### Abstract

Model checking is a technique for automatically assessing the quality of software and hardware systems and designs. Given a formalisation of both the system behaviour and the requirements the system should meet, a model checker returns either a yes or a no. In case the answer is not as expected, it is desirable to provide feedback to the user as to why this is the case. Providing such feedback, however, is not straightforward if the requirement is expressed in a highly expressive logic such as the modal µ-calculus, and when the decision problem is solved using intermediate formalisms. In this paper, we show how to extract witnesses and counterexamples from parameterised Boolean equation systems encoding the model checking problem for the first-order modal µ-calculus. We have implemented our technique in the modelling and analysis toolset mCRL2 and showcase our approach on a few illustrative examples.

Language | English |
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Title of host publication | Proceedings of the 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics (ARQNL 2018) |

Subtitle of host publication | Oxford, UK, July 18, 2018. |

Editors | Christoph Benzmüller, Jens Otten |

Publisher | CEUR-WS.org |

Pages | 86-100 |

Number of pages | 15 |

State | Published - 1 Jan 2018 |

Event | 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics, (ARQNL 2018) - Oxford, United Kingdom Duration: 18 Jul 2018 → 18 Jul 2018 http://ceur-ws.org/Vol-2095/ |

### Publication series

Name | CEUR Workshop Proceedings |
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Volume | 2095 |

ISSN (Print) | 1613-0073 |

### Conference

Conference | 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics, (ARQNL 2018) |
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Abbreviated title | ARQNL2018 |

Country | United Kingdom |

City | Oxford |

Period | 18/07/18 → 18/07/18 |

Internet address |

### Fingerprint

### Cite this

*Proceedings of the 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics (ARQNL 2018): Oxford, UK, July 18, 2018.*(pp. 86-100). (CEUR Workshop Proceedings; Vol. 2095). CEUR-WS.org.

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*Proceedings of the 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics (ARQNL 2018): Oxford, UK, July 18, 2018..*CEUR Workshop Proceedings, vol. 2095, CEUR-WS.org, pp. 86-100, 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics, (ARQNL 2018), Oxford, United Kingdom, 18/07/18.

**Evidence extraction from parameterised Boolean equation systems.** / Wesselink, Wieger; Willemse, Tim A.C.

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

TY - GEN

T1 - Evidence extraction from parameterised Boolean equation systems

AU - Wesselink,Wieger

AU - Willemse,Tim A.C.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Model checking is a technique for automatically assessing the quality of software and hardware systems and designs. Given a formalisation of both the system behaviour and the requirements the system should meet, a model checker returns either a yes or a no. In case the answer is not as expected, it is desirable to provide feedback to the user as to why this is the case. Providing such feedback, however, is not straightforward if the requirement is expressed in a highly expressive logic such as the modal µ-calculus, and when the decision problem is solved using intermediate formalisms. In this paper, we show how to extract witnesses and counterexamples from parameterised Boolean equation systems encoding the model checking problem for the first-order modal µ-calculus. We have implemented our technique in the modelling and analysis toolset mCRL2 and showcase our approach on a few illustrative examples.

AB - Model checking is a technique for automatically assessing the quality of software and hardware systems and designs. Given a formalisation of both the system behaviour and the requirements the system should meet, a model checker returns either a yes or a no. In case the answer is not as expected, it is desirable to provide feedback to the user as to why this is the case. Providing such feedback, however, is not straightforward if the requirement is expressed in a highly expressive logic such as the modal µ-calculus, and when the decision problem is solved using intermediate formalisms. In this paper, we show how to extract witnesses and counterexamples from parameterised Boolean equation systems encoding the model checking problem for the first-order modal µ-calculus. We have implemented our technique in the modelling and analysis toolset mCRL2 and showcase our approach on a few illustrative examples.

UR - http://www.scopus.com/inward/record.url?scp=85049752576&partnerID=8YFLogxK

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

SP - 86

EP - 100

BT - Proceedings of the 3rd International Workshop on Automated Reasoning in Quantified Non-Classical Logics (ARQNL 2018)

PB - CEUR-WS.org

ER -