Coherent Integration of Databases by Abductive Logic Programming

We introduce an abductive method for a coherent integration of independent data-sources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called Asystem, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to `recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the `recovered databases' in terms of the `preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and -- to the best of our knowledge -- is more expressive (thus more general) than any other implementation of coherent integration of databases

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Exploiting partial knowledge for efficient model analysis

The advancement of constraint solvers and model checkers has enabled the effective analysis of high-level formal specification languages. However, these typically handle a specification in an opaque manner, amalgamating all its constraints in a single monolithic verification task, which often proves to be a performance bottleneck. This paper addresses this issue by proposing a solving strategy that exploits user-provided partial knowledge, namely by assigning symbolic bounds to the problem’s variables, to automatically decompose a verification task into smaller ones, which are prone to being independently analyzed in parallel and with tighter search spaces. An effective implementation of the technique is provided as an extension to the Kodkod relational constraint solver. Evaluation shows that, in average, the proposed technique outperforms the regular amalgamated verification procedure.ERDF - European Regional Development Fund(POCI-01-0145-FEDER-016826)This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-016826.info:eu-repo/semantics/publishedVersio

Simplifying the analysis of software design variants with a colorful alloy

Formal modeling and automatic analysis are essential to achieve a trustworthy software design prior to its implementation. Alloy and its Analyzer are a popular language and tool for this task. Frequently, rather than a single software artifact, the goal is to develop a full software product line (SPL) with many variants supporting different features. Ideally, software design languages and tools should provide support for analyzing all such variants (e.g., by helping pinpoint combinations of features that could break a property), but that is not currently the case. Even when developing a single artifact, support for multi-variant analysis is desirable to explore design alternatives. Several techniques have been proposed to simplify the implementation of SPLs. One such technique is to use background colors to identify the fragments of code associated with each feature. In this paper we propose to use that same technique for formal design, showing how to add support for features and background colors to Alloy and its Analyzer, thus easing the analysis of software design variants. Some illustrative examples and evaluation results are presented, showing the benefits and efficiency of the implemented technique.This work is financed by the ERDF - European Regional Development Fund - through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 - and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia, within project POCI-01- 0145-FEDER-016826. The third author was also supported by the FCT sabbatical grant with reference SFRH/BSAB/143106/2018

Cracks in the Glass: The Emergence of a New Image Typology from the Spatio-temporal Schisms of the 'Filmic' Virtual Reality Panorama

Virtual Reality Panoramas have fascinated me for some time; their interactive nature affording a spectatorial engagement not evident within other forms of painting or digital imagery. This interactivity is not generally linear as is evident in animation or film, nor is the engagement with the image reduced to the physical or visual border of the image, as its limit is never visible to the viewer in its entirety. Further, the time taken to interact and navigate across the Virtual Reality panorama’s surface is not reflected or recorded within the observed image. The procedural construction of the Virtual Reality panorama creates an a-temporal image event that denies the durée of its own index and creation. This is particularly evident in the cinematic experiments conducted by Jeffrey Shaw in the 1990s that ‘spatialised’ time and image through the fusion of the formal typology of the Panorama together with the cinematic moving-image, creating a new kind of image technology. The incorporation of the space enclosed by the panorama’s drum, into the conception and execution of the cinematic event, reveals an interesting conceptual paradox. Space and time infinitely and autonomously repeat upon each other as the linear trajectory of the singular cinematic shot is interrupted by a ‘time schism’ on the surface of the panorama. This paper explores what this conceptual paradox means to the evolution of emerging image-technologies and how Shaw’s ‘mixed-reality’ installation reveals a wholly new image typology that presents techniques and concepts though which to record, interrogate, and represent time and space in Architecture

Deception in Optimal Control

In this paper, we consider an adversarial scenario where one agent seeks to achieve an objective and its adversary seeks to learn the agent's intentions and prevent the agent from achieving its objective. The agent has an incentive to try to deceive the adversary about its intentions, while at the same time working to achieve its objective. The primary contribution of this paper is to introduce a mathematically rigorous framework for the notion of deception within the context of optimal control. The central notion introduced in the paper is that of a belief-induced reward: a reward dependent not only on the agent's state and action, but also adversary's beliefs. Design of an optimal deceptive strategy then becomes a question of optimal control design on the product of the agent's state space and the adversary's belief space. The proposed framework allows for deception to be defined in an arbitrary control system endowed with a reward function, as well as with additional specifications limiting the agent's control policy. In addition to defining deception, we discuss design of optimally deceptive strategies under uncertainties in agent's knowledge about the adversary's learning process. In the latter part of the paper, we focus on a setting where the agent's behavior is governed by a Markov decision process, and show that the design of optimally deceptive strategies under lack of knowledge about the adversary naturally reduces to previously discussed problems in control design on partially observable or uncertain Markov decision processes. Finally, we present two examples of deceptive strategies: a "cops and robbers" scenario and an example where an agent may use camouflage while moving. We show that optimally deceptive strategies in such examples follow the intuitive idea of how to deceive an adversary in the above settings

A logic programming framework for modeling temporal objects

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