Exploring Perspectives, Issues, and Practices in the Testing and Quality Validation of AI Software

Jukaria, Mukta; Husain, Saif O.; Muhsin, Enas; Jaafar, Abdul Hassan Majli; Hussein, Laith; Ali, Sajjad; SaadAlwan, Ali

doi:10.1109/icacite60783.2024.10617318

2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) 2024

DOI: 10.1109/icacite60783.2024.10617318

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Exploring Perspectives, Issues, and Practices in the Testing and Quality Validation of AI Software

Mukta Jukaria,

Saif O. Husain,

Enas Muhsin

et al.

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Evaluating Quality of Software Systems by the Confidence and Prediction Intervals of Regressions for RFC, CBO and WMC Metrics

Prykhodko

2024

Wseas Transactions on Systems

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We have proposed to apply the confidence and prediction intervals of nonlinear regressions for the metrics RFC, CBO, and WMC at the app level to evaluate the quality of software systems from the point of view of their object-oriented design (OOD). A modified technique for evaluating the quality of software systems has been introduced. We have given the example of using the modified technique to detect the software quality of open-source Java systems.

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Evaluating Quality of Software Systems by the Confidence and Prediction Intervals of Regressions for RFC, CBO and WMC Metrics

Prykhodko

2024

Wseas Transactions on Systems

View full text Add to dashboard Cite

show abstract

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Exploring Perspectives, Issues, and Practices in the Testing and Quality Validation of AI Software

Cited by 1 publication

References 30 publications

Evaluating Quality of Software Systems by the Confidence and Prediction Intervals of Regressions for RFC, CBO and WMC Metrics

Evaluating Quality of Software Systems by the Confidence and Prediction Intervals of Regressions for RFC, CBO and WMC Metrics

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