Abstract
Depending upon the type of fault prediction model, a model can be used to classify software modules into faulty or non-faulty categories or a model can be used to predict the number of faults in the given software system. The former approach is known as the binary class classification of software faults. In this type of prediction , if a given software module has one or more faults, then it is classified as faulty; otherwise, it is classified as non-faulty. Most the studies available in the literature related to the software fault prediction have focused on the binary class classification of software faults.
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Kumar, S., Rathore, S.S. (2018). Evaluation of Techniques for Binary Class Classification. In: Software Fault Prediction. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-8715-8_5
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DOI: https://doi.org/10.1007/978-981-10-8715-8_5
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