Download or read book Fault Prediction Approach written by Dhana Laxmi and published by . This book was released on 2019-03-28 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2019 in the subject Computer Science - Software, grade: A, course: Doctoral Degree, language: English, abstract: This research works seeks to explore and provide an improved fault detection approach for inspection and fault detection. It systematically investigate and characterize software faults and faults to improve fault detection and prevention mechanisms in the quality software development process. Firstly, it contributes an Adaptive PSO-based association rule mining techniques for software fault classification using ANN. This task categorizes real defects by finding the best support and reliability to have the best policy for software fault classification using ANN. Secondly, it provides a Fault Prediction Approach (FPA) based on probabilistic models to perform software testing in Software Inspection. This describes a cost-effective way to accurately detect the defects by performing software inspection to develop quality software. The proposed FPA probes stochastic methods using the modified Naive Bayes classification to estimate the possible faults in the experimental environment to suggest novel defect control development. Software reliability engineering has become very important as the complexity of the system has increased exponentially with technological advances. The fact that all systems today depend on many other systems and interfaces is not only an application error but also a number of environmental factors that lead to failure. The impact of these failures depends on the nature of the system, but many of them cause customer dissatisfaction and business loss. System testing and fault detection have become the most important processes in the software life cycle. Various failure prediction models can be analyzed and suggested so that failures can be detected at an early stage and many test efforts can be saved. Software development has many defects in the design phase. In the past, many examples of software development

Download or read book Software Fault Prediction Models Using Machine Learning Approach written by Golnoush Abaei and published by . This book was released on 2015 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Cold start Problem in Software Fault Prediction written by Inbal Roshanski and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Software is an integral part of our lives today. Unfortunately, the more sophisticated and complicated software becomes, the greater the chance of failures. Predicting the probability of software components being faulty can help maintaining the software effectiveness. A key factor to the success of prediction algorithms is the amount and quality of historical data of the project collected by the version control and issue tracker tools. However, for new projects, for example, there is no historical data to learn from. This is known as the cold-start problem. Previous work proposed cross-project software fault prediction models, where fault prediction models of other projects are used to determine whether new project's components are faulty or not. In this paper we suggest a novel component-sensitive cross-project software fault prediction approach (OSCAR). OSCAR proceeds in two steps. First, it separately classifies each component in the new project to its most similar project among a set of other projects. Then, OSCAR uses the fault prediction model of that project to predict whether the component in the new project is faulty. This approach is in contrast to previous work that try to find one suitable model for all the components in the new project. Furthermore, we suggest an improvement to OSCAR, by using clustering algorithm combined with it. Evaluation, conducted on three datasets which includes 43 software projects, shows that the prediction of OSCAR is more accurate than state-of-the-art competitive algorithms.

Download or read book Fault Prediction Modeling for the Prediction of Number of Software Faults written by Santosh Singh Rathore and published by Springer. This book was released on 2019-04-03 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses software faults—a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults. A must-read for readers seeking a “one-stop” source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.

Download or read book Software Fault Prediction written by Sandeep Kumar and published by Springer. This book was released on 2018-06-06 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on exploring the use of software fault prediction in building reliable and robust software systems. It is divided into the following chapters: Chapter 1 presents an introduction to the study and also introduces basic concepts of software fault prediction. Chapter 2 explains the generalized architecture of the software fault prediction process and discusses its various components. In turn, Chapter 3 provides detailed information on types of fault prediction models and discusses the latest literature on each model. Chapter 4 describes the software fault datasets and diverse issues concerning fault datasets when building fault prediction models. Chapter 5 presents a study evaluating different techniques on the basis of their performance for software fault prediction. Chapter 6 presents another study evaluating techniques for predicting the number of faults in the software modules. In closing, Chapter 7 provides a summary of the topics discussed. The book will be of immense benefit to all readers who are interested in starting research in this area. In addition, it offers experienced researchers a valuable overview of the latest work in this area.

Download or read book 2021 9th International Conference in Software Engineering Research and Innovation CONISOFT written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enhancing Software Fault Prediction With Machine Learning Emerging Research and Opportunities written by Rashid, Ekbal and published by IGI Global. This book was released on 2017-09-13 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative source of material on the latest advances and strategies for software quality prediction. Including a range of pivotal topics such as case-based reasoning, rate of improvement, and expert systems, this book is an ideal reference source for engineers, researchers, academics, students, professionals, and practitioners interested in novel developments in software design and analysis.

Download or read book A Metrics Suite for Object Oriented Design written by Shyam R Chidamber and published by Franklin Classics. This book was released on 2018-10-15 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Download or read book Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery written by Yaguo Lei and published by Butterworth-Heinemann. This book was released on 2016-11-02 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery provides a comprehensive introduction of intelligent fault diagnosis and RUL prediction based on the current achievements of the author's research group. The main contents include multi-domain signal processing and feature extraction, intelligent diagnosis models, clustering algorithms, hybrid intelligent diagnosis strategies, and RUL prediction approaches, etc. This book presents fundamental theories and advanced methods of identifying the occurrence, locations, and degrees of faults, and also includes information on how to predict the RUL of rotating machinery. Besides experimental demonstrations, many application cases are presented and illustrated to test the methods mentioned in the book. This valuable reference provides an essential guide on machinery fault diagnosis that helps readers understand basic concepts and fundamental theories. Academic researchers with mechanical engineering or computer science backgrounds, and engineers or practitioners who are in charge of machine safety, operation, and maintenance will find this book very useful. Provides a detailed background and roadmap of intelligent diagnosis and RUL prediction of rotating machinery, involving fault mechanisms, vibration characteristics, health indicators, and diagnosis and prognostics Presents basic theories, advanced methods, and the latest contributions in the field of intelligent fault diagnosis and RUL prediction Includes numerous application cases, and the methods, algorithms, and models introduced in the book are demonstrated by industrial experiences

