Statistical model checking: challenges and perspectives
A Legay, M Viswanathan - International Journal on Software Tools for …, 2015 - Springer
Statistical model checking (SMC) is a powerful and widely used approach that consists in
estimating the probability for a system to satisfy a temporal property. This is done by …
estimating the probability for a system to satisfy a temporal property. This is done by …
The role of model checking in software engineering
Abstract Model checking is a formal verification technique. It takes an exhaustively strategy
to check hardware circuits and network protocols against desired properties. Having been …
to check hardware circuits and network protocols against desired properties. Having been …
A statistical model checker for nondeterminism and rare events
Statistical model checking avoids the state space explosion problem in verification and
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …
An efficient statistical model checker for nondeterminism and rare events
Statistical model checking avoids the state space explosion problem in verification and
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …
naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach …
The 10,000 facets of MDP model checking
This paper presents a retrospective view on probabilistic model checking. We focus on
Markov decision processes (MDPs, for short). We survey the basic ingredients of MDP …
Markov decision processes (MDPs, for short). We survey the basic ingredients of MDP …
The modest state of learning, sampling, and verifying strategies
A Hartmanns, M Klauck - … on Leveraging Applications of Formal Methods, 2022 - Springer
Optimal decision-making under stochastic uncertainty is a core problem tackled in artificial
intelligence/machine learning (AI), planning, and verification. Planning and AI methods aim …
intelligence/machine learning (AI), planning, and verification. Planning and AI methods aim …
[HTML][HTML] In the quantitative automata zoo
A Hartmanns, H Hermanns - Science of Computer Programming, 2015 - Elsevier
Quantitative model checking and performance evaluation deal with the analysis of complex
systems that must not only satisfy correctness requirements, but also meet performance and …
systems that must not only satisfy correctness requirements, but also meet performance and …
Input/Output Stochastic Automata: Compositionality and Determinism
Stochastic automata provide a way to symbolically model systems in which the occurrence
time of events may respond to any continuous random variable. We introduce here an …
time of events may respond to any continuous random variable. We introduce here an …
A novel approach to determine a tactical and operational decision for dynamic appointment scheduling at nuclear medical center
In this research, appointment scheduling is addressed in a nuclear medical center. A finite-
horizon Markov Decision Process as dynamic programming is applied to formulate the …
horizon Markov Decision Process as dynamic programming is applied to formulate the …
On the analysis of stochastic timed systems
A Hartmanns - 2015 - publikationen.sulb.uni-saarland.de
The formal methods approach to develop reliable and efficient safety-or performance-critical
systems is to construct mathematically precise models of such systems on which properties …
systems is to construct mathematically precise models of such systems on which properties …