Generic Model Refactorings

Many modeling languages share some common concepts and principles. For example, Java, MOF, and UML share some aspects of the concepts\ud of classes, methods, attributes, and inheritance. However, model\ud transformations such as refactorings specified for a given language\ud cannot be readily reused for another language because their related\ud metamodels may be structurally different. Our aim is to enable a\ud flexible reuse of model transformations across various metamodels.\ud Thus, in this paper, we present an approach allowing the specification\ud of generic model transformations, in particular refactorings, so\ud that they can be applied to different metamodels. Our approach relies\ud on two mechanisms: (1) an adaptation based mainly on the weaving\ud of aspects; (2) the notion of model typing, an extension of object\ud typing in the model-oriented context. We validated our approach by\ud performing some experiments that consisted of specifying three well\ud known refactorings (Encapsulate Field, Move Method, and Pull Up Method)\ud and applying each of them onto three different metamodels (Java,\ud MOF, and UML)

Simulation of complex environments:the Fuzzy Cognitive Agent

The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit

A Conceptual Framework for Adapation

This paper presents a white-box conceptual framework for adaptation that promotes a neat separation of the adaptation logic from the application logic through a clear identification of control data and their role in the adaptation logic. The framework provides an original perspective from which we survey archetypal approaches to (self-)adaptation ranging from programming languages and paradigms, to computational models, to engineering solutions

A Conceptual Framework for Adapation

This paper presents a white-box conceptual framework for adaptation that promotes a neat separation of the adaptation logic from the application logic through a clear identification of control data and their role in the adaptation logic. The framework provides an original perspective from which we survey archetypal approaches to (self-)adaptation ranging from programming languages and paradigms, to computational models, to engineering solutions

A Conceptual Framework for Adapation

We present a white-box conceptual framework for adaptation. We called it CODA, for COntrol Data Adaptation, since it is based on the notion of control data. CODA promotes a neat separation between application and adaptation logic through a clear identification of the set of data that is relevant for the latter. The framework provides an original perspective from which we survey a representative set of approaches to adaptation ranging from programming languages and paradigms, to computational models and architectural solutions

Event-driven Adaptation in COP

Context-Oriented Programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented language with two-components: a declarative constituent for programming the context and a functional one for computing. This paper describes an extension of ML_CoDa to deal with adaptation to unpredictable context changes notified by asynchronous events.Comment: In Proceedings PLACES 2016, arXiv:1606.0540