568 research outputs found
Explicit Model Checking of Very Large MDP using Partitioning and Secondary Storage
The applicability of model checking is hindered by the state space explosion
problem in combination with limited amounts of main memory. To extend its
reach, the large available capacities of secondary storage such as hard disks
can be exploited. Due to the specific performance characteristics of secondary
storage technologies, specialised algorithms are required. In this paper, we
present a technique to use secondary storage for probabilistic model checking
of Markov decision processes. It combines state space exploration based on
partitioning with a block-iterative variant of value iteration over the same
partitions for the analysis of probabilistic reachability and expected-reward
properties. A sparse matrix-like representation is used to store partitions on
secondary storage in a compact format. All file accesses are sequential, and
compression can be used without affecting runtime. The technique has been
implemented within the Modest Toolset. We evaluate its performance on several
benchmark models of up to 3.5 billion states. In the analysis of time-bounded
properties on real-time models, our method neutralises the state space
explosion induced by the time bound in its entirety.Comment: The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-319-24953-7_1
A Hierarchy of Scheduler Classes for Stochastic Automata
Stochastic automata are a formal compositional model for concurrent
stochastic timed systems, with general distributions and non-deterministic
choices. Measures of interest are defined over schedulers that resolve the
nondeterminism. In this paper we investigate the power of various theoretically
and practically motivated classes of schedulers, considering the classic
complete-information view and a restriction to non-prophetic schedulers. We
prove a hierarchy of scheduler classes w.r.t. unbounded probabilistic
reachability. We find that, unlike Markovian formalisms, stochastic automata
distinguish most classes even in this basic setting. Verification and strategy
synthesis methods thus face a tradeoff between powerful and efficient classes.
Using lightweight scheduler sampling, we explore this tradeoff and demonstrate
the concept of a useful approximative verification technique for stochastic
automata
On Zone-Based Analysis of Duration Probabilistic Automata
We propose an extension of the zone-based algorithmics for analyzing timed
automata to handle systems where timing uncertainty is considered as
probabilistic rather than set-theoretic. We study duration probabilistic
automata (DPA), expressing multiple parallel processes admitting memoryfull
continuously-distributed durations. For this model we develop an extension of
the zone-based forward reachability algorithm whose successor operator is a
density transformer, thus providing a solution to verification and performance
evaluation problems concerning acyclic DPA (or the bounded-horizon behavior of
cyclic DPA).Comment: In Proceedings INFINITY 2010, arXiv:1010.611
Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance
Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft
or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner.
Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''.
The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few.
This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage.
The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling
Synthesis and Stochastic Assessment of Cost-Optimal Schedules
We present a novel approach to synthesize good schedules for a class
of scheduling problems that is slightly more general than the
scheduling problem FJm,a|gpr,r_j,d_j|early/tardy. The idea is to prime
the schedule synthesizer with stochastic information more meaningful
than performance factors with the objective to minimize the expected
cost caused by storage or delay. The priming information is
obtained by stochastic simulation of the system environment. The generated
schedules are assessed again by simulation. The approach is
demonstrated by means of a non-trivial scheduling problem from
lacquer production. The experimental results show that our approach
achieves in all considered scenarios better results than the
extended processing times approach
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/MĂśbius tool tandem. Second, we exploit this translation for a detailed analysis of the train radio case study
Formal and Informal Methods for Multi-Core Design Space Exploration
We propose a tool-supported methodology for design-space exploration for
embedded systems. It provides means to define high-level models of applications
and multi-processor architectures and evaluate the performance of different
deployment (mapping, scheduling) strategies while taking uncertainty into
account. We argue that this extension of the scope of formal verification is
important for the viability of the domain.Comment: In Proceedings QAPL 2014, arXiv:1406.156
On the analysis of stochastic timed systems
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 of interest, such as safety guarantees or performance requirements, can be verified automatically. In this thesis, we present techniques that extend the reach of exhaustive and statistical model checking to verify reachability and reward-based properties of compositional behavioural models that support quantitative aspects such as real time and randomised decisions.
We present two techniques that allow sound statistical model checking for the nondeterministic-randomised model of Markov decision processes. We investigate the relationship between two different definitions of the model of probabilistic timed automata, as well as potential ways to apply statistical model checking. Stochastic timed automata allow nondeterministic choices as well as nondeterministic and stochastic delays, and we present the first exhaustive model checking algorithm that allows their analysis. All the approaches introduced in this thesis are implemented as part of the Modest Toolset, which supports the construction and verification of models specified in the formal modelling language Modest. We conclude by applying this language and toolset to study novel distributed control strategies for photovoltaic microgenerators
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