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Does calling structure information improve the accuracy of fault prediction?
2009
2009 6th IEEE International Working Conference on Mining Software Repositories
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The addition of calling structure information to a model based solely on non-calling structure code attributes provided noticeable improvement in prediction accuracy, but only marginally improved the best ...
In this study of an industrial software system, we investigate the effectiveness of adding information about calling structure to fault prediction models. ...
Any opinions expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. ...
doi:10.1109/msr.2009.5069481
dblp:conf/msr/ShinBOW09
fatcat:a6vjvxxlh5hypk3y6y5zzm5eou
Fault Prediction of Electronic Equipment Based on Combination Prediction Model
2015
International Journal of Control and Automation
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This paper analyses some typical fault prediction method of electronic equipment, and presented improvement measures for the practical problems, finally proposed a combination of fault prediction model ...
Fault prediction is the precondition of Condition Based Maintenance (CBM), accurate prediction for equipment can not only make warning before failure occurs, but also reduce the cost of maintenance of ...
To choose the appropriate feature extraction method can improve the accuracy of the prediction to a great extent. ...
doi:10.14257/ijca.2015.8.5.18
fatcat:m36mkngasre3fd6nxaykqn7qnm
A BP Neural Network Prediction Model Based on Dynamic Cuckoo Search Optimization Algorithm for Industrial Equipment Fault Prediction
2019
IEEE Access
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And the experimental results show that the proposed prediction model has faster convergence and higher accuracy. INDEX TERMS IWSN, fault prediction, BP neural network, dynamic cuckoo search. ...
In the process of discovering the global optimal solution, the probability of preserving the offspring with good fitness is increased, and the uncertainty of preference random walk is improved. ...
The algorithm improves the training speed of the fuzzy logic control model, but the algorithm still has certain deficiencies in the accuracy of the equipment fault prediction. ...
doi:10.1109/access.2019.2892729
fatcat:s73r6j5xzzcopf43ikryl4d66y
Programmer-based fault prediction
2010
Proceedings of the 6th International Conference on Predictive Models in Software Engineering - PROMISE '10
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The goal of the investigation is to determine whether information about which particular developer modified a file is able to improve defect predictions. ...
In contrast, very little research exists to indicate whether information about individual developers can profitably be used to improve predictions. ...
If so, we might be able to use that information to improve the accuracy of our prediction models. ...
doi:10.1145/1868328.1868357
dblp:conf/promise/OstrandWB10
fatcat:heb53kwgujb6zdsbcgpuwrduba
Software Maintenance Severity Prediction With Soft Computing Approach
2009
Zenodo
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The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software. ...
the modeling of maintenance severity or impact of fault severity. ...
affect the Accuracy of software quality prediction. ...
doi:10.5281/zenodo.1330266
fatcat:74z7fncbefak3fxaligriojewa
Prediction
[article]
2010
arXiv
pre-print
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On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particularly ...
The so-called self-exciting Hawkes point processes capture parsimoniously the idea that events can trigger other events, and their cascades of interactions and mutual influence are essential to understand ...
significant improvements in predicting the dynamics of the system. ...
arXiv:1007.2420v1
fatcat:5rivn4q4w5ggfpaihcdwokujjm
Class level fault prediction using software clustering
2013
2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE)
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Classes are clustered using structural information and fault prediction models are built using the metrics on the classes in each cluster identified. ...
We propose a intrarelease fault prediction technique, which learns from clusters of related classes, rather than from the entire system. ...
ACKNOWLEDGMENT We would like to thank the Maria La Becca, who developed some of the software modules of the prototype implementing the clustering approach presented here. ...
doi:10.1109/ase.2013.6693126
dblp:conf/kbse/ScannielloGMM13
fatcat:2fkvmxqnlfgpdd433yl2pbenxm
Rethinking Earthquake Prediction
1999
Pure and Applied Geophysics
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A series of recent articles in scientific literature and the media claim that earthquakes cannot be predicted and that exceedingly high accuracy is needed for predictions to be of societal value. ...
That a natural system is complex does not mean that predictions are not possible for some spatial, temporal and size regimes. ...
Wyss for their critical reading of the manuscript and J. Deng and S. Jaumé for discussions. This work was supported by the Southern California Earthquake Center. ...
doi:10.1007/s000240050263
fatcat:wfskfejrk5hohhpu7zcxbitdlm
Rethinking Earthquake Prediction
[chapter]
1999
Seismicity Patterns, their Statistical Significance and Physical Meaning
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A series of recent articles in scientific literature and the media claim that earthquakes cannot be predicted and that exceedingly high accuracy is needed for predictions to be of societal value. ...
