Lightweight Statistical Model Checking in Nondeterministic Continuous Time

Lightweight scheduler sampling brings statistical model checking to nondeterministic formalisms with undiscounted properties, in constant memory. Its direct application to continuous-time models is rendered ineffective by their dense concrete state spaces and the need to consider continuous input for optimal decisions. In this paper we describe the challenges and state of the art in applying lightweight scheduler sampling to three continuous-time formalisms: After a review of recent work on exploiting discrete abstractions for probabilistic timed automata, we discuss scheduler sampling for Markov automata and apply it on two case studies. We provide further insights into the tradeoffs between scheduler classes for stochastic automata. Throughout, we present extended experiments and new visualisations of the distribution of schedulers.</p

Probabilistic Bisimulation: Naturally on Distributions

In contrast to the usual understanding of probabilistic systems as stochastic processes, recently these systems have also been regarded as transformers of probabilities. In this paper, we give a natural definition of strong bisimulation for probabilistic systems corresponding to this view that treats probability distributions as first-class citizens. Our definition applies in the same way to discrete systems as well as to systems with uncountable state and action spaces. Several examples demonstrate that our definition refines the understanding of behavioural equivalences of probabilistic systems. In particular, it solves a long-standing open problem concerning the representation of memoryless continuous time by memory-full continuous time. Finally, we give algorithms for computing this bisimulation not only for finite but also for classes of uncountably infinite systems

Model-Based Verification, Optimization, Synthesis and Performance Evaluation of Real-Time Systems

International audienceThis article aims at providing a concise and precise Travellers Guide, Phrase Book or Reference Manual to the timed automata modeling formalism introduced by Alur and Dill [8, 9]. The paper gives comprehensive definitions of timed automata, priced (or weighted) timed automata, and timed games and highlights a number of results on associated decision problems related to model checking, equivalence checking, optimal scheduling, the existence of winning strategies, and then statistical model checking

Characteristics of Passive Solute Transport across Primary Rat Alveolar Epithelial Cell Monolayers

Primary rat alveolar epithelial cell monolayers (RAECM) were grown without (type I cell-like phenotype, RAECM-I) or with (type II cell-like phenotype, RAECM-II) keratinocyte growth factor to assess passive transport of 11 hydrophilic solutes. We estimated apparent permeability (Papp) in the absence/presence of calcium chelator EGTA to determine the effects of perturbing tight junctions on “equivalent” pores. Papp across RAECM-I and -II in the absence of EGTA are similar and decrease as solute size increases. We modeled Papp of the hydrophilic solutes across RAECM-I/-II as taking place via heterogeneous populations of equivalent pores comprised of small (0.41/0.32 nm radius) and large (9.88/11.56 nm radius) pores, respectively. Total equivalent pore area is dominated by small equivalent pores (99.92–99.97%). The number of small and large equivalent pores in RAECM-I was 8.55 and 1.29 times greater, respectively, than those in RAECM-II. With EGTA, the large pore radius in RAECM-I/-II increased by 1.58/4.34 times and the small equivalent pore radius increased by 1.84/1.90 times, respectively. These results indicate that passive diffusion of hydrophilic solutes across an alveolar epithelium occurs via small and large equivalent pores, reflecting interactions of transmembrane proteins expressed in intercellular tight junctions of alveolar epithelial cells