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Hybrid optimization-enabled deep Q network for fault prediction in service-oriented architecture
Fault prediction in service-oriented architecture-based models has been recognized as one of the essential processes to reduce computational expenses...
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Software fault prediction using deep learning techniques
Software fault prediction (SFP) techniques identify faults at the early stages of the software development life cycle (SDLC). We find machine...
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Software fault prediction with imbalanced datasets using SMOTE-Tomek sampling technique and Genetic Algorithm models
Over the years, there has been a considerable discussion regarding machine learning (ML) techniques to forecast software faults. It can be...
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Improved Software Fault Prediction Model Based on Optimal Features Set and Threshold Values Using Metaheuristic Approach
Software fault prediction models are very important to prioritize software classes for effective testing and efficient use of resources so that the...
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The impact of class imbalance techniques on crashing fault residence prediction models
Software crashes occur when the software program is executed wrongly or interrupted compulsively, which negatively impacts on user experience. Since...
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Decision Tree Regression Analysis of Proposed Metric Suite for Software Fault Prediction
The objective of this study is to identify a metric suite for software fault prediction that can solve challenges related to reliability, quality,...
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An Efficient Hybrid Mine Blast Algorithm for Tackling Software Fault Prediction Problem
An inherent problem in software engineering is that competing prediction systems have been found to produce conflicting results. Yet accurate...
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Prediction of fault evolution and remaining useful life for rolling bearings with spalling fatigue using digital twin technology
AbstractQuantifying fault severity is a critical part of rolling bearing health management. There are numerous methods for evaluating the severity of...
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SS-WDRN: sparrow search optimization-based weighted dual recurrent network for software fault prediction
Predicting software faults at the primary stage is a challenging role for software engineers and tech industries. During the development of software...
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An Experience in the Evaluation of Fault Prediction
Background. ROC (Receiver Operating Characteristic) curves are widely used to represent the performance (i.e., degree of correctness) of fault...
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A machine and deep learning analysis among SonarQube rules, product, and process metrics for fault prediction
BackgroundDevelopers spend more time fixing bugs refactoring the code to increase the maintainability than develo** new features. Researchers...
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Fault-attri-attention: a method for fault identification based on seismic attributes attention
The imaging principle of seismic images is different from natural images, which results in very limited resolution, complex reflection features and...
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DBOS_US: a density-based graph under-sampling method to handle class imbalance and class overlap issues in software fault prediction
Improving software quality by predicting faults during the early stages of software development is a primary goal of software fault prediction (SFP)....
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FaultGuard: A Generative Approach to Resilient Fault Prediction in Smart Electrical Grids
Predicting and classifying faults in electricity networks is crucial for uninterrupted provision and kee** maintenance costs at a minimum. Thanks...
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Analysis of Different Sampling Techniques for Software Fault Prediction
The process of predicting whether or not a software module is faulty based on specific metrics is known as software fault prediction. Software faults...
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Data quality issues in software fault prediction: a systematic literature review
Software fault prediction (SFP) aims to improve software quality with a possible minimum cost and time. Various machine learning models have been...
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Software Fault Prediction Using Deep Neural Networks
Software failure prediction is the process of building models that software interpreters can use to detect faulty constructs early in the software...
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Software fault prediction using lion optimization algorithm
Software fault prediction (SFP) refers to the early prediction of fault-prone modules in software development which are susceptible to faults and...
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3G Cellular Network Fault Prediction Using LSTM-Conv1D Model
Cellular network plays an important role in daily life by exploring digital world of communication. Cellular network technology continuously evolves...
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Prediction of software fault-prone classes using ensemble random forest with adaptive synthetic sampling algorithm
The process of predicting fault module in software is known as Software Fault Prediction (SFP) which is important for releasing software versions...
