ensures that even a reliable system is secure against accidental or deliberate intrusions and is free of vulnerabilities. This book covers tools and techniques, cutting-edge research topics, and methodologies in the areas of system reliability and security. It examines prediction models and methods as well as how to secure a system as it is being developed.
Download or read book Rough Sets Fuzzy Sets Data Mining and Granular Computing written by Hiroshi Sakai and published by Springer. This book was released on 2009-12-15 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2009, held in Delhi, India in December 2009 in conjunction with the Third International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009. RSFDGrC 2009 is the core component of a broader Rough Set Year in India initiative, RSIndia09. The 56 revised full papers presented together with 6 invited papers and a report on the Rough Set Year in India 2009 project were carefully reviewed and selected from a total of 130 submissions. The papers are organized in topical sections on foundations of rough sets and beyond; rought set algorithms and applications; fuzzy set foundations and applications; data mining and knowledge discovery; clustering and current trends in computing; and information retrieval and text mining.
Download or read book Meta Heuristic Techniques in Software Engineering and Its Applications written by Mihir Narayan Mohanty and published by Springer Nature. This book was released on 2022-10-17 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.
Download or read book Data Management Analytics and Innovation written by Valentina Emilia Balas and published by Springer. This book was released on 2018-08-09 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the latest, high-quality, technical contributions and research findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It discusses state-of-the-art topics as well as the challenges and solutions for future development. It includes original and previously unpublished international research work highlighting research domains from different perspectives. This book is mainly intended for researchers and practitioners in academia and industry.
Download or read book Handbook of Research on Machine Learning Innovations and Trends written by Hassanien, Aboul Ella and published by IGI Global. This book was released on 2017-04-03 with total page 1269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.
Download or read book Cognitive Analytics Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-03-06 with total page 1961 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.
