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Predicting and Classifying Software Faults
Proceedings of the 2019 7th International Conference on Computer and Communications Management, 2019In the field of software engineering, the detection of fault in the software has become a major topic to explore. With the help of data mining and machine learning approaches, this paper aims to denote whether a software is fault prone or not. In order to accomplish that this paper gives importance to compare between different machine learning ...
Shamse Tasnim Cynthia +1 more
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An empirical study of some software fault prediction techniques for the number of faults prediction
Soft Computing, 2016During the software development process, prediction of the number of faults in software modules can be more helpful instead of predicting the modules being faulty or non-faulty. Such an approach may help in more focused software testing process and may enhance the reliability of the software system.
Santosh Singh Rathore +1 more
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Performance tuning for automotive Software Fault Prediction
2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), 2017Fault prediction on high quality industry grade software often suffers from strong imbalanced class distribution due to a low bug rate. Previous work reports on low predictive performance, thus tuning parameters is required. As the State of the Art recommends sampling methods for imbalanced learning, we analyse effects when under- and oversampling the ...
Harald Altinger +4 more
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Novel Algorithms for Web Software Fault Prediction
Quality and Reliability Engineering International, 2014Reliability is gaining importance with time for Web system because of the popularity of different Web‐based applications, namely, different Web sites and social community networks. In order to aggrandize the reliability of a Web system, some methods are required to measure its current reliability.
Subhashis Chatterjee, Arunava Roy
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A Software Fault Prediction on Inter- and Intra-Release Prediction Scenarios
International Journal of Open Source Software and Processes, 2021Software quality engineering applied numerous techniques for assuring the quality of software, namely testing, verification, validation, fault tolerance, and fault prediction of the software. The machine learning techniques facilitate the identification of software modules as faulty or non-faulty.
Ashutosh Mishra, Meenu Singla
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A taxonomy of metrics for software fault prediction
Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019In the field of Software Fault Prediction (SFP), researchers exploit software metrics to build predictive models using machine learning and/or statistical techniques. SFP has existed for several decades and the number of metrics used has increased dramatically.
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Software Fault Prediction Models for Web Applications
2010 IEEE 34th Annual Computer Software and Applications Conference Workshops, 2010Our daily life increasingly relies on Web applications. Web applications provide us with abundant services to support our everyday activities. As a result, quality assurance for Web applications is becoming important and has gained much attention from software engineering community.
Le Truong Giang +2 more
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Prediction of Undetected Faults in Safety-Critical Software
2019 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2019Safety-critical software systems need to meet exceptionally strict standards in terms of dependability. Best practice to achieve this is to follow and develop the software according to domain specific standards. These standards give guidelines on development and testing activities.
Johan Sundell +3 more
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Variance Analysis in Software Fault Prediction Models
2009 20th International Symposium on Software Reliability Engineering, 2009Software fault prediction models play an important role in softwarequality assurance. They identify software subsystems (modules,components, classes, or files) which are likely to contain faults.These subsystems, in turn, receive additional resources forverification and validation activities.
Yue Jiang 0001 +3 more
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Software fault prediction using firefly algorithm
International Journal of Intelligent Engineering Informatics, 2018The software fault prediction (SFP) literature has shown an immense growth of the research studies involving the artificial neural network (ANN) based fault prediction models. However, the default gradient descent back propagation neural networks (BPNNs) have a high risk of getting stuck in the local minima of the search space.
Ishani Arora, Anju Saha
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