That a natural system is complex does not mean that predictions are not possible for some spatial, temporal and size regimes. ...
Wyss for their critical reading of the manuscript and J. Deng and S. Jaumé for discussions. This work was supported by the Southern California Earthquake Center. ...
doi:10.1007/978-3-0348-8677-2_2
fatcat:nwy4l5qbozhkjei2iz6wnmqjdy
Distributed Monitoring with Collaborative Prediction
2012
2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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We formulate the problem of probe selection for fault prediction based on end-to-end probing as a Collaborative Prediction (CP) problem. ...
Isolating users from the inevitable faults in large distributed systems is critical to Quality of Experience. ...
ACKNOWLEDGMENTS This work has been partially supported by the European Infrastructure Project EGI-InsPIRE INFSO-RI-261323, by France-Grilles, and by the Chinese Scholarship Council. ...
doi:10.1109/ccgrid.2012.36
dblp:conf/ccgrid/FengGG12
fatcat:fr2iw2zg5fhl3fkdiadqopguoe
Software Defect Prediction using Adaptive Neural Networks
2012
International Journal of Applied Information Systems
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A vigilance parameter (θ) in ARNN defines the stopping criterion and hence helps in manipulating the accuracy of the trained network. ...
maximum Recall (i.e. true negative rate) is 100% and average Precision=54%.In case of ART n/w shortfalls are seen for Accuracy as this is a subjective measure. ...
Either a smaller number of correctly predicted faulty modules or a large number of erroneously tagged fault-free modules would result in ACCURACY:-The accuracy measures the chances of correctly predicting ...
doi:10.5120/ijais12-450612
fatcat:qd6ptmnhxrhgtgzxvduygvkuwe
Performance prediction of paging workloads using lightweight tracing
2006
Future generations computer systems
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This leads to a slight loss of accuracy. Using a suite of memory-intensive applications, we evaluate the capture overhead and measure the predictive accuracy of the approach. ...
Replaying system call traces alone sometimes leads to inaccurate predictions because paging, and access to memorymapped files, are not modelled. This paper extends tracing to handle such workloads. ...
With this information recorded in the traces, trace replay can be extended to reproduce a workload's memory referencing behaviour at the page level, thereby improving the accuracy of the predictions that ...
doi:10.1016/j.future.2006.02.003
fatcat:fte2mqxqszgkxomd2jp4pzciga
Towards Benchmarking Feature Subset Selection Methods for Software Fault Prediction
[chapter]
2016
Studies in Computational Intelligence
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We conclude that in general, FSS is beneficial as it helps improve classification accuracy of NB and C4.5. ...
(CFS); consistency-based subset evaluation (CNS); wrapper subset evaluation (WRP); and an evolutionary computation method, genetic programming (GP), on five fault prediction datasets from the PROMISE ...
GP is well suited for symbolic regression problems, as it does not make any assumptions about the structure of the function. ...
doi:10.1007/978-3-319-25964-2_3
fatcat:nayb6jq2kzeapexcdobbk2xpbi
Service Outages Prediction through Logs and Tickets Analysis
2021
International Journal of Advanced Computer Science and Applications
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Accurate prediction of faults helps in responding to downtime even before the customer tickets are raised or network trouble is encountered. ...
The work refers to i) identifying number of trouble tickets that are related to the device a few days before the network component fails, ii) predicting fault will occur in broadband networks. ...
The proposed techniques try to better them in terms of accuracy of prediction of faults. ...
doi:10.14569/ijacsa.2021.0120424
fatcat:z4cew5gxzzgytb3r7ppc5t3se4
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
2017
Journal of Reliable Intelligent Environments
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2019 pre-print arXiv:1903.11993v1 fatcat:x3v4f25tuvhrxblile6lzfl57a
Deeper structure, i.e. the stacked autoencoder has been found to be useful for a more complex localization function where a large amount of information needs to be worked through, in different layers, ...
To tackle the above problem, we propose a fault detection and localization model based on a combination of shallow and deep learning structures. ...
Prediction of impending failure, dealing with incomplete information and analyzing trends to predict failure are some of the key requirements. ...
doi:10.1007/s40860-017-0053-y
fatcat:iym4uouhqzer7gek3llyqxbuje
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