Consistency preservation and crazy formulas in BMS

International audienceWe provide conditions under which seriality is preserved during an update in the BMS framework. We consider not only whether the entire updated model is serial but also whether its generated submodels are serial. We also introduce the notion of crazy formulas which are formulas such that after being publicly announced at least one of the agents' beliefs become inconsistent

Evaluating Model Differencing for the Consistency Preservation of State-based Views

While developers and users of modern software systems usually only need to interact with a specific part of the system at a time, they are hindered by the ever-increasing complexity of the entire system. Views are projections of underlying models and can be employed to abstract from that complexity. When a view is modified, the changes must be propagated back into the underlying model without overriding simultaneous modifications. Hence, the view needs to provide a fine-grained sequence of changes to update the model minimally invasively. Such fine-grained changes are often unavailable for views that integrate with existing workflows and tools. To this end, model differencing approaches can be leveraged to compare two states of a view and derive an estimated change sequence. However, these model differencing approaches are not intended to operate with views, as their correctness is judged solely by comparing the input models. For views, the changes are derived from the view states, but the correctness depends on the underlying model. This work introduces a refined notion of correctness for change sequences in the context of model-view consistency. Furthermore, we evaluate state-of-the-art model differencing regarding model-view consistency. Our results show that model differencing largely performs very well. However, incorrect change sequences were derived for two common refactoring operation types, leading to an incorrect model state. These types can be easily reproduced and are likely to occur in practice. By considering our change sequence properties in the view type design, incorrect change sequences can be detected and semi-automatically repaired to prevent such incorrect model states

A Bistochastic Nonparametric Estimator

We explore the relevance of adopting a bistochastic nonparametric estimator. This estimator has two main implications. First, the estimator reduces variability according to the robust criterion of second-order stochastic (and Lorenz) dominance. This is a universally criterion in risk and welfare economics, which expands the applicability of nonparametric estimation in economics, for instance to the measurement of economic discrimination. Second, the bistochastic estimator produces smaller errors than do positive-weights nonparametric estimators, in terms of the bias-variance trade-off. This result is verified in a general simulation exercise. This improvement is due to a significant reduction in boundary bias, which makes the estimator itself useful in empirical applications. Finally, consistency, preservation of the mean value, and multidimensional extension are some other useful properties of this estimator.nonparametric estimation, second-order stochastic dominance, bistochastic estimator

Consistent View-Based Management of Variability in Space and Time

Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems

Belief Revision in Structured Probabilistic Argumentation

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates -- based on well-known ones developed for classical knowledge bases -- that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates

Transparent Dynamic reconfiguration for CORBA

Distributed systems with high availability requirements have to support some form of dynamic reconfiguration. This means that they must provide the ability to be maintained or upgraded without being taken off-line. Building a distributed system that allows dynamic reconfiguration is very intrusive to the overall design of the system, and generally requires special skills from both the client and server side application developers. There is an opportunity to provide support for dynamic reconfiguration at the object middleware level of distributed systems, and create a dynamic reconfiguration transparency to application developers. We propose a Dynamic Reconfiguration Service for CORBA that allows the reconfiguration of a running system with maximum transparency for both client and server side developers. We describe the architecture, a prototype implementation, and some preliminary test result