42,702 research outputs found
Testing Reactive Probabilistic Processes
We define a testing equivalence in the spirit of De Nicola and Hennessy for
reactive probabilistic processes, i.e. for processes where the internal
nondeterminism is due to random behaviour. We characterize the testing
equivalence in terms of ready-traces. From the characterization it follows that
the equivalence is insensitive to the exact moment in time in which an internal
probabilistic choice occurs, which is inherent from the original testing
equivalence of De Nicola and Hennessy. We also show decidability of the testing
equivalence for finite systems for which the complete model may not be known
Moving forward with combinatorial interaction testing
Combinatorial interaction testing (CIT) is an efficient and effective method of detecting failures that are caused by the interactions of various system input parameters. In this paper, we discuss CIT, point out some of the difficulties of applying it in practice, and highlight some recent advances that have improved CITās applicability to modern systems. We also provide a roadmap for future research and directions; one that we hope will lead to new CIT research and to higher quality testing of industrial systems
Markovian Testing Equivalence and Exponentially Timed Internal Actions
In the theory of testing for Markovian processes developed so far,
exponentially timed internal actions are not admitted within processes. When
present, these actions cannot be abstracted away, because their execution takes
a nonzero amount of time and hence can be observed. On the other hand, they
must be carefully taken into account, in order not to equate processes that are
distinguishable from a timing viewpoint. In this paper, we recast the
definition of Markovian testing equivalence in the framework of a Markovian
process calculus including exponentially timed internal actions. Then, we show
that the resulting behavioral equivalence is a congruence, has a sound and
complete axiomatization, has a modal logic characterization, and can be decided
in polynomial time
Uniform Labeled Transition Systems for Nondeterministic, Probabilistic, and Stochastic Process Calculi
Labeled transition systems are typically used to represent the behavior of
nondeterministic processes, with labeled transitions defining a one-step state
to-state reachability relation. This model has been recently made more general
by modifying the transition relation in such a way that it associates with any
source state and transition label a reachability distribution, i.e., a function
mapping each possible target state to a value of some domain that expresses the
degree of one-step reachability of that target state. In this extended
abstract, we show how the resulting model, called ULTraS from Uniform Labeled
Transition System, can be naturally used to give semantics to a fully
nondeterministic, a fully probabilistic, and a fully stochastic variant of a
CSP-like process language.Comment: In Proceedings PACO 2011, arXiv:1108.145
Disjunctive Probabilistic Modal Logic is Enough for Bisimilarity on Reactive Probabilistic Systems
Larsen and Skou characterized probabilistic bisimilarity over reactive
probabilistic systems with a logic including true, negation, conjunction, and a
diamond modality decorated with a probabilistic lower bound. Later on,
Desharnais, Edalat, and Panangaden showed that negation is not necessary to
characterize the same equivalence. In this paper, we prove that the logical
characterization holds also when conjunction is replaced by disjunction, with
negation still being not necessary. To this end, we introduce reactive
probabilistic trees, a fully abstract model for reactive probabilistic systems
that allows us to demonstrate expressiveness of the disjunctive probabilistic
modal logic, as well as of the previously mentioned logics, by means of a
compactness argument.Comment: Aligned content with version accepted at ICTCS 2016: fixed minor
typos, added reference, improved definitions in Section 3. Still 10 pages in
sigplanconf forma
Metric Semantics and Full Abstractness for Action Refinement and Probabilistic Choice
This paper provides a case-study in the field of metric semantics for probabilistic programming. Both an operational and a denotational semantics are presented for an abstract process language L_pr, which features action refinement and probabilistic choice. The two models are constructed in the setting of complete ultrametric spaces, here based on probability measures of compact support over sequences of actions. It is shown that the standard toolkit for metric semantics works well in the probabilistic context of L_pr, e.g. in establishing the correctness of the denotational semantics with respect to the operational one. In addition, it is shown how the method of proving full abstraction --as proposed recently by the authors for a nondeterministic language with action refinement-- can be adapted to deal with the probabilistic language L_pr as well
Hypothesis Testing Interpretations and Renyi Differential Privacy
Differential privacy is a de facto standard in data privacy, with
applications in the public and private sectors. A way to explain differential
privacy, which is particularly appealing to statistician and social scientists
is by means of its statistical hypothesis testing interpretation. Informally,
one cannot effectively test whether a specific individual has contributed her
data by observing the output of a private mechanism---any test cannot have both
high significance and high power.
In this paper, we identify some conditions under which a privacy definition
given in terms of a statistical divergence satisfies a similar interpretation.
These conditions are useful to analyze the distinguishability power of
divergences and we use them to study the hypothesis testing interpretation of
some relaxations of differential privacy based on Renyi divergence. This
analysis also results in an improved conversion rule between these definitions
and differential privacy
A uniform framework for modelling nondeterministic, probabilistic, stochastic, or mixed processes and their behavioral equivalences
Labeled transition systems are typically used as behavioral models of concurrent processes, and the labeled transitions define the a one-step state-to-state reachability relation. This model can be made generalized by modifying the transition relation to associate a state reachability distribution, rather than a single target state, with any pair of source state and transition label. The state reachability distribution becomes a function mapping each possible target state to a value that expresses the degree of one-step reachability of that state. Values are taken from a preordered set equipped with a minimum that denotes unreachability. By selecting suitable preordered sets, the resulting model, called ULTraS from Uniform Labeled Transition System, can be specialized to capture well-known models of fully nondeterministic processes (LTS), fully
probabilistic processes (ADTMC), fully stochastic processes (ACTMC), and of nondeterministic and probabilistic (MDP) or nondeterministic and stochastic (CTMDP) processes. This uniform treatment of different behavioral models extends to behavioral equivalences. These can be defined on ULTraS by relying on appropriate measure functions that expresses the degree of reachability of a set of states when performing
single-step or multi-step computations. It is shown that the specializations of bisimulation, trace, and testing
equivalences for the different classes of ULTraS coincide with the behavioral equivalences defined in the literature over traditional models
On Probabilistic Applicative Bisimulation and Call-by-Value -Calculi (Long Version)
Probabilistic applicative bisimulation is a recently introduced coinductive
methodology for program equivalence in a probabilistic, higher-order, setting.
In this paper, the technique is applied to a typed, call-by-value,
lambda-calculus. Surprisingly, the obtained relation coincides with context
equivalence, contrary to what happens when call-by-name evaluation is
considered. Even more surprisingly, full-abstraction only holds in a symmetric
setting.Comment: 30 page
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