Weaving Rules into [email protected] for Embedded Smart Systems

Smart systems are characterised by their ability to analyse measured data in live and to react to changes according to expert rules. Therefore, such systems exploit appropriate data models together with actions, triggered by domain-related conditions. The challenge at hand is that smart systems usually need to process thousands of updates to detect which rules need to be triggered, often even on restricted hardware like a Raspberry Pi. Despite various approaches have been investigated to efficiently check conditions on data models, they either assume to fit into main memory or rely on high latency persistence storage systems that severely damage the reactivity of smart systems. To tackle this challenge, we propose a novel composition process, which weaves executable rules into a data model with lazy loading abilities. We quantitatively show, on a smart building case study, that our approach can handle, at low latency, big sets of rules on top of large-scale data models on restricted hardware.Comment: pre-print version, published in the proceedings of MOMO-17 Worksho

Ellogon: A New Text Engineering Platform

This paper presents Ellogon, a multi-lingual, cross-platform, general-purpose text engineering environment. Ellogon was designed in order to aid both researchers in natural language processing, as well as companies that produce language engineering systems for the end-user. Ellogon provides a powerful TIPSTER-based infrastructure for managing, storing and exchanging textual data, embedding and managing text processing components as well as visualising textual data and their associated linguistic information. Among its key features are full Unicode support, an extensive multi-lingual graphical user interface, its modular architecture and the reduced hardware requirements.Comment: 7 pages, 9 figures. Will be presented to the Third International Conference on Language Resources and Evaluation - LREC 200

Loupe: Verifying Publish-Subscribe Architectures with a Magnifying Lens

CONE

Generating a contract checker for an SLA language

SLAng is a language for expressing Service LevelAgreements (SLAs) under development as part of the Europeanproject TAPAS. It is defined using a meta-model, an instance ofthe Meta-Object Facility (MOF) model, in which the relationshipbetween the syntax of the language and its domain of applicationis explicitly represented, and the violation semantics ofthe language defined using Object Constraint Language (OCL)constraints. The concrete syntax of the language is the XMLMeta-data Interchange (XMI) mapping of the syntactic part ofthe meta-model. In this paper we describe how the Java MetadataInterface (JMI) mapping can be applied to the meta-modelof the language to generate interfaces and classes to create andquery SLAs and relevant service monitoring data in memory;and how an OCL interpreter can be applied to check violationconstraints over this data, resulting in the implementation of acontract checker that is highly likely to respect the semantics ofthe language

Thread-Modular Static Analysis for Relaxed Memory Models

We propose a memory-model-aware static program analysis method for accurately analyzing the behavior of concurrent software running on processors with weak consistency models such as x86-TSO, SPARC-PSO, and SPARC-RMO. At the center of our method is a unified framework for deciding the feasibility of inter-thread interferences to avoid propagating spurious data flows during static analysis and thus boost the performance of the static analyzer. We formulate the checking of interference feasibility as a set of Datalog rules which are both efficiently solvable and general enough to capture a range of hardware-level memory models. Compared to existing techniques, our method can significantly reduce the number of bogus alarms as well as unsound proofs. We implemented the method and evaluated it on a large set of multithreaded C programs. Our experiments showthe method significantly outperforms state-of-the-art techniques in terms of accuracy with only moderate run-time overhead.Comment: revised version of the ESEC/FSE 2017 pape