Fault Prediction Approach
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Fault Prediction Approach
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Author : Dhana Laxmi
language : en
Publisher:
Release Date : 2019-03-28
Fault Prediction Approach written by Dhana Laxmi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-28 with categories.
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
Software Fault Prediction Models Using Machine Learning Approach
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Author : Golnoush Abaei
language : en
Publisher:
Release Date : 2015
Software Fault Prediction Models Using Machine Learning Approach written by Golnoush Abaei and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
The Cold Start Problem In Software Fault Prediction
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Author : Inbal Roshanski
language : en
Publisher:
Release Date : 2020
The Cold Start Problem In Software Fault Prediction written by Inbal Roshanski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
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.
Fault Prediction Modeling For The Prediction Of Number Of Software Faults
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Author : Santosh Singh Rathore
language : en
Publisher: Springer
Release Date : 2019-04-03
Fault Prediction Modeling For The Prediction Of Number Of Software Faults written by Santosh Singh Rathore and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-03 with Computers categories.
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.
Enhancing Software Fault Prediction With Machine Learning Emerging Research And Opportunities
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Author : Rashid, Ekbal
language : en
Publisher: IGI Global
Release Date : 2017-09-13
Enhancing Software Fault Prediction With Machine Learning Emerging Research And Opportunities written by Rashid, Ekbal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-13 with Computers categories.
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.
An Ann Based Approach For Software Fault Prediction Using Object Oriented Metrics
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Author : Independently Published
language : en
Publisher:
Release Date : 2018-09-10
An Ann Based Approach For Software Fault Prediction Using Object Oriented Metrics written by Independently Published and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-10 with categories.
During recent years, the enormous increase in demand for software products has been experienced. High quality software is the major demand of users. Predicting the faults in early stages will improve the quality of software and apparently reduce the development efforts or cost. Fault prediction is majorly based on the selection of technique and the metrics to predict the fault. Thus metrics selection is a critical part of software fault prediction. Currently techniques been evaluated based on traditional set of metrics. There is a need to identify the different techniques and evaluate them on the bases of appropriate metrics. In this research, Artificial neural network based SFP model is designed. The ANN model is trained using Levenberg Marquardt (LM) Algorithm For classification task, ANN is one of the most effective technique. Prediction is performed on the basis of object-oriented metrics. 5 object oriented metrics . are selected as input parameter from CK and Martin metric sets are selected as input parameters. DIT(Depth of inheritance tree, RFC(Response for class), WMC (weíghted methods per class), Ca (Afferent coupling), CBO (couplíng between objects) are the metrics used in this study. The experiments are performed on 18 public datasets from PROMISE repository. Receiver operating characteristic curve, accuracy, and Mean squared error are taken as performance parameters for the prediction task. The results of the proposed systems signify that ANN provides significant results in terms of accuracy and error rate.
Software Fault Prediction
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Author : Devi Akalya
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2012-06
Software Fault Prediction written by Devi Akalya and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06 with categories.
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.
Architecture Aware Online Failure Prediction For Software Systems
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Author : Teerat Pitakrat
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-06-19
Architecture Aware Online Failure Prediction For Software Systems written by Teerat Pitakrat and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with Computers categories.
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.
Fault Prediction Method For Product Development
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Author :
language : en
Publisher:
Release Date : 2008
Fault Prediction Method For Product Development written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Search Based Approaches To Software Fault Prediction And Software Testing
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Author : Wasif Afzal
language : en
Publisher:
Release Date : 2009
Search Based Approaches To Software Fault Prediction And Software Testing written by Wasif Afzal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.