1,890 research outputs found
A theory of normed simulations
In existing simulation proof techniques, a single step in a lower-level
specification may be simulated by an extended execution fragment in a
higher-level one. As a result, it is cumbersome to mechanize these techniques
using general purpose theorem provers. Moreover, it is undecidable whether a
given relation is a simulation, even if tautology checking is decidable for the
underlying specification logic. This paper introduces various types of normed
simulations. In a normed simulation, each step in a lower-level specification
can be simulated by at most one step in the higher-level one, for any related
pair of states. In earlier work we demonstrated that normed simulations are
quite useful as a vehicle for the formalization of refinement proofs via
theorem provers. Here we show that normed simulations also have pleasant
theoretical properties: (1) under some reasonable assumptions, it is decidable
whether a given relation is a normed forward simulation, provided tautology
checking is decidable for the underlying logic; (2) at the semantic level,
normed forward and backward simulations together form a complete proof method
for establishing behavior inclusion, provided that the higher-level
specification has finite invisible nondeterminism.Comment: 31 pages, 10figure
Generalized Strong Preservation by Abstract Interpretation
Standard abstract model checking relies on abstract Kripke structures which
approximate concrete models by gluing together indistinguishable states, namely
by a partition of the concrete state space. Strong preservation for a
specification language L encodes the equivalence of concrete and abstract model
checking of formulas in L. We show how abstract interpretation can be used to
design abstract models that are more general than abstract Kripke structures.
Accordingly, strong preservation is generalized to abstract
interpretation-based models and precisely related to the concept of
completeness in abstract interpretation. The problem of minimally refining an
abstract model in order to make it strongly preserving for some language L can
be formulated as a minimal domain refinement in abstract interpretation in
order to get completeness w.r.t. the logical/temporal operators of L. It turns
out that this refined strongly preserving abstract model always exists and can
be characterized as a greatest fixed point. As a consequence, some well-known
behavioural equivalences, like bisimulation, simulation and stuttering, and
their corresponding partition refinement algorithms can be elegantly
characterized in abstract interpretation as completeness properties and
refinements
Stuttering Min oscillations within E. coli bacteria: A stochastic polymerization model
We have developed a 3D off-lattice stochastic polymerization model to study
subcellular oscillation of Min proteins in the bacteria Escherichia coli, and
used it to investigate the experimental phenomenon of Min oscillation
stuttering. Stuttering was affected by the rate of immediate rebinding of MinE
released from depolymerizing filament tips (processivity), protection of
depolymerizing filament tips from MinD binding, and fragmentation of MinD
filaments due to MinE. Each of processivity, protection, and fragmentation
reduces stuttering, speeds oscillations, and reduces MinD filament lengths.
Neither processivity or tip-protection were, on their own, sufficient to
produce fast stutter-free oscillations. While filament fragmentation could, on
its own, lead to fast oscillations with infrequent stuttering; high levels of
fragmentation degraded oscillations. The infrequent stuttering observed in
standard Min oscillations are consistent with short filaments of MinD, while we
expect that mutants that exhibit higher stuttering frequencies will exhibit
longer MinD filaments. Increased stuttering rate may be a useful diagnostic to
find observable MinD polymerization in experimental conditions.Comment: 21 pages, 7 figures, missing unit for k_f inserte
Personalising the user experience of a mobile health application towards Patient Engagement
Stuttering is a multifactorial speech disorder that usually has several impacts on daily life, especially regarding loss of confidence in social situations and increased anxiety levels. BroiStu is a mobile health application that was developed to address the impacts of stuttering on people who stutter, allowing them to be more aware of their speech disorder in their everyday life. The personalisation of the user experience may be particularly important to maintain the patient engaged with the application towards a long-term use to take full advantage of the application’s features. This paper presents the implementation of personalisation aspects in BroiStu, introducing the model that is being followed, describing the features used, and presenting the results obtained with a preliminary experiment. The personalisation mechanisms are provided by a cloud-based platform that is designed to serve different applications. Interesting findings and further work are presented.info:eu-repo/semantics/publishedVersio
Assembling evidence for identifying reservoirs of infection
Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems
Generalizing the Paige-Tarjan Algorithm by Abstract Interpretation
The Paige and Tarjan algorithm (PT) for computing the coarsest refinement of
a state partition which is a bisimulation on some Kripke structure is well
known. It is also well known in model checking that bisimulation is equivalent
to strong preservation of CTL, or, equivalently, of Hennessy-Milner logic.
Drawing on these observations, we analyze the basic steps of the PT algorithm
from an abstract interpretation perspective, which allows us to reason on
strong preservation in the context of generic inductively defined (temporal)
languages and of possibly non-partitioning abstract models specified by
abstract interpretation. This leads us to design a generalized Paige-Tarjan
algorithm, called GPT, for computing the minimal refinement of an abstract
interpretation-based model that strongly preserves some given language. It
turns out that PT is a straight instance of GPT on the domain of state
partitions for the case of strong preservation of Hennessy-Milner logic. We
provide a number of examples showing that GPT is of general use. We first show
how a well-known efficient algorithm for computing stuttering equivalence can
be viewed as a simple instance of GPT. We then instantiate GPT in order to
design a new efficient algorithm for computing simulation equivalence that is
competitive with the best available algorithms. Finally, we show how GPT allows
to compute new strongly preserving abstract models by providing an efficient
algorithm that computes the coarsest refinement of a given partition that
strongly preserves the language generated by the reachability operator.Comment: Keywords: Abstract interpretation, abstract model checking, strong
preservation, Paige-Tarjan algorithm, refinement algorith
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