@InProceedings{amalou_et_al:LIPIcs.ECRTS.2023.7, author = {Amalou, Abderaouf N and Fromont, Elisa and Puaut, Isabelle}, title = {{CAWET: Context-Aware Worst-Case Execution Time Estimation Using Transformers}}, booktitle = {35th Euromicro Conference on Real-Time Systems (ECRTS 2023)}, pages = {7:1--7:20}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-280-8}, ISSN = {1868-8969}, year = {2023}, volume = {262}, editor = {Papadopoulos, Alessandro V.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2023.7}, URN = {urn:nbn:de:0030-drops-180367}, doi = {10.4230/LIPIcs.ECRTS.2023.7}, annote = {Keywords: Worst-case execution time, machine learning, transformers, hybrid technique} }