### Resumé

processes of society. Errors in these embedded systems can lead to human

casualties or severe monetary loss. Model checking technology has proven

formal methods capable of finding and correcting errors in software. However,

software is approaching the boundary in terms of the complexity and size that

model checking can handle. Furthermore, software systems are nowadays more

frequently interacting with their environment hence accurately modelling such

systems requires modelling the environment as well - resulting in undecidability

issues for the traditional model checking approaches.

Statistical model checking has proven itself a valuable supplement to model

checking and this thesis is concerned with extending this software validation

technique to stochastic hybrid systems. The thesis consists of two parts: the first

part motivates why existing model checking technology should be supplemented

by new techniques. It also contains a brief introduction to probability theory

and concepts covered by the six papers making up the second part. The first two

papers are concerned with developing online monitoring techniques for deciding

if a simulation satisfies a property given as a WMTL[a;b] formula. The following

papers develops a framework allowing dynamical instantiation of processes,

in contrast to traditional static encoding of systems. A logic, QDMTL, is

developed to express properties of these dynamically evolving systems. The

fifth paper shows how stochastic hybrid automata are useful for modelling

biological systems and the final paper is concerned with showing how statistical

model checking is efficiently distributed. In parallel with developing the theory

contained in the papers, a substantial part of this work has been devoted to

implementation in Uppaal SMC.

Originalsprog | Engelsk |
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Udgivelses sted | Aalborg |
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Forlag | Aalborg Universitetsforlag |

Antal sider | 204 |

ISBN (Elektronisk) | 978-87-7112-527-6 |

DOI | |

Status | Udgivet - 2015 |

Navn | Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet |
---|---|

ISSN | 2246-1248 |

### Bibliografisk note

Kim Guldstrand Larsen, Hovedvejleder### Citer dette

*Statistical Model Checking of Rich Models and Properties*. Aalborg: Aalborg Universitetsforlag. Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet https://doi.org/10.5278/vbn.phd.engsci.00031

}

*Statistical Model Checking of Rich Models and Properties*. Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet, Aalborg Universitetsforlag, Aalborg. https://doi.org/10.5278/vbn.phd.engsci.00031

**Statistical Model Checking of Rich Models and Properties.** / Poulsen, Danny Bøgsted.

Publikation: Bog/antologi/afhandling/rapport › Ph.d.-afhandling › Forskning

TY - BOOK

T1 - Statistical Model Checking of Rich Models and Properties

AU - Poulsen, Danny Bøgsted

N1 - Kim Guldstrand Larsen, Hovedvejleder

PY - 2015

Y1 - 2015

N2 - Software is in increasing fashion embedded within safety- and business criticalprocesses of society. Errors in these embedded systems can lead to humancasualties or severe monetary loss. Model checking technology has provenformal methods capable of finding and correcting errors in software. However,software is approaching the boundary in terms of the complexity and size thatmodel checking can handle. Furthermore, software systems are nowadays morefrequently interacting with their environment hence accurately modelling suchsystems requires modelling the environment as well - resulting in undecidabilityissues for the traditional model checking approaches.Statistical model checking has proven itself a valuable supplement to modelchecking and this thesis is concerned with extending this software validationtechnique to stochastic hybrid systems. The thesis consists of two parts: the firstpart motivates why existing model checking technology should be supplementedby new techniques. It also contains a brief introduction to probability theoryand concepts covered by the six papers making up the second part. The first twopapers are concerned with developing online monitoring techniques for decidingif a simulation satisfies a property given as a WMTL[a;b] formula. The followingpapers develops a framework allowing dynamical instantiation of processes,in contrast to traditional static encoding of systems. A logic, QDMTL, isdeveloped to express properties of these dynamically evolving systems. Thefifth paper shows how stochastic hybrid automata are useful for modellingbiological systems and the final paper is concerned with showing how statisticalmodel checking is efficiently distributed. In parallel with developing the theorycontained in the papers, a substantial part of this work has been devoted toimplementation in Uppaal SMC.

AB - Software is in increasing fashion embedded within safety- and business criticalprocesses of society. Errors in these embedded systems can lead to humancasualties or severe monetary loss. Model checking technology has provenformal methods capable of finding and correcting errors in software. However,software is approaching the boundary in terms of the complexity and size thatmodel checking can handle. Furthermore, software systems are nowadays morefrequently interacting with their environment hence accurately modelling suchsystems requires modelling the environment as well - resulting in undecidabilityissues for the traditional model checking approaches.Statistical model checking has proven itself a valuable supplement to modelchecking and this thesis is concerned with extending this software validationtechnique to stochastic hybrid systems. The thesis consists of two parts: the firstpart motivates why existing model checking technology should be supplementedby new techniques. It also contains a brief introduction to probability theoryand concepts covered by the six papers making up the second part. The first twopapers are concerned with developing online monitoring techniques for decidingif a simulation satisfies a property given as a WMTL[a;b] formula. The followingpapers develops a framework allowing dynamical instantiation of processes,in contrast to traditional static encoding of systems. A logic, QDMTL, isdeveloped to express properties of these dynamically evolving systems. Thefifth paper shows how stochastic hybrid automata are useful for modellingbiological systems and the final paper is concerned with showing how statisticalmodel checking is efficiently distributed. In parallel with developing the theorycontained in the papers, a substantial part of this work has been devoted toimplementation in Uppaal SMC.

U2 - 10.5278/vbn.phd.engsci.00031

DO - 10.5278/vbn.phd.engsci.00031

M3 - Ph.D. thesis

T3 - Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet

BT - Statistical Model Checking of Rich Models and Properties

PB - Aalborg Universitetsforlag

CY - Aalborg

ER -