Barnert, MaximilianKrcmar, HelmutKelter, Udo2022-11-242022-11-242020https://dl.gi.de/handle/20.500.12116/39800The specification of complex user behavior as accurate as possible is required in order to evaluate performance characteristics for application systems. Approaches exist to model probabilistic aspects within user behavior for session-based application systems using Markov chains. To integrate these approach into performance prediction activities, the authors transform the workload specifications of WESSBAS into performance model instances of the Palladio Component Model (PCM). This paper presents our approach to enable backward transitions within Markov chains using available elements of the PCM meta-model. By extending the existing approach, further complexity within workload for application systems is supported during performance modeling.enperformancepredictionprobabilisticMarkovPalladio Component ModelText/Conference Paper0720-8928