# High-Level Counterexamples for Probabilistic Automata

@inproceedings{Wimmer2013HighLevelCF, title={High-Level Counterexamples for Probabilistic Automata}, author={Ralf Wimmer and N. Jansen and Andreas Vorpahl and Erika {\'A}brah{\'a}m and Joost-Pieter Katoen and Bernd Becker}, booktitle={International Conference on Quantitative Evaluation of Systems}, year={2013} }

Providing compact and understandable counterexamples for violated system properties is an essential task in model checking. Existing works on counterexamples for probabilistic systems so far computed either a large set of system runs or a subset of the system's states, both of which are of limited use in manual debugging. Many probabilistic systems are described in a guarded command language like the one used by the popular model checker PRISM. In this paper we describe how a minimal subset of…

## 35 Citations

### HIGH-LEVEL COUNTEREXAMPLES

- Computer Science
- 2015

This paper describes how a smallest possible subset of the commands can be identified which together make the system erroneous and shows how the selected commands can been further simplified to obtain a well-understandable counterexample.

### Fast Debugging of PRISM Models

- Computer ScienceATVA
- 2014

This work's novel approach to computing a minimal critical command set achieves a speed-up of up to five orders of magnitude over the previously existing technique.

### Counterexample Generation for Discrete-Time Markov Models: An Introductory Survey

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- 2014

This paper is an introductory survey of available methods for the computation and representation of probabilistic counterexamples for discrete-time Markov chains and Probabilistic automata, using explicit and symbolic techniques.

### Counterexamples in Model Checking - A survey

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Algorithms for counterexample generation are surveyed, from classical algorithms in graph theory to novel algorithms for producing small and indicative countserexamples, and how they can benefit from delivering countereXamples for other purposes.

### Bounded Model Checking for Probabilistic Programs

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This paper proposes an on–the–fly approach where the operational model is successively created and verified via a step–wise execution of the program, enabling to take key features of many probabilistic programs into account: nondeterminism and conditioning.

### Counterexample-Driven Synthesis for Probabilistic Program Sketches

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This work adopts counterexample-guided inductive synthesis (CEGIS) to automatically synthesise finite-state probabilistic programs to deal with uncertainty in e.g. controller synthesis.

### The probabilistic model checker Storm: symbolic methods for probabilistic model checking

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The JANI modeling language is proposed to unify the multitude of input languages of probabilistic model checkers and is shown to drastically reduce the sizes of models involving probabilities, continuous time, nondeterminism and rewards.

### Debugging of Markov Decision Processes (MDPs) Models

- Computer ScienceCREST@ETAPS
- 2016

This paper proposes an aided-diagnostic method for probabilistic counterexamples based on the notions of causality, responsibility and blame for Markov Decision Processes (MDPs).

### Minimal witnesses for probabilistic timed automata

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Using a new operation on difference bounds matrices, it is shown how Farkas certificates of finite-state bisimulation quotients of a PTA can be translated into witnessing subsystems.

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