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Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study., , , , and . CoRR, (2023)Bug characterization in machine learning-based systems., , , , and . Empir. Softw. Eng., 29 (1): 14 (February 2024)Faults in deep reinforcement learning programs: a taxonomy and a detection approach., , , and . Autom. Softw. Eng., 29 (1): 8 (2022)Bugs in machine learning-based systems: a faultload benchmark., , , and . Empir. Softw. Eng., 28 (3): 62 (June 2023)Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach., , , and . CoRR, (2021)Automatic Fault Detection for Deep Learning Programs Using Graph Transformations., , , and . CoRR, (2021)Automatic Fault Detection for Deep Learning Programs Using Graph Transformations., , , and . ACM Trans. Softw. Eng. Methodol., 31 (1): 14:1-14:27 (2022)Bug Characterization in Machine Learning-based Systems., , , , and . CoRR, (2023)Technical debts and faults in open-source quantum software systems: An empirical study., , , , and . J. Syst. Softw., (2022)Bugs in Machine Learning-based Systems: A Faultload Benchmark., , , and . CoRR, (2022)