arXiv subjects

Fernando Brito e Abreu

Publications and source records attributed to Fernando Brito e Abreu.

18 recordsLinked to original sources

arXiv2026

Evaluating the Health of Open-Source Smart City Platforms

To manage the complexity of smart cities, a variety of smart city platforms (SCPs), both proprietary and open-source, have been proposed. Typically acting as middleware between IoT devices at a lower layer and smart services at a higher layer, these platforms simplify the management of smart cities by reifying a variety of requirements common to different municipalities. Open-source software (OSS) is typically free of charge, making open-source SCPs an attractive option for municipalities with smaller budgets that still wish to improve efficiency and quality of life for residents and visitors. Furthermore, using an OSS SCP promotes digital sovereignty, since municipalities can control where the data will reside and will be less prone to vendor lock-in. A lack of support for OSS hinders its adoption by municipalities' IT teams, often with scarce technical resources. An active (aka "healthy") ecosystem, including well-orchestrated developers and users, the availability of installation and user manuals, non-vulnerable and documented code, test batteries, and other artifacts, is an important decision factor before adopting an OSS SCP. In this paper, we evaluate different open-source SCPs using the concept of "OSS health", covering several of the aforementioned characteristics.

cs.SE↗

arXiv2025

Plataforma para visualização geo-temporal de apinhamento turístico

Tourist crowding degrades the visitor experience and negatively impacts the environment and the local population, potentially making tourism in popular destinations unsustainable. This motivated us to develop, within the framework of the European RESETTING project related to the digital transformation of tourism, a platform to visualize this crowding, exploring historical data, detecting patterns and trends and predicting future events. The ultimate goal is to support short- and medium-term decision-making to mitigate the phenomenon. To this end, the platform takes into account the carrying capacity of the target sites when calculating crowding density. The integration of data from different sources is achieved with an extensible, connector-based architecture. Three scenarios for using the platform are described, relating to major annual crowding events. Two of them, in the municipality of Lisbon, are based on data from a mobile network provided by the LxDataLab initiative. The third, in Melbourne, Australia, using public data from a network of movement sensors called the Pedestrian Counting System. An experiment to evaluate the usability of the proposed platform using NASA-TLX is also described. -- -- O apinhamento turístico degrada a experiência dos visitantes e impacta negativamente o ambiente e a população local, podendo tornar insustentável o turismo em destinos populares. Isto motivou-nos a desenvolver, no âmbito do projeto europeu RESETTING relacionado com a transformação digital do turismo, uma plataforma para visualizar este apinhamento, explorando dados históricos, detetando padrões e tendências e prevendo eventos futuros. O objetivo final é apoiar a tomada de decisão, a curto e médio prazo, para mitigar o fenómeno. Para tal, a plataforma considera a capacidade de carga dos locais alvo no cálculo da densidade de apinhamento. A integração de dados de diversas fontes é conseguida com uma arquitetura extensível, à base de conetores. São descritos três cenários de utilização da plataforma, relativos a eventos anuais de grande apinhamento. Dois deles, no município de Lisboa, baseados em dados de uma rede móvel disponibilizados pela iniciativa LxDataLab. O terceiro, em Melbourne na Austrália, utilizando dados públicos de uma rede de sensores de movimento designada de Pedestrian Counting System. É ainda descrita uma experiência de avaliação da usabilidade da plataforma proposta, usando o NASA-TLX.

cs.HC↗

arXiv2025

Digital twins in tourism: a systematic literature review

Purpose: This systematic literature review (SLR) characterizes the current state of the art on digital twinning (DT) technology in tourism-related applications. We aim to evaluate the types of DTs described in the literature, identifying their purposes, the areas of tourism where they have been proposed, their main components, and possible future directions based on current work. Design/methodology/approach: We conducted this SLR with bibliometric analysis based on an existing, validated methodology. Thirty-four peer-reviewed studies from three major scientific databases were selected for review. They were categorized using a taxonomy that included tourism type, purpose, spatial scale, data sources, data linkage, visualization, and application. Findings: The topic is at an early, evolving stage, as the oldest study found dates back to 2021. Most reviewed studies deal with cultural tourism, focusing on digitising cultural heritage. Destination management is the primary purpose of these DTs, with mainly site-level spatial scales. In many studies, the physical-digital data linkage is unilateral, lacking twin synchronization. In most DTs considered bilateral, the linkage is indirect. There are more applied than theoretical studies, suggesting progress in applying DTs in the field. Finally, there is an extensive research gap regarding DT technology in tourism, which is worth filling. Originality/Value: This paper presents a novel SLR with a bibliometric analysis of DTs' applied and theoretical application in tourism. Each reviewed publication is assessed and characterized, identifying the current state of the topic, possible research gaps, and future directions.

