Abstract
Na viragem do milénio, decorrentes sobretudo do Processo de Bolonha e da (r)evolução tecnológica, colocaram-se ao Ensino Superior e aos docentes vários desafios, nomeadamente os relacionados com questões pedagógicas. Tendo essa situação por referência, o artigo apresenta um estudo que analisou a produção académica em Portugal entre 2012-2021, pesquisada com recurso a diversas bases de dados e interpretada por técnicas de análise de frequência e de conteúdo. A análise evidenciou que: o número de artigos publicados em revistas indexadas ou em atas de conferências não foi tão expressivo como a urgência da reflexão que a temática merecia; o número de teses de doutoramento e dissertações de mestrado com foco nas questões pedagógicas no Ensino Superior foi relativamente reduzido; a metodologia desses trabalhos, embora distribuída entre procedimentos de orientação qualitativa, mista e quantitativa, teve menor expressão neste último tipo metodológico; muitos dos autores dos trabalhos académicos são do campo educacional, embora existam também autores de outras áreas científicas; a maior parte dos trabalhos académicos teve como foco a formação pedagógica dos docentes do Ensino Superior, a que se seguiram estudos relativos a práticas pedagógicas e a desafios colocados ao Ensino Superior. A par dessas conclusões, o estudo permitiu identificar limitações que justificam o seu aprofundamento, mas também recomendações para futuros trabalhos de investigação sobre essa temática.

Abstract
In the evolving landscape of global education, Artificial Intelligence's (AI) integration into Learning Management Systems (LMS) promises a transformative shift. This paper presents Mozambique's journey in this domain, comparing it with global advancements. While the Mozambican higher education sector stands at the cusp of a digital revolution, its engagement with AI in LMS remains foundational. This is juxtaposed against the global trend where AI tools, such as ChatGPT, are rapidly becoming standard in many educational platforms, enhancing personalization, efficiency, and data-driven insights. The benefits of AI integration, such as tailored learning experiences and administrative automation, are counterbalanced by challenges, including data privacy concerns and over-reliance on technology. Drawing from real-world case studies, the paper highlights pioneering endeavours that showcase AI's potential in reshaping educational paradigms. As Mozambique navigates its unique challenges, insights from global best practices offer a roadmap for harnessing the transformative potential of AI in LMS, aiming to elevate its higher education sector to new heights.;Na evolução da educação global, a integração da Inteligência Artificial (IA) nos Sistemas de Gestão de Aprendizagem (LMS) promete uma transformação significativa. Este artigo investiga a jornada de Moçambique neste domínio, comparando-a com os avanços globais. Enquanto o setor de ensino superior moçambicano está à beira de uma revolução digital, seu envolvimento com a IA em LMS ainda está em uma fase inicial. Isso é contrastado com a tendência global, onde ferramentas de IA, como o ChatGPT, estão rapidamente se a se tornar padrão em muitas plataformas educativas, aprimorando a personalização, eficiência e insights baseados em dados. Os benefícios da integração da IA, como experiências de aprendizagem adaptadas e automação administrativa, são equilibrados por desafios, incluindo preocupações com a privacidade dos dados e excesso de dependência da tecnologia. Através de estudos de caso do mundo real, o artigo destaca esforços pioneiros que mostram o potencial da IA em remodelar os paradigmas educacionais. Enquanto Moçambique navega pelos seus desafios únicos, os insights das melhores práticas globais oferecem um roteiro para aproveitar o potencial transformador da IA em SGA, com o objetivo de elevar seu setor de ensino superior a novos patamares.

Abstract

Abstract
Monitoring a system over time is as important as ever with the increasing use of cloud-native software architectures. This paper expands the set of patterns published in a previous paper (Liveness Endpoint, Readiness Endpoint and Synthetic Testing) with two solutions for supporting teams in diagnosing occurring issues — Deployment Tracking and Exception Tracking. These patterns advise tracking relevant events that occur in the system. The Deployment Tracking pattern provides means to limit the sources of an anomaly, and the Exception Tracking pattern makes a specific class of anomalies visible so that a team can act on them. Both patterns help practitioners identify the root cause of an issue, which is instrumental in fixing it. They can help even less experienced professionals to improve monitoring processes, and reduce the mean time to resolve problems with their application. These patterns draw on documented industry best practices and existing tools. In order to help the reader find other patterns that supplement the ones suggested in this study, relations to already-existing monitoring patterns are also examined.

Abstract
While Microservices are a preferred choice for modern cloud-based applications, the migration and architectural refactoring of existing legacy systems is still a major challenge in industry. To address this, academia has proposed many strategies and approaches that aim to automate the process of decomposing a monolith into functional units. In this study, we review existing migration approaches regarding techniques used and tool support. From 91 publications, we extracted 22 tools, 7 of which address service decomposition. To assess them from an end-user perspective, we investigated their underlying techniques, installation, documentation, usability and support. For 5 of them, we generated service cuts using reference applications. The results of our preliminary work suggest that the inspected tools pursue promising concepts, but lack maturity and generalizability for reliable use by industry.

Abstract
Service-based architecture is an approach that emerged to overcome software development challenges such as difficulty to scale, low productivity, and strong dependence between elements. Microservice, an architectural style that follows this approach, offers advantages such as scalability, agility, resilience, and reuse. This architectural style has been well accepted and used in industry and has been the target of several academic studies. However, analyzing the state-of-the-art and -practice, we can notice a fuzzy limit when trying to classify and characterize the architecture of service-based systems. Furthermore, it is possible to realize that it is difficult to analyze the trade-offs to make decisions regarding the design and evolution of this kind of system. Some concrete examples of these decisions are related to how big the services should be, how they communicate, and how the data should be divided/shared. Based on this context, we developed the CharM, a model for characterizing the architecture of service-based systems that adopts microservices guidelines. To achieve this goal, we followed the guidelines of the Design Science Research in five iterations, composed of an ad-hoc literature review, discussions with experts, two case studies, and a survey. As a contribution, the CharM is an easily understandable model that helps professionals with different profiles to understand, document, and maintain the architecture of service-based systems.& COPY; 2023 Elsevier Inc. All rights reserved.