Dura

The reactive event processing language, that is developed in the context of this project, has been called DEAL in previous documents. When we chose this name for our language it has not been used by other authors working in the same research area (complex event processing). However, in the meantime it appears in publications of other authors and because we have not used the name in publications yet we cannot claim that we were the first to use it. In order to avoid ambiguities and name conflicts in future publications we decided to rename our language to Dura which stands for “Declarative uniform reactive event processing language”. Therefore the title of this deliverable has been updated to “Dura – Concepts and Examples”

Big continuous data: dealing with velocity by composing event streams

International audienceThe rate at which we produce data is growing steadily, thus creating even larger streams of continuously evolving data. Online news, micro-blogs, search queries are just a few examples of these continuous streams of user activities. The value of these streams relies in their freshness and relatedness to on-going events. Modern applications consuming these streams need to extract behaviour patterns that can be obtained by aggregating and mining statically and dynamically huge event histories. An event is the notification that a happening of interest has occurred. Event streams must be combined or aggregated to produce more meaningful information. By combining and aggregating them either from multiple producers, or from a single one during a given period of time, a limited set of events describing meaningful situations may be notified to consumers. Event streams with their volume and continuous production cope mainly with two of the characteristics given to Big Data by the 5V’s model: volume & velocity. Techniques such as complex pattern detection, event correlation, event aggregation, event mining and stream processing, have been used for composing events. Nevertheless, to the best of our knowledge, few approaches integrate different composition techniques (online and post-mortem) for dealing with Big Data velocity. This chapter gives an analytical overview of event stream processing and composition approaches: complex event languages, services and event querying systems on distributed logs. Our analysis underlines the challenges introduced by Big Data velocity and volume and use them as reference for identifying the scope and limitations of results stemming from different disciplines: networks, distributed systems, stream databases, event composition services, and data mining on traces

A language and an execution model for the detection of active situations

This paper presents a thesis about a language and an execution model for the detection of situations aimed at reducing the complexity of active applications. This work has been motivated by the observation that in many cases, there is a gap between current tools that enable to react to a single event (following the ECA: Event – condition – action paradigm), and the reality, in which a single event may not require any reaction, however the reaction should be given to patterns over the event history. The concept of situation presented in this paper, extends the concept of composite event, in its expressive power, flexibility, and usability. This paper motivates the work, surveys other efforts in this are, and presents preliminary ideas for both the language and the execution model

A Framework for Executable Systems Modeling

Systems Modeling Language (SysML), like its parent language, the Unified Modeling Language (UML), consists of a number of independently derived model languages (i.e. state charts, activity models etc.) which have been co-opted into a single modeling framework. This, together with the lack of an overarching meta-model that supports uniform semantics across the various diagram types, has resulted in a large unwieldy and informal language schema. Additionally, SysML does not offer a built in framework for managing time and the scheduling of time based events in a simulation. In response to these challenges, a number of auxiliary standards have been offered by the Object Management Group (OMG); most pertinent here are the foundational UML subset (fUML), Action language for fUML (Alf), and the UML profile for Modeling and Analysis of Real Time and Embedded Systems (MARTE). However, there remains a lack of a similar treatment of SysML tailored towards precise and formal modeling in the systems engineering domain. This work addresses this gap by offering refined semantics for SysML akin to fUML and MARTE standards, aimed at primarily supporting the development of time based simulation models typically applied for model verification and validation in systems engineering. The result of this work offers an Executable Systems Modeling Language (ESysML) and a prototype modeling tool that serves as an implementation test bed for the ESysML language. Additionally a model development process is offered to guide user appropriation of the provided framework for model building

