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 |
|---|
| Udgivelses sted | Aalborg |
|---|---|
| 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, HovedvejlederCiter dette
}
Statistical Model Checking of Rich Models and Properties. / Poulsen, Danny Bøgsted.
Aalborg : Aalborg Universitetsforlag, 2015. 204 s. (Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet).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 -