AI-Based Software Defect Prediction for Trustworthy Android Apps
Author:
Affiliation:
1. Computer Science, COMSATS University, Pakistan
2. Department of Computer Science, Masaryk University, Czech Republic
3. Computer Science, Masaryk University, Czech Republic
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3530019.3531330
Reference34 articles.
1. Saiqa Aleem Luiz Fernando Capretz and Faheem Ahmed. 2015. Benchmarking machine learning technologies for software defect detection. arXiv preprint arXiv:1506.07563(2015). Saiqa Aleem Luiz Fernando Capretz and Faheem Ahmed. 2015. Benchmarking machine learning technologies for software defect detection. arXiv preprint arXiv:1506.07563(2015).
2. A Novel Approach to Detect Android Malware
3. Predicting defective modules in different test phases
4. Multiview Transfer Learning for Software Defect Prediction
5. Negative samples reduction in cross-company software defects prediction
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1. Multi‐task deep neural networks for just‐in‐time software defect prediction on mobile apps;Concurrency and Computation: Practice and Experience;2023-02-23
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