Debugging multi-agent systems, which are concurrent, distributed, and consist of complex components is difficult, yet crucial. The development of these complex systems is supported by agent-oriented software engineering methodologies which utilise agents as the central design metaphor. The systems that are developed are inherently complex since the components of these systems may interact in flexible and sophisticated ways and traditional debugging techniques are not appropriate. Despite this, very little effort has been applied to developing appropriate debugging tools and techniques. Debugging multi-agent systems without good debugging tools is highly impractical and without suitable debugging support developing and maintaining multi-agent systems will be more difficult than it need be. In this thesis we propose that the debugging process can be supported by following an agent-oriented design methodology, and then using the developed design artifacts in the debugging phase. We propose a domain independent debugging framework which comprises the developed processes and components that are necessary in using design artifacts as debugging artifacts. Our approach is to take a non-formal design artifact, such as an AUML protocol design, and encode it in a machine interpretable manner such that the design can be used as a model of correct system behaviour. These models are used by a run-time debugging system to compare observed behaviour against specified behaviour. We provide details for transforming two design artifact types into equivalent debugging artifacts and show how these can be used to detect bugs. During a debugging episode in which a bug has been identified our debugging approach can provide detailed information about the possible reason for the bug occurring. To determine if this information was useful in helping to debug programs we undertook a thorough empirical study and identified that use of the debugging tool translated to an improvement in debugging performance. We conclude that the debugging techniques developed in this thesis provide effective debugging support for multi-agent systems and by having an extensible framework new design artifacts can be explored and as translations are developed they can be added to the debugging system.

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-05-27T13:31:09Z No. of bitstreams: 1 adaptacao_conteudos.pdf: 1461923 bytes, checksum: 1272ba554f9ec06de579b9f337be5ff5 (MD5) / Made available in DSpace on 2015-05-27T13:31:09Z (GMT). No. of bitstreams: 1 adaptacao_conteudos.pdf: 1461923 bytes, checksum: 1272ba554f9ec06de579b9f337be5ff5 (MD5) Previous issue date: 2011 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Os objetos de aprendizagem (OAs) têm tomado um papel importante no contexto educacional atual, onde os meios computacionais se tornam cada vez mais presentes em sala de aula impulsionados por instituições governamentais. Dentre as características necessárias para utilização efetiva dos OAs a bibliografia enumera dois pontos principais, o reuso e o compartilhamento. Com o avanço de novos meios computacionais o conceito de reuso tem adquirido novas proporções vislumbrando a utilização do conteúdo educacional disponibilizado pelos OAs em diversos ambientes computacionais. Dentre estes novos ambientes computacionais, os dispositivos móveis e a televisão digital (TVD) estendem o conceito de e-learning criando duas novas vertentes, são elas o m-learning e t-learning respectivamente. Apesar disso, os OAs criados para os ambientes de e-learning dificilmente podem ser reutilizados nos novos ambientes devido às dificuldades de apresentação de conteúdo nos dispositivos móveis e de TVD. Para dar apoio à visualização de OAs nestes novos ambientes o presente trabalho apresenta conceitos relacionados à OAs, a TVD e aos agentes de software para basear a análise do sistema multiagentes desenvolvido. Este sistema tem como principal funcionalidade a adaptação de conteúdo para os ambientes de t-learning e m-learning. A intenção do presente trabalho é apresentar uma arquitetura, utilizando diagramas da Agent UML, que comporte a adaptação de OAs para que possam ser visualizados em múltiplos ambientes e aplicar esta arquitetura a casos de uso voltados à televisão digital. Através do sistema desenvolvido foi possível adaptar múltiplos formatos de conteúdos de OAs para que sejam visualizados nos dispositivos do Sistema Brasileiro de Televisão Digital (SBTVD). / Learning Objects (LO) are assuming an important role in current educational context, where computational resources are a common presence in the classroom due to government incentives. Among the needed characteristics for right using of LOs by teachers and students, two main aspects are highlighted by the literature, the reusing and sharing. With the advances in the new computing environments the concept of reusing has been taking new proportions viewing the utilization of its educational content in several computing environments. Among these new computing environments, the mobile devices and the digital television (DTV) extends the concept of e-learning creating two new strands, they are the m-learning and t-learning respectively. Nevertheless, the LOs created for e-learning environment hardly can be used in the new environments due to the difficulties of presenting on mobile and DTV devices. To help the presenting of LOs in these new environments this work presents concepts related to LOs, DTV and agents based software aiming the analysis of a multiagent system developed. This system has as your main feature the adaptation of content for t-learning and m-learning environments. The intention of this work is present an architecture, using Agent UML (AUML) diagrams, that supports the LOs adaptation for viewing in multiple environments and apply this architecture to digital television use cases. Through the system developed should be possible to adapt multiple LOs content formats to be viewed on the devices of the Brazilian System of Digital Television (SBTVD).