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

Modelling learning behaviour of intelligent agents using UML 2.0

This thesis aims to explore and demonstrate the ability of the new standard of structural and behavioural components in Unified Modelling Language (UML 2.0 / 2004) to model the learning behaviour of Intelligent Agents. The thesis adopts the research direction that views agent-oriented systems as an extension to object-oriented systems. In view of the fact that UML has been the de facto standard for modelling object-oriented systems, this thesis concentrates on exploring such modelling potential with Intelligent Agent-oriented systems. Intelligent Agents are Agents that have the capability to learn and reach agreement with other Agents or users. The research focuses on modelling the learning behaviour of a single Intelligent Agent, as it is the core of multi-agent systems. During the writing of the thesis, the only work done to use UML 2.0 to model structural components of Agents was from the Foundation for Intelligent Physical Agent (FIPA). The research builds upon, explores, and utilises this work and provides further development to model the structural components of learning behaviour of Intelligent Agents. The research also shows the ability of UML version 2.0 behaviour diagrams, namely activity diagrams and sequence diagrams, to model the learning behaviour of Intelligent Agents that use learning from observation and discovery as well as learning from examples of strategies. The research also evaluates if UML 2.0 state machine diagrams can model specific reinforcement learning algorithms, namely dynamic programming, Monte Carlo, and temporal difference algorithms. The thesis includes user guides of UML 2.0 activity, sequence, and state machine diagrams to allow researchers in agent-oriented systems to use the UML 2.0 diagrams in modelling the learning components of Intelligent Agents. The capacity for learning is a crucial feature of Intelligent Agents. The research identifies different learning components required to model the learning behaviour of Intelligent Agents such as learning goals, learning strategies, and learning feedback methods. In recent years, the Agent-oriented research has been geared towards the agency dimension of Intelligent Agents. Thus, there is a need to conduct more research on the intelligence dimension of Intelligent Agents, such as negotiation and argumentation skills. The research shows that behavioural components of UML 2.0 are capable of modelling the learning behaviour of Intelligent Agents while structural components of UML 2.0 need extension to cover structural requirements of Agents and Intelligent Agents. UML 2.0 has an extension mechanism to fulfil Agents and Intelligent Agents for such requirements. This thesis will lead to increasing interest in the intelligence dimension rather than the agency dimension of Intelligent Agents, and pave the way for objectoriented methodologies to shift more easily to paradigms of Intelligent Agent-oriented systems.The British Council, the University of Plymouth and the Arab-British Chamber Charitable Foundation

Understanding the Elements of Executable Architectures Through a Multi-Dimensional Analysis Framework

The objective of this dissertation study is to conduct a holistic investigation into the elements of executable architectures. Current research in the field of Executable Architectures has provided valuable solution-specific demonstrations and has also shown the value derived from such an endeavor. However, a common theory underlying their applications has been missing. This dissertation develops and explores a method for holistically developing an Executable Architecture Specification (EAS), i.e., a meta-model containing both semantic and syntactic information, using a conceptual framework for guiding data coding, analysis, and validation. Utilization of this method resulted in the description of the elements of executable architecture in terms of a set of nine information interrogatives: an executable architecture information ontology. Once the detail-rich EAS was constructed with this ontology, it became possible to define the potential elements of executable architecture through an intermediate level meta-model. The intermediate level meta-model was further refined into an interrogative level meta-model using only the nine information interrogatives, at a very high level of abstraction

OCL2Trigger: Deriving active mechanisms for relational databases using Model-Driven Architecture

16 pages, 10 figures.-- Issue title: "Best papers from the 2007 Australian Software Engineering Conference (ASWEC 2007), Melbourne, Australia, April 10-13, 2007, Australian Software Engineering Conference 2007".Transforming integrity constraints into active rules or triggers for verifying database consistency produces a serious and complex problem related to real time behaviour that must be considered for any implementation. Our main contribution to this work is to provide a complete approach for deriving the active mechanisms for Relational Databases from the specification of the integrity constraints by using OCL. This approach is designed in accordance with the MDA approach which consists of transforming the specified OCL clauses into a class diagram into SQL:2003 standard triggers, then transforming the standard triggers into target DBMS triggers. We believe that developing triggers and plugging them into a given model is insufficient because the behaviour of such triggers is invisible to the developers, and therefore not controllable. For this reason, a DBMS trigger verification model is used in our approach, in order to ensure the termination of trigger execution. Our approach is implemented as an add-in tool in Rational Rose called OCL2Trigger.This work is part of the "Software Process Management Platform: Modelling, reuse and measurement" TIN2004/07083 project.Publicad