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API recommendation for machine learning libraries: how far are we?

, , , , , and . ESEC/SIGSOFT FSE, page 370-381. ACM, (2022)

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Benchmarking Deep Learning Fuzzers., , and . CoRR, (2023)An Empirical Study on the Stability of Explainable Software Defect Prediction., , , , , and . APSEC, page 141-150. IEEE, (2023)Relaxing Pairwise Conditional Dependency of NB Attributes using Hidden Variables., , , and . IST, page 116-122. IEEE, (2020)Demystifying and Detecting Misuses of Deep Learning APIs., , , , , and . ICSE, page 201:1-201:12. ACM, (2024)Effectiveness of ChatGPT for Static Analysis: How Far Are We?, , , , , , and . AIware, ACM, (2024)Automatic Static Vulnerability Detection for Machine Learning Libraries: Are We There Yet?, , , , and . ISSRE, page 795-806. IEEE, (2023)API recommendation for machine learning libraries: how far are we?, , , , , and . ESEC/SIGSOFT FSE, page 370-381. ACM, (2022)Fairness Analysis of Machine Learning-Based Code Reviewer Recommendation., , , , , , and . BIAS, volume 2227 of Communications in Computer and Information Science, page 46-63. Springer, (2024)SkipAnalyzer: An Embodied Agent for Code Analysis with Large Language Models., , , , , , and . CoRR, (2023)Analysis and modeling conditional mutual dependency of metrics in software defect prediction using latent variables., and . Neurocomputing, (2021)