cs.CY↗

arXiv2024

Smart ETL and LLM-based contents classification: the European Smart Tourism Tools Observatory experience

Purpose: Our research project focuses on improving the content update of the online European Smart Tourism Tools (STTs) Observatory by incorporating and categorizing STTs. The categorization is based on their taxonomy, and it facilitates the end user's search process. The use of a Smart ETL (Extract, Transform, and Load) process, where \emph{Smart} indicates the use of Artificial Intelligence (AI), is central to this endeavor. Methods: The contents describing STTs are derived from PDF catalogs, where PDF-scraping techniques extract QR codes, images, links, and text information. Duplicate STTs between the catalogs are removed, and the remaining ones are classified based on their text information using Large Language Models (LLMs). Finally, the data is transformed to comply with the Dublin Core metadata structure (the observatory's metadata structure), chosen for its wide acceptance and flexibility. Results: The Smart ETL process to import STTs to the observatory combines PDF-scraping techniques with LLMs for text content-based classification. Our preliminary results have demonstrated the potential of LLMs for text content-based classification. Conclusion: The proposed approach's feasibility is a step towards efficient content-based classification, not only in Smart Tourism but also adaptable to other fields. Future work will mainly focus on refining this classification process.

cs.IR↗

arXiv2024

A Carrying Capacity Calculator for Pedestrians Using OpenStreetMap Data: Application to Urban Tourism and Public Spaces

Determining the carrying capacity of urban tourism destinations and public spaces is essential for sustainable management. This paper presents an online tool that calculates pedestrian carrying capacities for user-defined areas based on OpenStreetMap (OSM) data. The tool considers physical, real, and effective carrying capacities by incorporating parameters such as area per pedestrian, rotation factor, corrective factors, and management capacity. The carrying capacity calculator aids in balancing environmental, economic, social, and experiential factors to prevent overcrowding and preserve the quality of life for residents and visitors. This tool is particularly useful for tourism destination management, urban planning, and event management, ensuring positive visitor experiences and sustainable infrastructure development. We detail the implementation of the calculator, its underlying algorithm, and its application to the Santa Maria Maior parish in Lisbon, highlighting its effectiveness in managing urban tourism and public spaces.

cs.CY↗

arXiv2024

Preserving Automotive Heritage: A Blockchain-Based Solution for Secure Documentation of Classic Cars Restoration

Classic automobiles are an important part of the automotive industry and represent the historical and technological achievements of certain eras. However, to be considered masterpieces, they must be maintained in pristine condition or restored according to strict guidelines applied by expert services. Therefore, all data about restoration processes and other relevant information about these vehicles must be rigorously documented to ensure their verifiability and immutability. Here, we report on our ongoing research to adequately provide such capabilities to the classic car ecosystem. Using a design science research approach, we have developed a blockchain-based solution using Hyperledger Fabric that facilitates the proper recording of classic car information, restoration procedures applied, and all related documentation by ensuring that this data is immutable and trustworthy while promoting collaboration between interested parties. This solution was validated and received positive feedback from various entities in the classic car sector. The enhanced and secured documentation is expected to contribute to the digital transformation of the classic car sector, promote authenticity and trustworthiness, and ultimately increase the market value of classic cars.

cs.CY↗

arXiv2024

Towards a Consensual Definition for Smart Tourism and Smart Tourism Tools

Smart tourism (ST) stems from the concepts of e-tourism - focused on the digitalization of processes within the tourism industry, and digital tourism - also considering the digitalization within the tourist experience. The earlier ST references found regard ST Destinations and emerge from the development of Smart Cities. Our initial literature review on the ST concept and Smart Tourism Tools (STT) revealed significant research uncertainties: ST is poorly defined and frequently linked to the concept of Smart Cities; different authors have different, sometimes contradictory, views on the goals of ST; STT claims are often only based on technological aspects, and their "smartness" is difficult to evaluate; often the term "Smart" describes developments fueled by cutting-edge technologies, which lose that status after a few years. This chapter is part of the ongoing initiative to build an online observatory that provides a comprehensive view of STTs' offerings in Europe, known as the European STT Observatory. To achieve this, the observatory requires methodologies and tools to evaluate "smartness" based on a sound definition of ST and STT, while also being able to adapt to technological advancements. In this chapter, we present the results of a participatory approach where we invited ST experts from around the world to help us achieve this level of soundness. Our goal is to make a valuable contribution to the discussion on the definition of ST and STT.

