The Cold Start Problem In Software Fault Prediction
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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.
Software Fault Prediction
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Author : Sandeep Kumar
language : en
Publisher: Springer
Release Date : 2018-06-06
Software Fault Prediction written by Sandeep Kumar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-06 with Computers categories.
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.
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.
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.
Learning From Failure
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Author : Falco Dürsch
language : en
Publisher: Universitätsverlag Potsdam
Release Date : 2023-03-15
Learning From Failure written by Falco Dürsch and has been published by Universitätsverlag Potsdam this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-15 with Computers categories.
Regression testing is a widespread practice in today's software industry to ensure software product quality. Developers derive a set of test cases, and execute them frequently to ensure that their change did not adversely affect existing functionality. As the software product and its test suite grow, the time to feedback during regression test sessions increases, and impedes programmer productivity: developers wait longer for tests to complete, and delays in fault detection render fault removal increasingly difficult. Test case prioritization addresses the problem of long feedback loops by reordering test cases, such that test cases of high failure probability run first, and test case failures become actionable early in the testing process. We ask, given test execution schedules reconstructed from publicly available data, to which extent can their fault detection efficiency improved, and which technique yields the most efficient test schedules with respect to APFD? To this end, we recover regression 6200 test sessions from the build log files of Travis CI, a popular continuous integration service, and gather 62000 accompanying changelists. We evaluate the efficiency of current test schedules, and examine the prioritization results of state-of-the-art lightweight, history-based heuristics. We propose and evaluate a novel set of prioritization algorithms, which connect software changes and test failures in a matrix-like data structure. Our studies indicate that the optimization potential is substantial, because the existing test plans score only 30% APFD. The predictive power of past test failures proves to be outstanding: simple heuristics, such as repeating tests with failures in recent sessions, result in efficiency scores of 95% APFD. The best-performing matrix-based heuristic achieves a similar score of 92.5% APFD. In contrast to prior approaches, we argue that matrix-based techniques are useful beyond the scope of effective prioritization, and enable a number of use cases involving software maintenance. We validate our findings from continuous integration processes by extending a continuous testing tool within development environments with means of test prioritization, and pose further research questions. We think that our findings are suited to propel adoption of (continuous) testing practices, and that programmers' toolboxes should contain test prioritization as an existential productivity tool.
Artificial Intelligence And Information Technologies
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Author : Arvind Dagur
language : en
Publisher: CRC Press
Release Date : 2024-07-31
Artificial Intelligence And Information Technologies written by Arvind Dagur and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Computers categories.
This book contains the proceedings of a non-profit conference with the objective of providing a platform for academicians, researchers, scholars and students from various institutions, universities and industries in India and abroad to exchange their research and innovative ideas in the field of Artificial Intelligence and information technologies. It begins with exploring the research and innovation in the field of Artificial Intelligence and information technologies, including secure transaction, monitoring, real time assistance and security for advanced stage learners, researchers and academicians has been presented. It goes on to cover: Broad knowledge and research trends about Artificial Intelligence and information technologies and their role in today’s digital era Depiction of system model and architecture for clear picture of Artificial Intelligence in real life Discussion on the role of Artificial Intelligence in various real-life problems such as banking, healthcare, navigation, communication and security Explanation of the challenges and opportunities in Artificial Intelligence-based healthcare, education, banking and related industries Recent information technologies and challenges in this new epoch This book will be beneficial to researchers, academicians, undergraduate students, postgraduate students, research scholars, professionals, technologists and entrepreneurs.
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.
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.
Object Oriented Metrics
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Author : Brian Henderson-Sellers
language : en
Publisher: Prentice Hall
Release Date : 1996
Object Oriented Metrics written by Brian Henderson-Sellers and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.
Object-oriented (OO) metrics are an integral part of object technology -- at the research level and in commercial software development projects. This book offers theoretical and empirical tips and facts for creating an OO complexity metrics (measurement) program, based on a review of existing research from the last several years. KEY TOPICS: Covers moving through object-oriented concepts as they related to managing the project lifecycle; the framework in which metrics exist; structural complexity metrics for traditional systems; OO product metrics; and current industrial applications. MARKET: For software developers, programmers, and managers.