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A Search-Based Testing Approach for Deep Reinforcement Learning Agents., , , , and . IEEE Trans. Software Eng., 49 (7): 3715-3735 (July 2023)An observational study on the state of REST API uses in Android mobile applications., , , , , and . MOBILESoft@ICSE, page 66-75. IEEE / ACM, (2019)Safety Monitoring of Deep Reinforcement Learning Agents., , , and . ICSE Companion, page 286-287. ACM, (2024)Formalising Solutions to REST API Practices as Design (Anti)Patterns., , and . ICSOC, volume 13121 of Lecture Notes in Computer Science, page 153-170. Springer, (2021)Codifying Hidden Dependencies in Legacy J2EE Applications., , , , , , , , and . APSEC, page 305-314. IEEE, (2018)DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks., , , and . ACM Trans. Softw. Eng. Methodol., 33 (6): 158 (July 2024)A Type-Sensitive Service Identification Approach for Legacy-to-SOA Migration., , , , , , and . ICSOC, volume 12571 of Lecture Notes in Computer Science, page 476-491. Springer, (2020)Collection and Identification Of Microservices Patterns And Antipatterns., , , , and . CAL, volume L-9 of RNTI, page 1-8. Éditions RNTI, (2019)On the Use of Mobile GPU for Accelerating Malware Detection Using Trace Analysis., , , and . SRDS Workshop, page 42-46. IEEE Computer Society, (2015)Black-Box Testing of Deep Neural Networks through Test Case Diversity., , , , and . IEEE Trans. Software Eng., 49 (5): 3182-3204 (2023)