An empirical study of some software fault prediction techniques for the number of faults prediction
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DOI: 10.1007/s00500-016-2284-x
Abstract: During 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… read more here.
Keywords: fault prediction; regression; number faults; prediction ... See more keywords
Flow shop failure prediction problem based on Grey-Markov model
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DOI: 10.1007/s00779-021-01618-0
Abstract: Mechanical equipment in the process of operation appears a variety of faults due to different reasons. These faults affect the operation of machinery, causing economic losses, moreover, it may cause accidents, or even casualties. Predicting… read more here.
Keywords: flow shop; fault prediction; model; prediction ... See more keywords
Multiple-classifiers in software quality engineering: Combining predictors to improve software fault prediction ability
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DOI: 10.1016/j.jestch.2019.10.005
Abstract: Abstract Software development projects require a critical and costly testing phase to investigate efficiency of the resultant product. As the size and complexity of project increases, manual prediction of software defects becomes a time consuming… read more here.
Keywords: software quality; fault prediction; prediction; software ... See more keywords
Big data analytics based fault prediction for shop floor scheduling
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DOI: 10.1016/j.jmsy.2017.03.008
Abstract: The current task scheduling mainly concerns the availability of machining resources, rather than the potential errors after scheduling. To minimise such errors in advance, this paper presents a big ... read more here.
Keywords: big data; fault prediction; data analytics; based fault ... See more keywords
Linear regression with factor analysis in fault prediction of software
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DOI: 10.1080/09720502.2020.1721641
Abstract: Abstract In software fault prediction, before beginning with the real software testing process, faultprone software modules are identified with the help of various properties related to the software project. This leads to the achievement of… read more here.
Keywords: factor analysis; software fault; fault prediction; software ... See more keywords
Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction
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DOI: 10.1109/access.2018.2835304
Abstract: Software fault prediction is a consequential research area in software quality promise. In this paper, we propose a semi-supervised deep fuzzy C-mean (DFCM) clustering for software fault prediction, which is the cumulation of semi-supervised DFCM… read more here.
Keywords: fault prediction; semi supervised; software fault; prediction ... See more keywords
The Empirical Study of Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction
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DOI: 10.1109/access.2018.2866082
Abstract: Software fault prediction is a very consequent research topic for software quality assurance. The performance of fault prediction model depends on the features that are used to train it. Redundant and irrelevant features can hinder… read more here.
Keywords: fault prediction; software fault; performance; prediction ... See more keywords
A Fault Prediction Model of Adaptive Fuzzy Neural Network for Optimal Membership Function
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DOI: 10.1109/access.2020.2997368
Abstract: As an essential and challenging technology of fault prediction and health management(PHM), fault prediction technology has been a research focus in the field of fault diagnosis. However, the current model-based fault prediction technology and data-driven… read more here.
Keywords: membership; fault; model; prediction ... See more keywords
Efficacy of Inheritance Aspect in Software Fault Prediction—A Survey Paper
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DOI: 10.1109/access.2020.3022087
Abstract: Software fault prediction (SFP) is a research area that helps development and testing process deliver software of good quality. Software metrics are of various types and are used in SFP for measurements. Inheritance is a… read more here.
Keywords: software fault; fault prediction; inheritance; software ... See more keywords
A Deep Explainable Model for Fault Prediction Using IoT Sensors
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DOI: 10.1109/access.2022.3184693
Abstract: IoT sensors and deep learning models can widely be applied for fault prediction. Although deep learning models are considerably more potent than many conventional machine learning models, they are not transparent. This paper first examines… read more here.
Keywords: time; iot sensors; fault; model ... See more keywords
Process Monitoring and Fault Prediction in Multivariate Time Series Using Bag-of-Words
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DOI: 10.1109/tase.2020.3026065
Abstract: Multivariate time series (MTS) arise due to multisensor data collection in manufacturing. These data are complex in the sense that attributes have a varying scale, volitivity, continuity, and so on, and interattribute dependence also appears,… read more here.
Keywords: time; time series; mts; fault ... See more keywords