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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

4. Software Fault Dataset

verfasst von : Sandeep Kumar, Santosh Singh Rathore

Erschienen in: Software Fault Prediction

Verlag: Springer Singapore

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Abstract

Machine learning and statistical techniques are used in software fault prediction to predict the presence or the absence of faults in the given software modules. In order to make the predictions, a software fault prediction learns upon the software fault data having the information about the software system (software metrics) augmented with the fault value. An implicit requirement to perform effective software fault prediction is the availability of reasonable quality fault data. However, obtaining quality software fault data is difficult as in general software development companies are not keen to share their software development information or they are not having any software repository in first place.

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Vorheriges Kapitel Types of Software Fault Prediction
Nächstes Kapitel Evaluation of Techniques for Binary Class Classification
Fußnoten
1
Understand for Java, https://​scitools.​com/​.
 
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Metadaten
Titel
Software Fault Dataset
verfasst von
Sandeep Kumar
Santosh Singh Rathore
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Software Fault Prediction

Print ISBN: 978-981-10-8714-1

Electronic ISBN: 978-981-10-8715-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-8715-8_4