Abstract
A Learning management system (LMS) is considered appropriate for company training. It is increasingly used in companies or organizations as a tool to manage their online training. The company or organization should consider the implementation of an LMS that provides ease in training content selection to achieve the best use and satisfaction of its employees in the learning process. From this perspective, the present study aims to investigate the implementation of a personalized LMS to facilitate the formative content selection tailored to employees’ roles. A Survey research methodology was used to achieve this objective. Based on the literature and survey results, we propose an approach to reach the personalization of content selection.

Abstract
Training employees in organizations is essential for enhancing productivity and profitability, updating their knowledge, and better preparing them for market demands. Through digital platforms (LMS) and the e-Learning method, training occurs in web-based environments, enabling content management and accessibility across multiple devices. e-Learning typically follows a modular structure, ensuring adaptability, flexibility, and asynchronous learning. This study applies to the Design Science Research method to implement a data protection training course via an LMS, facilitating knowledge dissemination and employee self-assessment. The organization faces challenges in rapidly spreading knowledge due to its widespread locations, diverse working hours, and geographical constraints. The study evaluates training dissemination through microlearning, leveraging Moodle (LMS) and Digital Storytelling techniques. Additionally, it assesses the pedagogical and engagement aspects to ensure training is efficient, standardized, flexible, and more appealing to employees, increasing their receptivity and interest.

Abstract
Software businesses are continuously increasing their presence in the cloud. While cloud computing is not a new research topic, designing software for the cloud is still challenging, requiring engineers to invest in research to become proficient at working with it. Design patterns can be used to facilitate cloud adoption, as they provide valuable design knowledge and implementation guidelines for recurrent engineering problems. This work introduces a pattern language for designing software for the cloud. We believe developers can significantly reduce their R&D time by adopting these patterns to bootstrap their cloud architecture. The language comprises 10 patterns, organized into four categories: Automated Infrastructure Management, Orchestration and Supervision, Monitoring, and Discovery and Communication.

Abstract
General-purpose AI-assisted tools, such as ChatGPT, have recently gained much attention from the media and the general public. That raised questions about in which tasks we can apply such a tool. A good code design is essential for agile software development to keep it ready for change. In this context, identifying which design pattern can be appropriate for a given scenario can be considered an advanced skill that requires a high degree of abstraction and a good knowledge of object orientation. This paper aims to perform an exploratory study investigating the effectiveness of an AI-assisted tool in assisting developers in choosing a design pattern to solve design scenarios. To reach this goal, we gathered 56 existing questions used by teachers and public tenders that provide a concrete context and ask which design pattern would be suitable. We submitted these questions to ChatGPT and analyzed the answers. We found that 93% of the questions were answered correctly with a good level of detail, demonstrating the potential of such a tool as a valuable resource to help developers to apply design patterns and make design decisions.

Abstract
As organizations increasingly transition from monolithic systems to microservices, they aim to achieve higher availability, automatic scaling, simplified infrastructure management, enhanced collaboration, and streamlined deployments. However, this migration process remains largely manual and labour-intensive. While existing literature offers various strategies for decomposing monoliths, these approaches primarily focus on architecture-level guidance, often overlooking the code-level challenges and dependencies that developers must address during the migration. This article introduces a catalogue of seven refactorings specifically designed to support the transition to a microservices architecture with a focus on handling dependencies. The catalogue provides developers with a systematic guide that consolidates refactorings identified in the literature and addresses the critical gap in systematizing the process at the code level. By offering a structured, step-by-step approach, this work simplifies the migration process and lays the groundwork for its potential automation, empowering developers to implement these changes efficiently and effectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
Service-based architectures provide substantial benefits, yet service orchestration remains a challenge, particularly for newcomers. While various resources on orchestration techniques exist, they often lack clarity and standardization, making best practices difficult to implement and limiting their adoption within the software industry. To address this gap, we analyzed existing literature and tools to identify common orchestration practices. Based on our findings, we define three key orchestration resource optimization patterns: Preemptive Scheduling, Service Balancing, and Garbage Collection. Preemptive Scheduling allows the allocation of sufficient resources for services of higher priority in stressful situations, while Service Balancing enables a restructuring of the nodes to allow better resource usage. To end, Garbage Collection creates cleanup mechanisms to better understand the system’s resource usage and optimize it. These patterns serve as foundational elements for improving orchestration practices and fostering broader adoption in service-based architectures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.