Apr 22, 2021 · In this work, we propose a novel Imbalanced Deep Learning model, called IDL, to conduct JIT defect prediction task for Android mobile apps.
[PDF] Just-in-Time Defect Prediction for Android Apps via ... - Meng Yan's
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We conduct experiments on a benchmark defect data consisting of 12 Android mobile apps. The results of rigorous exper- iments show that our proposed IDL model ...
We conduct experiments on a benchmark defect data consisting of 12 Android mobile apps. The results of rigorous experiments show that our proposed IDL model ...
Mar 26, 2021 · In this work, we propose a novel. Imbalanced Deep Learning model, called IDL, to conduct JIT defect prediction task for Android mobile apps.
Dec 12, 2023 · ... Zhao et al. presented a deep learningbased model for just-in-time defect prediction of Android applications. They applied their proposed ...
Jun 9, 2023 · (2021b) proposed an imbalanced DL (IDL) methodology for JIT defect prediction in Android applications through applying a cost-sensitive cross ...
Just-In-Time ... Time Defect Prediction for Mobile Applications: Using Shallow or Deep Learning? ... DefectDataset is a PyTorch data object used by the MLP model.
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Jun 9, 2023 · This study indicates that DL-based models are not always the optimal solution for software defect prediction, and thus, shallow, traditional ...
May 8, 2024 · Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time. Hence, developers can take precautions to avoid defects ...
Jun 9, 2023 · This study indicates that DL-based models are not always the optimal solution for software defect prediction, and thus, shallow, traditional ...
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