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Ball bearing fault detection using an acoustic based machine learning approach. [PDF]

Sci Rep
Chandrakala CB, Karumanchi SS, Raghudathesh GP, Madhwesh N.   +3 more
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Software fault prediction tool

Proceedings of the 19th international symposium on Software testing and analysis, 2010
We have developed an interactive tool that predicts fault likelihood for the individual files of successive releases of large, long-lived, multi-developer software systems. Predictions are the result of a two-stage process: first, the extraction of current and historical properties of the system, and second, application of a negative binomial ...
Thomas J. Ostrand, Elaine J. Weyuker
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Predicting and Classifying Software Faults

Proceedings of the 2019 7th International Conference on Computer and Communications Management, 2019
In 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, Shamim H. Ripon
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Class level fault prediction using software clustering

2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2013
Defect prediction approaches use software metrics and fault data to learn which software properties associate with faults in classes. Existing techniques predict fault-prone classes in the same release (intra) or in a subsequent releases (inter) of a subject software system.
Giuseppe Scanniello, GRAVINO, Carmine, Andrian Marcus, Tim Menzies, SCANNIELLO, Giuseppe   +4 more
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Software fault prediction using firefly algorithm

International Journal of Intelligent Engineering Informatics, 2018
The 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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Software fault prediction

Journal of Systems and Software, 1995
Abstract Cost-effective and timely software development methods are essential today as software costs and backlogs escalate while applications are developed in rapidly changing environments. Focusing testing efforts on those portions of the code with the largest number of faults can reduce development costs and time, but requires prediction of the ...
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Software Fault Prediction Process

2018
Accurate detection and early removal of software faults during the software development can reduce the overall cost of software development and can result in the improved software quality product. These inherent advantages of software fault prediction have attracted many researchers to focus on the software fault prediction.
Sandeep Kumar, Santosh Singh Rathore
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