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Does calling structure information improve the accuracy of fault prediction?

Yonghee Shin, Robert Bell, Thomas Ostrand, Elaine Weyuker
2009 2009 6th IEEE International Working Conference on Mining Software Repositories  
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

Xiaohui Ye
2015 International Journal of Control and Automation  
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

Wenbo Zhang, Guangjie Han, Jing Wang, Yue Liu
2019 IEEE Access  
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

Thomas J. Ostrand, Elaine J. Weyuker, Robert M. Bell
2010 Proceedings of the 6th International Conference on Predictive Models in Software Engineering - PROMISE '10  
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

Ebru Ardil, Erdem Uçar, Parvinder S. Sandhu
2009 Zenodo  
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]

Didier Sornette, Ivan Osorio
2010 arXiv   pre-print
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

Giuseppe Scanniello, Carmine Gravino, Andrian Marcus, Tim Menzies
2013 2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE)  
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

L. R. Sykes, B. E. Shaw, C. H. Scholz
1999 Pure and Applied Geophysics  
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]

Lynn R. Sykes, Bruce E. Shaw, Christopher H. Scholz
1999 Seismicity Patterns, their Statistical Significance and Physical Meaning  
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

Dawei Feng, Cécile Germain-Renaud, Tristan Glatard
2012 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)  
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

Seema Singh, Mandeep Singh
2012 International Journal of Applied Information Systems  
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

Ariel N. Burton, Paul H.J. Kelly
2006 Future generations computer systems  
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]

Wasif Afzal, Richard Torkar
2016 Studies in Computational Intelligence  
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

Sunita A Yadwad, V. Valli, S Venkata
2021 International Journal of Advanced Computer Science and Applications  
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

Lav Gupta, M Samaka, Raj Jain, Aiman Erbad, Deval Bhamare, H Anthony Chan
2017 Journal of Reliable Intelligent Environments  
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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