Model-Checking Algorithms for

TL;DR: Correctness of the abstraction holds when automata are almost-surely fair, which it is shown, is the case for two large classes of systems, single- clock automata and so-called weak-reactive automata.

TL;DR: The notion of safe diagnosability for stochastic automata, in which fault detection occurs before any given forbidden string in the failed mode of system is executed, is defined.

TL;DR: The goal of this work is to facilitate the identification of causal factors in the potentially very large sets of execution paths that form counterexamples in stochastic model checking.

TL;DR: The Hybrid Automata Stochastic Logic (HASL), a new temporal logic formalism for the verification of discrete event stochastic processes (DESP), provides a unifying verification framework where temporal reasoning is naturally blended with elaborate reward-based analysis.

TL;DR: Puterman as discussed by the authors provides a uniquely up-to-date, unified, and rigorous treatment of the theoretical, computational, and applied research on Markov decision process models, focusing primarily on infinite horizon discrete time models and models with discrete time spaces while also examining models with arbitrary state spaces, finite horizon models, and continuous time discrete state models.

TL;DR: This text introduces the basic data structures and programming techniques often used in efficient algorithms, and covers use of lists, push-down stacks, queues, trees, and graphs.

TL;DR: Alur et al. as discussed by the authors proposed timed automata to model the behavior of real-time systems over time, and showed that the universality problem and the language inclusion problem are solvable only for the deterministic automata: both problems are undecidable (II i-hard) in the non-deterministic case and PSPACE-complete in deterministic case.

TL;DR: The value of depth-first search or “backtracking” as a technique for solving problems is illustrated by two examples of an improved version of an algorithm for finding the strongly connected components of a directed graph.