Download or read book Software Fault Prediction written by Devi Akalya and published by LAP Lambert Academic Publishing. This book was released on 2012-06 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quality of the software is an important factor for any software company. Software fault prediction is a data mining process that helps to improve the quality. Data mining tools both open source and proprietary are available today. These bring lots of research works in this area. Software fault is the bug in the software that is identified only after its installation and it makes the software behave not in the expected way. Bug is there even after testing due to various constraints like cost, time. Prediction will help identify those fault prone areas and with that one can concentrate on those modules in future. Hybrid Feature Selection and Hybrid Classifier approach is a way to improve the software fault prediction accuracy. In Hybrid feature selection, irrelevant, redundant features are first filtered and this filtered feature set reduces the input feature set of wrapper. In Hybrid Classifier approach Linear Discriminant Analysis score is used as an additional feature for Neural Network classifier. These models give a better fault prediction accuracy.

Download or read book Automated Software Engineering A Deep Learning Based Approach written by Suresh Chandra Satapathy and published by Springer Nature. This book was released on 2020-01-07 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses various open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation. Many traditional techniques are available for addressing these problems. But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software’s complexity. Hence, many previously used methods are proving insufficient to solve the problems now arising in software development. The book highlights a number of unique problems and effective solutions that reflect the state-of-the-art in software engineering. Deep learning is the latest computing technique, and is now gaining popularity in various fields of software engineering. This book explores new trends and experiments that have yielded promising solutions to current challenges in software engineering. As such, it offers a valuable reference guide for a broad audience including systems analysts, software engineers, researchers, graduate students and professors engaged in teaching software engineering.

Download or read book International Conference on Communication Computing and Electronics Systems written by V. Bindhu and published by Springer Nature. This book was released on 2021-03-25 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality papers presented at the International Conference on Communication, Computing and Electronics Systems 2020, held at the PPG Institute of Technology, Coimbatore, India, on 21–22 October 2020. The book covers topics such as automation, VLSI, embedded systems, integrated device technology, satellite communication, optical communication, RF communication, microwave engineering, artificial intelligence, deep learning, pattern recognition, Internet of Things, precision models, bioinformatics, and healthcare informatics.

Download or read book Architecture Aware Online Failure Prediction for Software Systems written by Teerat Pitakrat and published by BoD – Books on Demand. This book was released on 2018-06-19 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Failures at runtime in complex software systems are inevitable because these systems usually contain a large number of components. Having all components working perfectly at the same time is, if at all possible, very difficult. Hardware components can fail and software components can still have hidden faults waiting to be triggered at runtime and cause the system to fail. This dissertation proposes an architecture-aware online failure prediction approach, called Hora. The Hora approach improves online failure prediction by combining the results of failure prediction with the architectural knowledge about the system. The task of failure prediction is split into predicting the failure of each individual component, in contrast to predicting the whole system failure. Suitable prediction techniques can be employed for different types of components. The architectural knowledge is used to deduce the dependencies between components which can reflect how a failure of one component can affect the others. The failure prediction and the component dependencies are combined into one model which employs Bayesian network theory to represent failure propagation. The combined model is continuously updated at runtime and makes predictions for individual components, as well as inferring their effects on other components and the whole system.

Download or read book Fundamentals and Methods of Machine and Deep Learning written by Pradeep Singh and published by John Wiley & Sons. This book was released on 2022-02-01 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.

Download or read book Fault Prediction Method for Product Development written by and published by . This book was released on 2008 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pre Earthquake Processes written by Dimitar Ouzounov and published by John Wiley & Sons. This book was released on 2018-05-30 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pre-Earthquake signals are advanced warnings of a larger seismic event. A better understanding of these processes can help to predict the characteristics of the subsequent mainshock. Pre-Earthquake Processes: A Multidisciplinary Approach to Earthquake Prediction Studies presents the latest research on earthquake forecasting and prediction based on observations and physical modeling in China, Greece, Italy, France, Japan, Russia, Taiwan, and the United States. Volume highlights include: Describes the earthquake processes and the observed physical signals that precede them Explores the relationship between pre-earthquake activity and the characteristics of subsequent seismic events Encompasses physical, atmospheric, geochemical, and historical characteristics of pre-earthquakes Illustrates thermal infrared, seismo–ionospheric, and other satellite and ground-based pre-earthquake anomalies Applies these multidisciplinary data to earthquake forecasting and prediction Written for seismologists, geophysicists, geochemists, physical scientists, students and others, Pre-Earthquake Processes: A Multidisciplinary Approach to Earthquake Prediction Studies offers an essential resource for understanding the dynamics of pre-earthquake phenomena from an international and multidisciplinary perspective.

Download or read book Handbook of Research on Emerging Advancements and Technologies in Software Engineering written by Ghani, Imran and published by IGI Global. This book was released on 2014-04-30 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced approaches to software engineering and design are capable of solving complex computational problems and achieving standards of performance that were unheard of only decades ago. Handbook of Research on Emerging Advancements and Technologies in Software Engineering presents a comprehensive investigation of the most recent discoveries in software engineering research and practice, with studies in software design, development, implementation, testing, analysis, and evolution. Software designers, architects, and technologists, as well as students and educators, will find this book to be a vital and in-depth examination of the latest notable developments within the software engineering community.