Centralised architecture models are often adopted in the development of smart cities to take advantage of the technologies provided by dominant companies such as Google, Meta, and Amazon. This approach often comes with significant drawbacks, such as (i) application developers becoming dependent on the policies and rules imposed by large companies, which are subject to change, and (ii) users having their data collected and used haphazardly, and often without authorisation, which can undermine the trust that users place in the solution. Infrastructure for smart cities should, therefore, incorporate decentralised technologies that satisfy or reinforce important quality attributes such as trustworthiness, privacy, and security. The main objective of this article is to survey and discuss how the services of a smart city can be implemented using decentralised architectures; we explain the advantages and disadvantages of decentralised architectures and emerging technologies. We review the specialised literature and compile a set of emerging technologies that are essential to conceive a decentralised architectural solution for smart cities. The current state-of-the-art in decentralisation shows that this model can be implemented with current technologies and help to satisfy the quality attributes mentioned above, and potentially reinforce the degree of trustworthiness of the solution. We also propose a four-dimension guideline that functions as a conceptual driver for structuring actions for researchers, system architects, policymakers, and city authorities in the design, evaluation, and long-term maintenance of decentralised smart cities, thereby enhancing their capacity to address escalating urban challenges. We conclude that the set of technologies discussed in this article has the potential to be reused and replicated across smart cities. • Choice between C-architecture and D-architecture for smart cities. • Concerns about interoperability, privacy, vendor lock-in, and sustainability. • Decentralisation offers improved interoperability, privacy, and sustainability. • Approach to decentralised digital identity, permissions, and integration solutions.

Background: The rapid adoption of Large Language Models (LLMs) in software engineering, such as in customer service chatbots, has brought substantial benefits but also significant risks. Biased, inappropriate, or harmful responses may occur when integrating LLMs as commercial off-the-shelf (COTS) components into user-facing applications. Aims: This paper aims to present emerging results from an exploratory study that compares commercial guardrail frameworks, assessing their effectiveness in filtering inappropriate content during chat interactions. Method: We empirically evaluated three guardrail frameworks LLM Guard, Llama Guard, and OpenAI Moderation - using two datasets containing toxic and offensive content. Results: The frameworks achieved high accuracy for one dataset (over 90%) but underperformed in other metrics, indicating that toxic or dangerous content could still reach users in certain scenarios, such as deployment in chatbots. Conclusions: These findings$h$ighlight$t$he$n$eed$f$or further improvements in guardrail frameworks and provide insights for researchers and practitioners to support the selection of appropriate solutions for enhancing harm mitigation in LLMbased applications.

Modeling and Simulation (M&S) is a fundamental approach for engineering disruptive solutions, widely applied in critical domains such as aerospace, military, healthcare, traffic, and energy.These domains often exhibit high complexity, uncertainty, and nonlinearity, making simulation and visualization particularly challenging.While M&S allows for the evaluation and analysis of innovative systems, enhancing the experience for analysts and engineers through complementary tools is crucial for improving realism, accuracy, and trustworthiness.In this paper, we present preliminary results on the development of a framework that integrates M&S with advanced visualization capabilities.Our approach bridges the Discrete-Event System Specification (DEVS) formalism with the Unity engine to provide a realistic graphical representation of simulations.By leveraging a Large Language Model (LLM) trained for this purpose, we automatically generate both simulation and animation codes, ensuring synchronized execution.The generated models exchange data, with the simulator serving as the computational engine and Unity as the visualization platform.Additionally, we provide a library of pre-defined simulation models for reuse in various domains.This integration enhances the interpretability of simulations, offering a more intuitive and immersive experience for system analysis.

Teaching (and also learning) software architecture is often challenging since it requires a high degree of abstraction from the students besides talent and creativity of the instructors. Given that context, flipped classroom (FC) has emerged as an approach with potential to reinforce software architecture learning. FC learning promotes a greater immersion in a topic than traditional teaching, improving student engagement, interaction and cooperation by offering students the content before the classroom. Despite the FC popularity and its potential to enhance software architecture learning, studies on the use of it in software architecture teaching are still scarce. The main contribution of this paper is then presenting results on the adoption of FC applied to software architecture teaching. A case study involving a lesson on software architecture inside a course on Internet of Things was taught to a control group (19 people taught using traditional method) and to a treatment group (54 people taught using flipped classroom). Results reveal that the treatment group (who received the intervention via the FC), had a significant better (i) assimilation of content (73.1% of the students acquired most of the content according to the applied assessment), (ii) easiness of abstraction (81.2% of students declared that understood the essential concepts), and also (iii) satisfaction with the technique (78.07% of the students were satisfied about the approach). Conversely, the application of traditional method revealed (i) a lower degree of content assimilation (only 19.1% retained most of the applied content), (ii) only 39.9 % of the students understood the fundamental concepts, and (iii) only 25.87% of the students were satisfied and feeling confident about the content learned.

Abstract Systems-of-Systems (SoS) combine heterogeneous, independent systems to offer complex functionalities for highly dynamic smart applications. Besides their dynamic architecture with continuous changes at runtime, SoS should be reliable and work without interrupting their operation and with no failures that could cause accidents or losses. SoS architectural design should facilitate the prediction of the impact of architectural changes and potential failures due to SoS behavior. However, existing approaches do not support such evaluation. Hence, these systems have been usually built without a proper evaluation of their architecture. This article presents Dynamic-SoS, an approach to predict/anticipate at design time the SoS architectural behavior at runtime to evaluate whether the SoS can sustain their operation. The main contributions of this approach comprise: (i) characterization of the dynamic architecture changes via a set of well-defined operators; (ii) a strategy to automatically include a reconfiguration controller for SoS simulation; and (iii) a means to evaluate architectural configurations that an SoS could assume at runtime, assessing their impact on the viability of the SoS operation. Results of our case study reveal Dynamic-SoS is a promising approach that could contribute to the quality of SoS by enabling prior assessment of its dynamic architecture.

English learning comprises the development of four abilities: listening, speaking, reading, and writing. Commonly, English teachers use songs to develop students' listening because it provides a fun approach for improving vocabulary and perceiving different accents. However, every time a teacher needs to prepare a listening lesson using songs, s/he needs to search for songs that contain the words that are being studied in that lesson, and also download and edit the lyrics, substituting the words by blank spaces to be filled by the students while they listen to the music. This paper presents the application of Information Retrieval (IR) techniques to index and retrieve songs according to a set of intended words, besides a module that prepares the songs for listening lessons, substituting the terms by blank spaces. Results reveal that the tool is well-succeeded to provide the aforementioned functionalities. Moreover, a teacher used the tool in the context of her English class, approving the solution provided and contributing to reduce the effort for preparing a pedagogical activity for a listening lesson.