2014/03/20 by Oana Andrei, Andrei, Oana, Muffy Calder +5 · 1 citation
Business, Management and Accounting · Computer Science · #Advanced Software Engineering Methodologies #Business Process Modeling and Analysis #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Software Engineering (cs.SE) #Software System Performance and Reliability
paper · pdf · doi:10.48550/arxiv.1403.6678
openalex publication_date 2014/03/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.