International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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A Comprehensive Study on Ensemble Methods for Software Error Detection

Author(s) Nagib Mahfuz, Md. Mahedi Hasan
Country Bangladesh
Abstract Software Developers often find it painful and tedious to locate or pinpoint the errors that reside in the source code which causes serious hindrance in the progression of developing any software. In the field of software engineering, it is very crucial to understand the software metrics that are directly involved with the progression of the software. Besides, various classification algorithms have been used to foresee the errors in building the software. In this paper, we focus especially on ensemble algorithms as they tend to provide more precise and statistically efficient outcomes than the other traditional algorithms. This paper contains twenty software metrics that are pivotal in identifying errors in software applications. Eight Java projects have been gathered to showcase the significance of the software metrics in predicting errors. In this study, three ensemble methods are considered, MultiBoostAB, Dagging, and Decorate. For a detailed inspection of the performance, accuracy, recall, precision, F-measure, and ROC Curve were appraised. The comparisons exhibit Decorate as the highest-performing method and Dagging as the lowest.
Keywords Ensemble, Software Metrics, Software Error Detection
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-14
Cite This A Comprehensive Study on Ensemble Methods for Software Error Detection - Nagib Mahfuz, Md. Mahedi Hasan - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16105
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.16105
Short DOI https://doi.org/gtqx28
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