Ontology-based feature modeling: an empirical study in changing scenarios

A software product line (SPL) is a set of software systems that have a particular set of common features\ud and that satisfy the needs of a particular market segment or mission. Feature modeling is one of the key\ud activities involved in the design of SPLs. The feature diagram produced in this activity captures the commonalities\ud and variabilities of SPLs. In some complex domains (e.g., ubiquitous computing, autonomic\ud systems and context-aware computing), it is difficult to foresee all functionalities and variabilities a\ud specific SPL may require. Thus, Dynamic Software Product Lines (DSPLs) bind variation points at runtime\ud to adapt to fluctuations in user needs as well as to adapt to changes in the environment. In this context,\ud relying on formal representations of feature models is important to allow them to be automatically analyzed\ud during system execution. Among the mechanisms used for representing and analyzing feature\ud models, description logic (DL) based approaches demand to be better investigated in DSPLs since it provides\ud capabilities, such as automated inconsistency detection, reasoning efficiency, scalability and\ud expressivity. Ontology is the most common way to represent feature models knowledge based on DL reasoners.\ud Previous works conceived ontologies for feature modeling either based on OWL classes and properties\ud or based on OWL individuals. However, considering change or evolution scenarios of feature\ud models, we need to compare whether a class-based or an individual-based feature modeling style is\ud recommended to describe feature models to support SPLs, and especially its capabilities to deal with\ud changes in feature models, as required by DSPLs. In this paper, we conduct a controlled experiment to\ud empirically compare two approaches based on each one of these modeling styles in several changing scenarios\ud (e.g., add/remove mandatory feature, add/remove optional feature and so on). We measure time to\ud perform changes, structural impact of changes (flexibility) and correctness for performing changes in our\ud experiment. Our results indicate that using OWL individuals requires less time to change and is more\ud flexible than using OWL classes and properties. These results provide insightful assumptions towards\ud the definition of an approach relying on reasoning capabilities of ontologies that can effectively support\ud products reconfiguration in the context of DSPL.CNPqCAPE

A computational model for the construction of adaptive and semantic educational systems.

A presente pesquisa está relacionada à concepção e construção de sistemas educacionais mediados por computador dotados de adaptatividade e baseados na Web semântica, integrando técnicas e tecnologias provenientes da Inteligência Artifical e Web Semântica. Nesse sentido, esta tese apresenta uma solução para viabilizar a construção efetiva dos sistemas em pauta, consistindo especificamente na integração de ontologias, agentes e serviços semânticos. Para tanto, foram estabelecidos os seguintes objetivos: 1) propor um modelo conceitual para construção de tais ambientes educacionais; 2) propor e implementar um modelo computacional baseado em ontologias, agentes e serviços semânticos e 3) propor e implementar um modelo de infraestrutura para interoperabilidade entre aplicações educacionais. Para avaliação da proposta foram definidos três estudos de casos, abrangendo os domínios de Matemática e Medicina. Os resultados alcançados mostraram-se adequados, tendo como contribuição a concepção e desenvolvimento de tais modelos, as quais correspondem: i) à proposição dos modelos para ambientes educacionais adaptativos e semânticos; ii) à garantia do desenvolvimento e manutenção de ambientes educacionais adaptativos e semânticos de forma mais fácil; iii) à possibilidade de produção em larga escala de tais ambientes e para as diversas áreas do conhecimento e iv) à possibilidade de permitir que instituições de ensino possam cooperar na produção de materiais educacionais e no acesso aos estudantes que necessitem deste tipo de tecnologia, tanto no Brasil quanto em outros países.This research examines the design and effective development of adaptive and semantic Web-based educational systems, integrating artificial intelligence techniques and semantic Web-based technologies. In this sense, this research presents a solution in order to ensure the effective construction of such educational systems, which means the integration of ontologias, agents and semantic Web services. As a consequence, the following goals are 1) to propose a conceptual model to build such educational environments; 2) to propose and to implement a computational model based on ontologies, agents, and semantic Web services; 3) to propose and to implement an interoperability model between edudational applications. Moreover, results obtained from three case studies (within Math and Medicine domains) are provided to evaluate the feasability of the thesis. The outcomes achieved were the conception and development of such models and the contributions are summarized as follows: i) the proposition of models to adaptive and semantic Web-based educational environments; ii) to ensure the development and maintenance of such educational sysems in an easy way; iii) to provide an structure to large-scale production of such environments and to different domains and iv) to provide the capability for universities to cooperate in the production of learning resources and access to students who needs this kind of technology as in Brazil as in abroad