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An Empirical Study of Classification Models Using AUC-ROC Curve for Software Fault Predictions

Authors :
null Mrs. Prachi Sasankar
null Dr. Gopal Sakarkar
Source :
International Journal of Scientific Research in Computer Science, Engineering and Information Technology. :250-260
Publication Year :
2023
Publisher :
Technoscience Academy, 2023.

Abstract

Software bug prediction is the process of identifying software modules that are likely to have bugs by using some fundamental project resources before the real testing starts. Due to high cost in correcting the detected bugs, it is advisable to start predicting bugs at the early stage of development instead of at the testing phase. There are many techniques and approaches that can be used to build the prediction models, such as machine learning. We have studied nine different types of datasets and seven types of machine learning techniques have been identified. As for performance measures, both graphical and numerical measures are used to evaluate the performance of models. A few challenges exist when constructing a prediction model. In this study, we have narrowed down to nine different types of datasets and seven types of machine learning techniques have been identified. As for the performance measure, both graphical and numerical measures are used to evaluate the performance of the models. There are a few challenges in constructing the prediction model. Thus, more studies need to be carried out so that a well-formed result is obtained. We also provide a recommendation for future research based on the results we got from this study.

Subjects

Subjects :
Pharmacology

Details

ISSN :
24563307
Database :
OpenAIRE
Journal :
International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Accession number :
edsair.doi...........88387258cb0729ebb9081348e5a0a021
Full Text :
https://doi.org/10.32628/cseit2390143