Weighted Branching Simulation Distance for Parametric Weighted Kripke Structures

This paper concerns branching simulation for weighted Kripke structures with parametric weights. Concretely, we consider a weighted extension of branching simulation where a single transitions can be matched by a sequence of transitions while preserving the branching behavior. We relax this notion to allow for a small degree of deviation in the matching of weights, inducing a directed distance on states. The distance between two states can be used directly to relate properties of the states within a sub-fragment of weighted CTL. The problem of relating systems thus changes to minimizing the distance which, in the general parametric case, corresponds to finding suitable parameter valuations such that one system can approximately simulate another. Although the distance considers a potentially infinite set of transition sequences we demonstrate that there exists an upper bound on the length of relevant sequences, thereby establishing the computability of the distance.Comment: In Proceedings Cassting'16/SynCoP'16, arXiv:1608.0017

Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms

Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events that can be non-exponentially distributed. Within parametric ACTMCs, the parameters of alarm-event distributions are not given explicitly and can be subject of parameter synthesis. An algorithm solving the $\varepsilon$-optimal parameter synthesis problem for parametric ACTMCs with long-run average optimization objectives is presented. Our approach is based on reduction of the problem to finding long-run average optimal strategies in semi-Markov decision processes (semi-MDPs) and sufficient discretization of parameter (i.e., action) space. Since the set of actions in the discretized semi-MDP can be very large, a straightforward approach based on explicit action-space construction fails to solve even simple instances of the problem. The presented algorithm uses an enhanced policy iteration on symbolic representations of the action space. The soundness of the algorithm is established for parametric ACTMCs with alarm-event distributions satisfying four mild assumptions that are shown to hold for uniform, Dirac and Weibull distributions in particular, but are satisfied for many other distributions as well. An experimental implementation shows that the symbolic technique substantially improves the efficiency of the synthesis algorithm and allows to solve instances of realistic size.Comment: This article is a full version of a paper accepted to the Conference on Quantitative Evaluation of SysTems (QEST) 201

IST Austria Technical Report

As hybrid systems involve continuous behaviors, they should be evaluated by quantitative methods, rather than qualitative methods. In this paper we adapt a quantitative framework, called model measuring, to the hybrid systems domain. The model-measuring problem asks, given a model M and a specification, what is the maximal distance such that all models within that distance from M satisfy (or violate) the specification. A distance function on models is given as part of the input of the problem. Distances, especially related to continuous behaviors are more natural in the hybrid case than the discrete case. We are interested in distances represented by monotonic hybrid automata, a hybrid counterpart of (discrete) weighted automata, whose recognized timed languages are monotone (w.r.t. inclusion) in the values of parameters.The contributions of this paper are twofold. First, we give sufficient conditions under which the model-measuring problem can be solved. Second, we discuss the modeling of distances and applications of the model-measuring problem

A Benchmarks Library for Extended Parametric Timed Automata

Parametric timed automata are a powerful formalism for reasoning on concurrent real-time systems with unknown or uncertain timing constants. In order to test the efficiency of new algorithms, a fair set of benchmarks is required. We present an extension of the IMITATOR benchmarks library, that accumulated over the years a number of case studies from academic and industrial contexts. We extend here the library with several dozens of new benchmarks; these benchmarks highlight several new features: liveness properties, extensions of (parametric) timed automata (including stopwatches or multi-rate clocks), and unsolvable toy benchmarks. These latter additions help to emphasize the limits of state-of-the-art parameter synthesis techniques, with the hope to develop new dedicated algorithms in the future.Comment: This is the author (and extended) version of the manuscript of the same name published in the proceedings of the 15th International Conference on Tests and Proofs (TAP 2021

Modeling a distributed Heterogeneous Communication System using Parametric Timed Automata

In this report, we study the application of the Parametric Timed Automata(PTA) tool to a concrete case of a distributed Heterogeneous Communication System (HCS). The description and requirements of HCS are presented and the system modeling is explained carefully. The system models are developed in UPPAAL and validated by different test cases. Part of the system models are then converted into parametric timed automata and the schedulability checking is run to produce the schedulability regions

Approximating Optimal Bounds in Prompt-LTL Realizability in Doubly-exponential Time

We consider the optimization variant of the realizability problem for Prompt Linear Temporal Logic, an extension of Linear Temporal Logic (LTL) by the prompt eventually operator whose scope is bounded by some parameter. In the realizability optimization problem, one is interested in computing the minimal such bound that allows to realize a given specification. It is known that this problem is solvable in triply-exponential time, but not whether it can be done in doubly-exponential time, i.e., whether it is just as hard as solving LTL realizability. We take a step towards resolving this problem by showing that the optimum can be approximated within a factor of two in doubly-exponential time. Also, we report on a proof-of-concept implementation of the algorithm based on bounded LTL synthesis, which computes the smallest implementation of a given specification. In our experiments, we observe a tradeoff between the size of the implementation and the bound it realizes. We investigate this tradeoff in the general case and prove upper bounds, which reduce the search space for the algorithm, and matching lower bounds.Comment: In Proceedings GandALF 2016, arXiv:1609.0364

Optimizing Performance of Continuous-Time Stochastic Systems using Timeout Synthesis

We consider parametric version of fixed-delay continuous-time Markov chains (or equivalently deterministic and stochastic Petri nets, DSPN) where fixed-delay transitions are specified by parameters, rather than concrete values. Our goal is to synthesize values of these parameters that, for a given cost function, minimise expected total cost incurred before reaching a given set of target states. We show that under mild assumptions, optimal values of parameters can be effectively approximated using translation to a Markov decision process (MDP) whose actions correspond to discretized values of these parameters

Parametric timed model checking for guaranteeing timed opacity

Information leakage can have dramatic consequences on systems security. Among harmful information leaks, the timing information leakage is the ability for an attacker to deduce internal information depending on the system execution time. We address the following problem: given a timed system, synthesize the execution times for which one cannot deduce whether the system performed some secret behavior. We solve this problem in the setting of timed automata (TAs). We first provide a general solution, and then extend the problem to parametric TAs, by synthesizing internal timings making the TA secure. We study decidability, devise algorithms, and show that our method can also apply to program analysis.Comment: This is the author (and extended) version of the manuscript of the same name published in the proceedings of ATVA 2019. This work is partially supported by the ANR national research program PACS (ANR-14-CE28-0002), the ANR-NRF research program (ProMiS) and by ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603), JS

A comparative reliability analysis of ETCS train radio communications

StoCharts have been proposed as a UML statechart extension for performance and dependability evaluation, and were applied in the context of train radio reliability assessment to show the principal tractability of realistic cases with this approach. In this paper, we extend on this bare feasibility result in two important directions. First, we sketch the cornerstones of a mechanizable translation of StoCharts to MoDeST. The latter is a process algebra-based formalism supported by the Motor/Möbius tool tandem. Second, we exploit this translation for a detailed analysis of the train radio case study