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A Lock Contention Classifier Based on Java Lock Contention Anti-Patterns., , , , , и . ICMLA, стр. 1106-1113. IEEE, (2023)Hands-on workshop on fast, efficient & seriously open cloud-native Java., , , , , и . CASCON, стр. 373-375. ACM, (2019)Identification of Java lock contention anti-patterns based on run-time performance data., , , , и . AST@ICSE, стр. 209-213. ACM, (2024)Supporting SIP Port Mapping and RTP Affinity Constraints in Container Orchestration Environments., , , , , , и . ICIN, стр. 13-19. IEEE, (2021)Failure Prediction using Transfer Learning in Large-scale Continuous Integration Environments., , , , , , и . CASCON, стр. 193-198. ACM, (2022)Failure Scenarios for SIP/RTP services in Container Orchestration Clusters., , , , , и . ISNCC, стр. 1-6. IEEE, (2020)Lock Contention Performance Classification for Java Intrinsic Locks., , , , , и . RV, том 13498 из Lecture Notes in Computer Science, стр. 274-282. Springer, (2022)Building microservices in a cloud-native world using eclipse microprofile and open liberty., , , и . CASCON, стр. 350-353. ACM, (2018)Mining Annotation Usage Rules: A Case Study with MicroProfile., , , , , и . ICSME, стр. 553-562. IEEE, (2022)A Human-in-the-loop Approach to Generate Annotation Usage Rules., , , , , и . CASCON, стр. 91-100. ACM, (2022)