Introducing Context-Awareness in Applications by Transforming High-Level Rules

International audienceIn the last years, we have witnessed the increase in the popu- larity and capabilities of mobile technologies. This evolution has enforced the idea of smart environments, in which devices are aware and able to react to changes in their environment. In this position paper we describe a specific approach for the development of context-aware software. We propose to make existing applications context-aware by means of three main components: context models, high-level rules and code-generation processors. We present each component and analyze the issues related to the development of context-aware software following this strategy

Model Refactorings through Rule-Based Inconsistency

The goal of model-driven engineering is to raise the level of abstraction by shifting the focus to models. As a result, complex software development activities move to the modelling level as well. One such activity is model refactoring, a technique for restructuring the models in order to improve some quality attributes of the models. As a first contribution of this paper, we argue and show that refactoring a model is enabled by inconsistency detection and resolution. Inconsistencies in or between models occur since models typically describe a software system from different viewpoints and on different levels of abstraction. A second contribution of this paper is rule-based inconsistency resolution, which enables reuse of different inconsistency resolutions across model refactorings and manages the flow of inconsistency resolution steps automatically

Using reflective logic programming to describe domain knowledge as an aspect

Software applications, mostly consisting of an algorithm applied to domain knowledge, are hard to maintain and to reuse as a result of their hard coded combination. We propose to follow the principles of aspect-oriented programming, separating the domain from the algorithm and describing them in a logic and conventional programming language respectively. In this paper, we report on an experiment that was conducted to validate this hypothesis, and to investigate the requirements of a programming environment for this configuration. An already existing environment that uses a logic meta-language to reason about objectoriented systems, SOUL, is used as a starting point for this experiment. The result is a working implementation in SOUL, which validates our ideas, reveals mechanisms that require more research, and points to other features that should be included.SCOPUS: cp.kinfo:eu-repo/semantics/publishe

Multi-Objective Genetic Algorithm for Task Assignment on Heterogeneous Nodes

Task assignment in grid computing, where both processing and bandwidth constraints at multiple heterogeneous devices need to be considered, is a challenging problem. Moreover, targeting the optimization of multiple objectives makes it even more challenging. This paper presents a task assignment strategy based on genetic algorithms in which multiple and conflicting objectives are simultaneously optimized. Specifically, we maximize task execution quality while minimizing energy and bandwidth consumption. Moreover, in our video processing scenario; we consider transcoding to lower spatial/temporal resolutions to tradeoff between video quality; processing, and bandwidth demands. The task execution quality is then determined by the number of successfully processed streams and the spatial-temporal resolution at which they are processed. The results show that the proposed algorithm offers a range of Pareto optimal solutions that outperforms all other reference strategies

ERCIM Symposium on Software Evolution 2007

Proceedings of the Third International ERCIM Symposium on Software Evolution - EVOL 200