The paper “Probabilistic Model Checking for Uncertain Scenario-Aware Data Flow” by Joost-Pieter Katoen and Hao Wu has been accepted for publication in the journal ACM Transactions on Embedded Computing Systems.  A short version thereof received the best paper award at the IDEA Workshop during the CPS week 2016.

Based on a compositional semantics of exponentially-timed S(A)DF it proposes to use efficient probabilistic model-checking techniques to analyse quantitative objectives of data-flow applications such as MPEG decoding and face recognition examples.