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Nachtigall, Marcus, et al. “Evaluation of Usability Criteria Addressed by Static Analysis Tools on a Large Scale.” Software Engineering 2023, Gesellschaft für Informatik e.V., 2023, pp. 95–96.
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Schlichtig, Michael, et al. “Introducing FUM: A Framework for API Usage Constraint and Misuse Classification.” Software Engineering 2023, Gesellschaft für Informatik e.V., 2023, pp. 105–106.
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Schlichtig, Michael, et al. CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite. 2022, doi:10.48550/ARXIV.2204.06447.
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Nachtigall, Marcus, et al. “A Large-Scale Study of Usability Criteria Addressed by Static Analysis Tools.”10.1145/3533767__Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis, ACM, 2022, pp. 532–43, doi:10.1145/3533767.
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Schlichtig, Michael, et al. “FUM - A Framework for API Usage Constraint and Misuse Classification.”https://doi.org/10.1109/SANER53432.2022.00085__2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2022, pp. 673–84, doi:https://doi.org/10.1109/SANER53432.2022.00085.
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Wickert, Anna-Katharina, et al. To Fix or Not to Fix: A Critical Study of Crypto-Misuses in the Wild. 2022, doi:10.48550/ARXIV.2209.11103.
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Opel, Simone Anna, and Michael Schlichtig. “Data Science und Big Data in der beruflichen Bildung – Konzeption und Erprobung eines Projektkurses für die Sekundarstufe II.”https://doi.org/10.3278/6004722w__Sammelband der 27. Fachtagung der BAG Berufliche Bildung, edited by Thomas Vollmer et al., vol. 55, wbv Media GmbH &; Co. KG, 2020, pp. 176–94, doi:https://doi.org/10.3278/6004722w.
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Schlichtig, Michael, et al. “Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material.” ISSEP 2019 - 12th International Conference on Informatics in Schools: Situation, Evaluation and Perspectives, Local Proceedings, edited by Egl Jasut and Sergei Pozdniakov, vol. 12, 2019, pp. 65–73.
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Opel, Simone Anna, et al. “Entwicklung und Reflexion einer Unterrichtssequenz zum Maschinellen Lernen als Aspekt von Data Science in der Sekundarstufe II.” INFOS, vol. P-288, Gesellschaft für Informatik, 2019, pp. 285–94.
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Schlichtig, Michael, et al. “Maschinelles Lernen im Unterricht mit Jupyter Notebook.” INFOS, vol. P-288, Gesellschaft für Informatik, 2019, p. 385.
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Opel, Simone Anna, et al. “Developing Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress).” WiPSCE, ACM, 2019, p. 11:1-11:2.
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Bemmann, Kai, et al. “Fully-Featured Anonymous Credentials with Reputation System.”10.1145/3230833.3234517__Proceedings of the 13th International Conference on Availability, Reliability and Security - ARES ’18, ACM, doi:10.1145/3230833.3234517.
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