Probabilistic model checking of DTMC models of user activity patterns

Andrei, O. , Calder, M. , Higgs, M. and Girolami, M. (2014) Probabilistic model checking of DTMC models of user activity patterns. Lecture Notes in Computer Science, 8657, pp. 138-153. (doi: 10.1007/978-3-319-10696-0_11)

Full text not currently available from Enlighten.

Publisher's URL:


Software developers cannot always anticipate how users will actually use their software as it may vary from user to user, and even from use to use for an individual user. In order to address questions raised by system developers and evaluators about software usage, we define new probabilistic models that characterise user behaviour, based on activity patterns inferred from actual logged user traces. We encode these new models in a probabilistic model checker and use probabilistic temporal logics to gain insight into software usage. We motivate and illustrate our approach by application to the logged user traces of an iOS app.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Andrei, Dr Oana and Higgs, Dr Matthew and Calder, Professor Muffy and Girolami, Prof Mark
Authors: Andrei, O., Calder, M., Higgs, M., and Girolami, M.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Lecture Notes in Computer Science

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
566711A population approach to ubicomp system designMatthew ChalmersEngineering & Physical Sciences Research Council (EPSRC)EP/J007617/1COM - COMPUTING SCIENCE