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FATE - Fault-driven Analysis and Testing for Design Robustness and Stability

Project: Research project

Project Details

Description

The main objective of FATE is to provide a human-centred verification approach for cyber-physical systems that will reduce testing effort while increasing coverage. To achieve this goal, the project will leverage recent advances in machine learning, formal methods and technology experience to develop effective and user-friendly methods to reason about correctness and robustness of complex systems during different phases of their development. The project results will contribute to the safety and robustness of cyber-physical applications and will significantly reduce the field returns in the semiconductor industry to faulty chips delivered to customers, while increasing the competitivity of the Austrian semiconductor industry in the light of the EU Chip Act vision.
StatusFinished
Effective start/end date1/11/22 → 31/10/25

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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
  • Parameterized Infinite-State Reactive Synthesis

    Maderbacher, B. & Bloem, R., 8 Jan 2026, In: Proceedings of the ACM on Programming Languages. 10, POPL, p. 2439-2467 29 p.

    Research output: Contribution to journal › Article › peer-review

    Open Access
  • An Adaptive, Provable Correct Simplex Architecture

    Maderbacher, B., Schupp, S., Bartocci, E., Bloem, R., Nickovic, D. & Könighofer, B., 4 Feb 2025, (E-pub ahead of print) In: International Journal on Software Tools for Technology Transfer. SPIN 2022-2024, 19 p., 2589.

    Research output: Contribution to journal › Article › peer-review

    Open Access
    File
  • Synthesis of Controllers for Continuous Blackbox Systems

    Maderbacher, B., Windisch, F., Larrauri Borroto, L. A. & Bloem, R., Jan 2025, Verification, Model Checking, and Abstract Interpretation - 26th International Conference, VMCAI 2025, Proceedings. Shankaranarayanan, K., Sankaranarayanan, S. & Trivedi, A. (eds.). Springer, Cham, Vol. 2. p. 137–159 23 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15530 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

    Open Access
    File