Probabilistic may/must testing: retaining probabilities by restricted schedulers

Georgievska, Sonja; Andova, Suzana

doi:10.1007/s00165-012-0236-5

Cited by 13 publications

(27 citation statements)

References 63 publications

(126 reference statements)

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“…To express linear semantics we need to evaluate and compare the probability of particular sequences of events to occur. As in PTSs this probability highly depends also on nondeterminism, schedulers [18,24,28] (or adversaries) resolving it become fundamental. They can be classified into two main classes: deterministic and randomized schedulers [24].…”

Section: Definition 3 (Computation)mentioning

confidence: 99%

Trace and Testing Metrics on Nondeterministic Probabilistic Processes

Castiglioni

2018

Electron. Proc. Theor. Comput. Sci.

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The combination of nondeterminism and probability in concurrent systems lead to the development of several interpretations of process behavior. If we restrict our attention to linear properties only, we can identify three main approaches to trace and testing semantics: the trace distributions, the trace-by-trace and the extremal probabilities approaches. In this paper, we propose novel notions of behavioral metrics that are based on the three classic approaches above, and that can be used to measure the disparities in the linear behavior of processes wrt. trace and testing semantics. We study the properties of these metrics, like non-expansiveness, and we compare their expressive powers. • •

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Section: Definition 3 (Computation)mentioning

confidence: 99%

Trace and Testing Metrics on Nondeterministic Probabilistic Processes

Castiglioni

2018

Electron. Proc. Theor. Comput. Sci.

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“…Intuitively, a scheduler reduces an ipBES to a element of H 1 Ω. While the technicalities of the schedulers we define in this paper is tailored towards a rely-guarantee reasoning, there might be relationships with previous works [22,23] where schedulers (and associated testing theories) are restricted in order achieve a broader class observationally equivalent processes.…”

Section: Schedulers On Ipbesmentioning

confidence: 99%

Probabilistic rely-guarantee calculus

McIver

Rabehaja

Struth

2016

Theoretical Computer Science

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Jones' rely-guarantee calculus for shared variable concurrency is extended to include probabilistic behaviours. We use an algebraic approach that is based on a combination of probabilistic Kleene algebra with concurrent Kleene algebra. Soundness of the algebra is shown relative to a general probabilistic event structure semantics. The main contribution of this paper is a collection of rely-guarantee rules built on top of that semantics. In particular, we show how to obtain bounds on probabilities of correctness by deriving quantitative extensions of rely-guarantee rules. The use of these rules is illustrated by a detailed verification of a simple probabilistic concurrent program: a faulty Eratosthenes sieve.

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“…This includes theories based on bisimulations; see for instance [32,9] for typical examples. But there are also theories based on testing [31] such as [36,17,14]. Much of this work is based on an intensional model called Probabilistic Labelled Transition Systems, pLTSs in [14], which are roughly equivalent to the Probabilistic Automata from [36] and the NPLTS model of [2].…”

Section: Y Deng M Hennessy / Science Of Computer Programming ( ) -mentioning

confidence: 99%

Compositional reasoning for weighted Markov decision processes

Deng

Hennessy

2013

Science of Computer Programming

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h i g h l i g h t s• We develop compositional methods for reasoning about weighted Markov decision processes (MDPs).• A coinductive simulation-based behavioural preorder is proposed for weighted MDPs.• The preorder is preserved by structural operators for constructing weighted MDPs from components.• For finitary convergent processes, the preorder can be characterised by a probabilistic logic and a novel form of testing. a r t i c l e i n f o b s t r a c tWeighted Markov decision processes (MDPs) have long been used to model quantitative aspects of systems in the presence of uncertainty. However, much of the literature on such MDPs takes a monolithic approach, by modelling a system as a particular MDP; properties of the system are then inferred by analysis of that particular MDP. In contrast in this paper we develop compositional methods for reasoning about weighted MDPs, as a possible basis for compositional reasoning about their quantitative behaviour. In particular we approach these systems from a process algebraic point of view. For these we define a coinductive simulation-based behavioural preorder which is compositional in the sense that it is preserved by structural operators for constructing weighted MDPs from components.For finitary convergent processes, which are finite-state and finitely branching systems without divergence, we provide two characterisations of the behavioural preorder. The first uses a novel quantitative probabilistic logic, while the second is in terms of a novel form of testing, in which benefits are accrued during the execution of tests.

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Probabilistic may/must testing: retaining probabilities by restricted schedulers

Cited by 13 publications

References 63 publications

Trace and Testing Metrics on Nondeterministic Probabilistic Processes

Trace and Testing Metrics on Nondeterministic Probabilistic Processes

Probabilistic rely-guarantee calculus

Compositional reasoning for weighted Markov decision processes

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