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A High Quality Data Pipeline for Reasonable-Scale Machine Learning.

. Softwaretechnik-Trends, 42 (4): 18-23 (2022)

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Correctness of Sensor Network Applications by Software Bounded Model Checking, and . Formal Methods for Industrial Critical Systems - 15th International Workshop, FMICS 2010, Antwerp, Belgium, September 20-21, 2010. Proceedings, page 115--131. Springer, (2010)Improving Non-Progress Cycle Checks, and . Model Checking Software, 16th International SPIN Workshop, Grenoble, France, June 26-28, 2009. Proceedings, page 50-67. Springer, (June 2009)Model-based Testing in Agile Software Development. 30. Treffen der GI-Fachgruppe Test, Analyse & Verifikation von Software (TAV), (2010)A Full-fledged Commit Message Quality Checker Based on Machine Learning., , and . COMPSAC, page 788-799. IEEE, (2023)TAV-2021: Herausforderungen beim Testen moderner Softwaresysteme., , , , , and . GI-Jahrestagung, volume P-314 of LNI, page 1809-1812. Gesellschaft für Informatik, Bonn, (2021)Wirtschaftlichkeitsberechnung für MBT: Wann sich modellbasiertes Testen lohnt, , , , , and . OBJEKTspektrum, (2013)Keynote: Microservices Testen - Erfahrungsbericht und Umfrage., and . Softwaretechnik-Trends, 40 (2): 50-53 (2020)A High Quality Data Pipeline for Reasonable-Scale Machine Learning.. Softwaretechnik-Trends, 42 (4): 18-23 (2022)Improved Underspecification for Model-based Testing in Agile Development.. FM+AM, volume P-179 of LNI, page 63-78. GI, (2010)Only diff Is Not Enough: Generating Commit Messages Leveraging Reasoning and Action of Large Language Model., , , and . Proc. ACM Softw. Eng., 1 (FSE): 745-766 (2024)