Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia. The main objective was to develop a new Adaptive Educational Hypermedia System based on Honey and Mumford learning style model (AEHS-H&M) and assess the effect of adapting educational materials individualized to the student's learning style. To achieve the main objectives, a case study was developed. An experiment between two groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions was designed to evaluate the new approach of matching learning materials with learning styles and their influence on student's learning achievement. The findings support the use of learning styles as guideline for adaptation into the adaptive e-learning hypermedia systems.

In Model-Driven Engineering, analogously to any software artifact, metamodels are equally prone to evolution. When a metamodel undergoes modifications, all the related artifacts must be accordingly adapted in order to remain valid. Manual co-evolution of models after these metamodel changes is error-prone. In this setting, this paper introduces a semiautomatic process for the co-evolution of models after metamodel evolution. The process is divided in four main stages: at the differencing stage, the changes to the metamodel are detected. After that these changes are linked with the original model elements and represented in a weaving model which serves to generate a transformation used in the last stage in order to obtain the evolved model. Contributions of this paper include the automatic co-evolution of breaking and resolvable changes and the assistance to the model developer in the co-evolution of breaking and un-resolvable changes.

Model Driven Software Engineering has matured over the last few years and is now becoming an established technology. As a consequence dealing with evolving metamodels and the necessary co-evolution of instances of this metamodel is becoming increasingly important. Several approaches have been proposed to solve model co-evolution problem. In this paper, Firstly, existing approaches in this area are analyzed to define requirements of our approach, namely automaticity, reuse, expressiveness and intelligence. After that we present a new approach CBRMig towards a solution to metamodel and model co-evolution problem. The core of our proposal is using a case based reasoning system that automates the process of creation and selection of cases to assist with the generation of a migration algorithm used for adapting models in response to metamodel evolution.

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Composing an application out of independent, reusable pieces has been a key challenge since the early days of software engineering. In this paper we examine some aspects of software architecture. We introduce our COSA+ model built in order to provide some enhancement in the COSA 1 one. Our main contributions are the new structure given to an explicit connector, and the conceptual view of the different abstract levels used to define the applications architectures. Profits expected from these improvements are numerous; mainly we can quote the reduction of the production costs and the time to market, simplify the maintenance operations, and foresee supports for the evolution of the software architecture.