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DRE: density-based data selection with entropy for adversarial-robust deep learning models., , , , и . Neural Comput. Appl., 35 (5): 4009-4026 (февраля 2023)Learning To Predict Vulnerabilities From Vulnerability-Fixes: A Machine Translation Approach., , , , , и . CoRR, (2020)Test Selection for Deep Learning Systems., , , , и . ACM Trans. Softw. Eng. Methodol., 30 (2): 13:1-13:22 (2021)What You See is What it Means! Semantic Representation Learning of Code based on Visualization and Transfer Learning., , , , и . CoRR, (2020)Requirements by Contracts allow Automated System Testing, , , и . ISSRE '03: Proceedings of the 14th International Symposium on Software Reliability Engineering, стр. 85. Washington, DC, USA, IEEE Computer Society, (2003)Bottom-Up Technologies for Reuse: A Framework to Support Extractive Software Product Line Adoption Activities., , , , и . Handbook of Re-Engineering Software Intensive Systems into Software Product Lines, Springer International Publishing, (2023)Smart discovery of periodic-frequent human routines for home automation., , , и . MobiQuitous, стр. 268-277. ACM, (2019)Popularity-Driven Ontology Ranking Using Qualitative Features., , и . ISWC (1), том 11778 из Lecture Notes in Computer Science, стр. 329-346. Springer, (2019)LOVBench: Ontology Ranking Benchmark., , , и . WWW, стр. 1750-1760. ACM / IW3C2, (2020)Confuzzion: A Java Virtual Machine Fuzzer for Type Confusion Vulnerabilities., , , , и . QRS, стр. 586-597. IEEE, (2021)