DX 2024
Mon 4 - Thu 7 November 2024 Vienna, Austria

For DX’24, we had 45 submissions in total - 3 for the journal-/major conference-first (JMCF) track, and 42 for the main track. Out of the 3 JMCF papers, 3 (100%) were accepted (one conditional). Out of the 42 main track papers, 39 went into the reviewing process where we finally accepted 18 (42.9%) as full papers and 13 (31%) as short papers (max. 14 pages). 8 papers (20.51%) were rejected in our final decisions.

Please find below preliminary, alphabetically ordered lists of the papers accepted for inclusion in the DX’24 proceedings:

Accepted full papers:

  • A Hierarchical Monitoring and Diagnosis System for Autonomous Robots
    Gerald Steinbauer-Wagner, Leo Fürbaß, Marco De Bortoli and Louise Travé-Massuyès
  • A Model-Based Approach for Monitoring and Diagnosing Digital Twin Discrepancies
    Elaheh Hosseinkhani, Martin Leucker, Martin Sachenbacher, Hendrik Streichhahn and Lars Bernd Vosteen
  • A Review of Fault Diagnosis Techniques Applied to Aircraft Air Data Sensors
    Lucas Gabriel Lima Lopes, Louise Travé-Massuyès, Carine Jauberthie and Guillaume Alcalay
  • A Study on Redundancy and Intrinsic Dimension for Data-Driven Fault Diagnosis
    Daniel Jung and David Axelsson
  • Bridging Hardware and Software Diagnosis: Leveraging Fault Signature Matrix and Spectrum-Based Fault Localization Similarities
    Louise Travé-Massuyès and Franz Wotawa
  • Challenges for Model-Based Diagnosis
    Ingo Pill and Johan de Kleer
  • Design Principles for Falsifiable, Replicable and Reproducible Empirical Machine Learning Research
    Daniel Vranješ, Jonas Ehrhardt, René Heesch, Lukas Moddemann, Henrik Sebastian Steude and Oliver Niggemann
  • Diagnosing Multi-Agent STRIPS Plans
    Avraham Natan, Roni Stern, Meir Kalech, William Yeoh and Tran Cao Son
  • Inferring Sensor Placement Using Critical Pairs and Satisfiability Modulo Theory
    Alexander Diedrich, René Heesch, Marco Bozzano, Björn Ludwig, Alessandro Cimatti and Oliver Niggemann
  • Leveraging Answer Set Programming for Continuous Monitoring, Fault Detection, and Explanation of Automated and Autonomous Driving Systems
    Lorenz Klampfl and Franz Wotawa
  • Leveraging Causal Information for Multivariate Timeseries Anomaly Detection
    Lukas Heppel, Andreas Gerhardus, Ferdinand Rewicki, Jan Deeken and Günther Waxenegger-Wilfing
  • Minimalist Diagnosis of Discrete-Event Systems
    Gianfranco Lamperti and Marina Zanella
  • MSO sets and MTES for dummies
    Maxence Glotin, Louise Travé-Massuyès and Elodie Chanthery
  • One-Class Classification and Cluster Ensembles for Anomaly Detection and Diagnosis in Multivariate Time Series Data
    Adil Mukhtar, Thomas Hirsch and Gerald Schweiger
  • Property Learning-Based Fault Detection for Liquid Propellant Rocket Engine Control Systems
    Andrea Urgolo, Ingo Pill, Günther Waxenegger-Wilfing and Manuel Freiberger
  • Quantifying the Sim-To-Real Gap in UAV Disturbance Rejection
    Austin Coursey, Marcos Quiñones-Grueiro, Luis Alvarez and Gautam Biswas
  • Real-Time Sensor Fault Detection in Drones: A Correlation-Based Algorithmic Approach
    Inbal Roshanski, Magenya Roshanski and Meir Kalech
  • Simulation-Based Diagnosis for Cyber-Physical Systems - A General Approach and Case Study on a Dual Three-Phase E-Machine
    David Kaufmann, Franz Wotawa and Matus Kozovsky

Accepted short papers:

  • Achieving Complete Structural Test Coverage in Embedded Systems using Trace-based Monitoring
    Alexander Weiss, Albert Schulz, Martin Heininger, Martin Sachenbacher, and Martin Leucker
  • Data-Driven Diagnosis of Electrified Vehicles: Results From a Structured Literature Review
    Stan Muñoz Gutiérrez, Adil Mukhtar and Franz Wotawa
  • Data-Driven RUL Prediction Using Performance Metrics
    Abel Diaz-Gonzalez, Austin Coursey, Marcos Quinones-Grueiro, Chetan S. Kulkarni and Gautam Biswas
  • Detecting Soft Faults in Heat Pumps
    Birgit Hofer and Franz Wotawa
  • Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions
    Avraham Natan, Roni Stern and Meir Kalech
  • Faster Diagnosis with Answer Set Programming
    Liliana Marie Prikler and Franz Wotawa
  • FLEX: Fault Localization with Open-Source LLMs in Powertrain Systems
    Herbert Mühlburger and Franz Wotawa
  • Hyperplanes Based Zonotopic Contractor
    Rahma Bengamra, Soheib Fergani and Carine Jauberthie
  • On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis
    Charles-Maxime Gauriat, Yannick Pencolé, Pauline Ribot and Gregory Brouillet
  • Test Selection for Diagnosing Multimode Systems
    Mattias Krysander and Fatemeh Hashemniya
  • Transformer-Based Signal Inference for Electrified Vehicle Powertrains
    Stan Muñoz Gutiérrez, Adil Mukhtar and Franz Wotawa
  • Usability of Symbolic Regression for Hybrid System Identification - System Classes and Parameters
    Swantje Plambeck, Maximilian Schmidt, Audine Subias, Louise Travé-Massuyès and Goerschwin Fey
  • Using Multi-Modal LLMs to Create Models for Fault Diagnosis
    Silke Merkelbach, Alexander Diedrich, Anna Sztyber-Betley, Louise Travé-Massuyès, Elodie Chanthery, Oliver Niggemann and Roman Dumitrescu

Accepted journal-/major conference-first papers (extended abstracts):

  • Summary of A Lazy Approach to Neural Numerical Planning with Control Parameters
    René Heesch, Alessandro Cimatti, Jonas Ehrhardt, Alexander Diedrich and Oliver Niggemann
    The original paper appeared in 27th European Conference on Artificial Intelligence (ECAI 2024)
  • Summary of Randomized Problem-Relaxation Solving for Over-Constrained Schedules
    Patrick Rodler, Erich Teppan and Dietmar Jannach
    The original paper appeared in 18th International Conference on Principles of Knowledge Representation and Reasoning (KR 2021)
  • Summary of Sequence-Oriented Diagnosis of Discrete-Event Systems
    Gianfranco Lamperti, Stefano Trerotola, Marina Zanella and Xiangfu Zhao
    The original paper appeared in Journal of Artificial Intelligence Research (JAIR), 78, 69-141, 2023