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ASE 2020
Mon 21 - Fri 25 September 2020 Melbourne, Australia
Tue 22 Sep 2020 09:30 - 09:50 at Kangaroo - Formal Methods (2) Chair(s): Eunsuk Kang

Recent probabilistic model checking techniques can verify reliability and performance properties of software systems affected by parametric uncertainty. This involves modelling the system behaviour using \emph{interval Markov chains}, i.e., Markov models with transition probabilities or rates specified as intervals. These intervals can be updated continually using Bayesian estimators with imprecise priors, enabling the verification of the system properties of interest at runtime. However, Bayesian estimators are slow to react to sudden changes in the actual value of the estimated parameters, yielding inaccurate intervals and leading to poor verification results after such changes. To address this limitation, we introduce an efficient interval change-point detection method, and we integrate it with a state-of-the-art Bayesian estimator with imprecise priors. Our experimental results show that the resulting end-to-end Bayesian approach to change-point detection and estimation of interval Markov chain parameters handles effectively a wide range of sudden changes in parameter values, and supports runtime probabilistic model checking under parametric uncertainty.

Tue 22 Sep
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09:10 - 10:10: Formal Methods (2)Research Papers at Kangaroo
Chair(s): Eunsuk KangCarnegie Mellon University, USA
09:10 - 09:30
Verified from Scratch: Program Analysis for Learners' Programs
Research Papers
Andreas StahlbauerUniversity of Passau, Christoph Fr├ĄdrichUniversity of Passau, Gordon FraserUniversity of Passau
09:30 - 09:50
Interval Change-Point Detection for Runtime Probabilistic Model Checking
Research Papers
Xingyu ZhaoHeriot-Watt University, Radu CalinescuUniversity of York, UK, Simos GerasimouUniversity of York, UK, Valentin RobuHeriot-Watt University, David FlynnHeriot-Watt University
09:50 - 10:10
UnchartIt: An Interactive Framework for Program Recovery from Charts
Research Papers
Daniel RamosINESC-ID/IST, Universidade de Lisboa, Jorge PereiraINESC-ID/IST, Universidade de Lisboa, Ines LynceINESC-ID/IST, Universidade de Lisboa, Vasco ManquinhoINESC-ID/IST, Universidade de Lisboa, Ruben MartinsCarnegie Mellon University