2026-07-23T19:07:48Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:24803 2026-02-09T07:47:34Z ddc:004 open_access

The DX Competition 2025 and Its Benchmarks (DX Competition) Pill, Ingo Jung, Daniel Kurudzija, Eldin Sztyber-Betley, Anna Syfert, Michał Dresia, Kai Waxenegger-Wilfing, Günther de Kleer, Johan Diagnosis Algorithms Evaluation Fault diagnosis has been addressed in many research communities, leading to a variety of available fault diagnosis techniques. Deciding as a user which fault diagnosis methods are suitable for a specific application is thus a nontrivial task. Benchmarks can provide the community with a holistic understanding of the landscape of newly developed and available fault diagnosis methods when making this decision. After a long hiatus, we revived the DX Competition with three fault diagnosis benchmarks: SLIDe, LUMEN, and LiU-ICE. The purpose of the benchmarks is to inspire fault diagnosis research with challenging problems in cyber-physical systems relevant for industry. The benchmarks share a common code structure and we used similar performance metrics in order to simplify the adaptation of diagnosis system solutions to the different case studies. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ingo Pill and Daniel Jung and Eldin Kurudzija and Anna Sztyber-Betley and Michał Syfert and Kai Dresia and Günther Waxenegger-Wilfing and Johan de Kleer 2025 Is Part Of OASIcs, Volume 136, 36th International Conference on Principles of Diagnosis and Resilient Systems (DX 2025) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.DX.2025.14 urn:nbn:de:0030-drops-248030 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.DX.2025.14 eng https://creativecommons.org/licenses/by/4.0/legalcode