6,828 research outputs found
Optimal Strategies in Infinite-state Stochastic Reachability Games
We consider perfect-information reachability stochastic games for 2 players
on infinite graphs. We identify a subclass of such games, and prove two
interesting properties of it: first, Player Max always has optimal strategies
in games from this subclass, and second, these games are strongly determined.
The subclass is defined by the property that the set of all values can only
have one accumulation point -- 0. Our results nicely mirror recent results for
finitely-branching games, where, on the contrary, Player Min always has optimal
strategies. However, our proof methods are substantially different, because the
roles of the players are not symmetric. We also do not restrict the branching
of the games. Finally, we apply our results in the context of recently studied
One-Counter stochastic games
Abstraction and Learning for Infinite-State Compositional Verification
Despite many advances that enable the application of model checking
techniques to the verification of large systems, the state-explosion problem
remains the main challenge for scalability. Compositional verification
addresses this challenge by decomposing the verification of a large system into
the verification of its components. Recent techniques use learning-based
approaches to automate compositional verification based on the assume-guarantee
style reasoning. However, these techniques are only applicable to finite-state
systems. In this work, we propose a new framework that interleaves abstraction
and learning to perform automated compositional verification of infinite-state
systems. We also discuss the role of learning and abstraction in the related
context of interface generation for infinite-state components.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455
A versatile infinite-state Markov reward model to study bottlenecks in 2-hop ad hoc networks
In a 2-hop IEEE 801.11-based wireless LAN, the distributed coordination function (DCF) tends to equally share the available capacity among the contending stations. Recently alternative capacity sharing strategies have been made possible. We propose a versatile infinite-state Markov reward model to study the bottleneck node in a 2-hop IEEE 801.11-based ad hoc network for different adaptive capacity sharing strategies. We use infinite-state stochastic Petri nets (iSPNs) to specify our model, from which the underlying QBD-type Markov-reward models are automatically derived. The impact of the different capacity sharing strategies is analyzed by CSRL model checking of the underlying infinite-state QBD, for which we provide new techniques. Our modeling approach helps in deciding under which circumstances which adaptive capacity sharing strategy is most appropriate
Generalization Strategies for the Verification of Infinite State Systems
We present a method for the automated verification of temporal properties of
infinite state systems. Our verification method is based on the specialization
of constraint logic programs (CLP) and works in two phases: (1) in the first
phase, a CLP specification of an infinite state system is specialized with
respect to the initial state of the system and the temporal property to be
verified, and (2) in the second phase, the specialized program is evaluated by
using a bottom-up strategy. The effectiveness of the method strongly depends on
the generalization strategy which is applied during the program specialization
phase. We consider several generalization strategies obtained by combining
techniques already known in the field of program analysis and program
transformation, and we also introduce some new strategies. Then, through many
verification experiments, we evaluate the effectiveness of the generalization
strategies we have considered. Finally, we compare the implementation of our
specialization-based verification method to other constraint-based model
checking tools. The experimental results show that our method is competitive
with the methods used by those other tools. To appear in Theory and Practice of
Logic Programming (TPLP).Comment: 24 pages, 2 figures, 5 table
Equivalence-Checking on Infinite-State Systems: Techniques and Results
The paper presents a selection of recently developed and/or used techniques
for equivalence-checking on infinite-state systems, and an up-to-date overview
of existing results (as of September 2004)
Efficient First-Order Temporal Logic for Infinite-State Systems
In this paper we consider the specification and verification of
infinite-state systems using temporal logic. In particular, we describe
parameterised systems using a new variety of first-order temporal logic that is
both powerful enough for this form of specification and tractable enough for
practical deductive verification. Importantly, the power of the temporal
language allows us to describe (and verify) asynchronous systems, communication
delays and more complex properties such as liveness and fairness properties.
These aspects appear difficult for many other approaches to infinite-state
verification.Comment: 16 pages, 2 figure
On-the-fly Uniformization of Time-Inhomogeneous Infinite Markov Population Models
This paper presents an on-the-fly uniformization technique for the analysis
of time-inhomogeneous Markov population models. This technique is applicable to
models with infinite state spaces and unbounded rates, which are, for instance,
encountered in the realm of biochemical reaction networks. To deal with the
infinite state space, we dynamically maintain a finite subset of the states
where most of the probability mass is located. This approach yields an
underapproximation of the original, infinite system. We present experimental
results to show the applicability of our technique
An expectation transformer approach to predicate abstraction and data independence for probabilistic programs
In this paper we revisit the well-known technique of predicate abstraction to
characterise performance attributes of system models incorporating probability.
We recast the theory using expectation transformers, and identify transformer
properties which correspond to abstractions that yield nevertheless exact bound
on the performance of infinite state probabilistic systems. In addition, we
extend the developed technique to the special case of "data independent"
programs incorporating probability. Finally, we demonstrate the subtleness of
the extended technique by using the PRISM model checking tool to analyse an
infinite state protocol, obtaining exact bounds on its performance
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