Tim A. C. Willemse
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Tim A. C. Willemse has a total of 193 co-authors. Here are the top co-authors by number of shared publications:
- Jeroen J. A. Keiren
Eindhoven University of Technology
16 shared publications - Jan Friso Groote
Eindhoven University of Technology
15 shared publications - Maurice Laveaux
Eindhoven University of Technology
9 shared publications Sjoerd Cranen
Eindhoven University of Technology, Eindhoven, The Netherlands
6 shared publications- Thomas Neele
Eindhoven University of Technology The Netherlands
6 shared publications Daniela Remenska
VU University Amsterdam
5 shared publications
Latest Publications
- 6 November 2026
- Published by Springer Nature
- p. 536-556
Explaining Access Control Through Causal Reasoning
- 6 November 2026
- Published by Springer Nature
- p. 536-556
Explaining Access Control Through Causal Reasoning
- 30 August 2026
- Published by Springer Nature
- p. 389-409
Verification of Parametric Markov Automata Under Time-Bounded Reachability
- 30 August 2026
- Published by Springer Nature
- p. 389-409
Verification of Parametric Markov Automata Under Time-Bounded Reachability
- Open Access
- 8 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 149-155
A Causal Framework for Explainable Access Control: [Work in Progress Paper]
- 8 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 149-155
Open AccessA Causal Framework for Explainable Access Control: [Work in Progress Paper]
- Open Access
- 3 July 2026
- Published by Springer Nature in Software and Systems Modeling
- Vol. 25 (4) , 1-2
Guest editorial for the special section on SEFM 2023
- 3 July 2026
- Published by Springer Nature in Software and Systems Modeling
- Vol. 25 (4) , 1-2
Open AccessGuest editorial for the special section on SEFM 2023
- 11 June 2026
- Published by Springer Nature
- p. 38-55
Control Flow-Based Symmetry Reduction for Parameterised Boolean Equation Systems
- 11 June 2026
- Published by Springer Nature
- p. 38-55
Control Flow-Based Symmetry Reduction for Parameterised Boolean Equation Systems
- 1 June 2026
- Published by Springer Nature
- p. 87-108
Constructing Weakly Terminating Interface Protocols
- 17 March 2026
- Published by Springer Nature
- p. 141-159
Deciding Impossible Futures
- Open Access
- 22 October 2025
- Published by Springer Nature in International Journal on Software Tools for Technology Transfer
- Vol. 27 (5) , 511-532
Formalising and analysing SMMT models using the mCRL2 toolset
The proprietary State Machine Modelling Tool (SMMT), developed and maintained at Canon Production Printing, can be used to model software components using state machines and generate executable production code. We provide an operational semantics of the language supported by SMMT, derived from already existing code generators and discussions with engineers. By subsequently formalising this operational semantics in the mCRL2 language, we unlock the ability to apply formal verification to SMMT models during their design using the mCRL2 toolset. Using the mCRL2 formalisation, we have found various subtle bugs in the implementation of the SMMT tool, affecting its correctness, and proposed fixes for SMMT.
- 22 October 2025
- Published by Springer Nature in International Journal on Software Tools for Technology Transfer
- Vol. 27 (5) , 511-532
Open AccessFormalising and analysing SMMT models using the mCRL2 toolset
The proprietary State Machine Modelling Tool (SMMT), developed and maintained at Canon Production Printing, can be used to model software components using state machines and generate executable production code. We provide an operational semantics of the language supported by SMMT, derived from already existing code generators and discussions with engineers. By subsequently formalising this operational semantics in the mCRL2 language, we unlock the ability to apply formal verification to SMMT models during their design using the mCRL2 toolset. Using the mCRL2 formalisation, we have found various subtle bugs in the implementation of the SMMT tool, affecting its correctness, and proposed fixes for SMMT.
- Open Access
- 1 May 2025
- Published by Springer Nature
- p. 191-210
Efficient Evidence Generation for Modal $\mu $-Calculus Model CheckingModel checking is a technique to automatically establish whether a model of the behaviour of a system meets its requirements. Evidence explaining why the behaviour does (not) meet its requirements is essential for the user to understand the model checking result. Willemse and Wesselink showed that parameterised Boolean equation systems (PBESs), an intermediate format for $$\mu $$ -calculus model checking, can be extended with information to generate such evidence. Solving the resulting PBES is much slower than solving one without additional information, and sometimes even impossible. In this paper we develop a two-step approach to solving a PBES with additional information: we first solve its core and subsequently use the information obtained in this step to solve the PBES with additional information. We prove the correctness of our approach and we have implemented it, demonstrating that it efficiently generates evidence using both explicit and symbolic solving techniques.- 1 May 2025
- Published by Springer Nature
- p. 191-210
Open AccessEfficient Evidence Generation for Modal $\mu $-Calculus Model CheckingModel checking is a technique to automatically establish whether a model of the behaviour of a system meets its requirements. Evidence explaining why the behaviour does (not) meet its requirements is essential for the user to understand the model checking result. Willemse and Wesselink showed that parameterised Boolean equation systems (PBESs), an intermediate format for $$\mu $$ -calculus model checking, can be extended with information to generate such evidence. Solving the resulting PBES is much slower than solving one without additional information, and sometimes even impossible. In this paper we develop a two-step approach to solving a PBES with additional information: we first solve its core and subsequently use the information obtained in this step to solve the PBES with additional information. We prove the correctness of our approach and we have implemented it, demonstrating that it efficiently generates evidence using both explicit and symbolic solving techniques. - Open Access
Efficient Evidence Generation for Modal $μ$-Calculus Model Checking (extended version)
Model checking is a technique to automatically assess whether a model of the behaviour of a system meets its requirements. Evidence explaining why the behaviour does (not) meet its requirements is essential for the user to understand the model checking result. Willemse and Wesselink showed that parameterised Boolean equation systems (PBESs), an intermediate format for $μ$-calculus model checking, can be extended with information to generate such evidence. Solving the resulting PBES is much slower than solving one without additional information, and sometimes even impossible. In this paper we develop a two-step approach to solving a PBES with additional information: we first solve its core and subsequently use the information obtained in this step to solve the PBES with additional information. We prove the correctness of our approach and we have implemented it, demonstrating that it efficiently generates evidence using both explicit and symbolic solving techniques.
Open AccessEfficient Evidence Generation for Modal $μ$-Calculus Model Checking (extended version)
Model checking is a technique to automatically assess whether a model of the behaviour of a system meets its requirements. Evidence explaining why the behaviour does (not) meet its requirements is essential for the user to understand the model checking result. Willemse and Wesselink showed that parameterised Boolean equation systems (PBESs), an intermediate format for $μ$-calculus model checking, can be extended with information to generate such evidence. Solving the resulting PBES is much slower than solving one without additional information, and sometimes even impossible. In this paper we develop a two-step approach to solving a PBES with additional information: we first solve its core and subsequently use the information obtained in this step to solve the PBES with additional information. We prove the correctness of our approach and we have implemented it, demonstrating that it efficiently generates evidence using both explicit and symbolic solving techniques.