cs.CY↗

arXiv2024

Wireless Crowd Detection for Smart Overtourism Mitigation

Overtourism occurs when the number of tourists exceeds the carrying capacity of a destination, leading to negative impacts on the environment, culture, and quality of life for residents. By monitoring overtourism, destination managers can identify areas of concern and implement measures to mitigate the negative impacts of tourism while promoting smarter tourism practices. This can help ensure that tourism benefits both visitors and residents while preserving the natural and cultural resources that make these destinations so appealing. This chapter describes a low-cost approach to monitoring overtourism based on mobile devices' wireless activity. A flexible architecture was designed for a smart tourism toolkit to be used by Small and Medium-sized Enterprises (SMEs) in crowding management solutions, to build better tourism services, improve efficiency and sustainability, and reduce the overwhelming feeling of pressure in critical hotspots. The crowding sensors count the number of surrounding mobile devices, by detecting trace elements of wireless technologies, mitigating the effect of MAC address randomization. They run detection programs for several technologies, and fingerprinting analysis results are only stored locally in an anonymized database, without infringing privacy rights. After that edge computing, sensors communicate the crowding information to a cloud server, by using a variety of uplink techniques to mitigate local connectivity limitations, something that has been often disregarded in alternative approaches. Field validation of sensors has been performed on Iscte's campus. Preliminary results show that these sensors can be deployed in multiple scenarios and provide a diversity of spatio-temporal crowding data that can scaffold tourism overcrowding management strategies.

cs.CY↗

arXiv2022

Software Development Analytics in Practice: A Systematic Literature Review

Context:Software Development Analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. Objective:This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade, with an emphasis on its application in practical settings. Method:Definition and execution of a search string upon several digital libraries, followed by a quality assessment criteria to identify the most relevant papers. On those, we extracted a set of characteristics (study type, data source, study perspective, development life-cycle activities covered, stakeholders, mining methods, and analytics scope) and classified their impact against a taxonomy. Results:Source code repositories, experimental case studies, and developers are the most common data sources, study types, and stakeholders, respectively. Product and project managers are also often present, but less than expected. Mining methods are evolving rapidly and that is reflected in the long list identified. Descriptive statistics are the most usual method followed by correlation analysis. Being software development an important process in every organization, it was unexpected to find that process mining was present in only one study. Most contributions to the software development life cycle were given in the quality dimension. Time management and costs control were lightly debated. The analysis of security aspects suggests it is an increasing topic of concern for practitioners. Risk management contributions are scarce. Conclusions:There is a wide improvement margin for software development analytics in practice. For instance, mining and analyzing the activities performed by software developers in their actual workbench, the IDE.

cs.SE↗

arXiv2021

Profiling Software Developers with Process Mining and N-Gram Language Models

Context: Profiling developers is challenging since many factors, such as their skills, experience, development environment and behaviors, may influence a detailed analysis and the delivery of coherent interpretations. Objective: We aim at profiling software developers by mining their software development process. To do so, we performed a controlled experiment where, in the realm of a Python programming contest, a group of developers had the same well-defined set of requirements specifications and a well-defined sprint schedule. Events were collected from the PyCharm IDE, and from the Mooshak automatic jury where subjects checked-in their code. Method: We used n-gram language models and text mining to characterize developers' profiles, and process mining algorithms to discover their overall workflows and extract the correspondent metrics for further evaluation. Results: Findings show that we can clearly characterize with a coherent rationale most developers, and distinguish the top performers from the ones with more challenging behaviors. This approach may lead ultimately to the creation of a catalog of software development process smells. Conclusions: The profile of a developer provides a software project manager a clue for the selection of appropriate tasks he/she should be assigned. With the increasing usage of low and no-code platforms, where coding is automatically generated from an upper abstraction layer, mining developer's actions in the development platforms is a promising approach to early detect not only behaviors but also assess project complexity and model effort.

cs.SE↗

arXiv2020

PHP code smells in web apps: survival and anomalies

Context: Code smells are considered symptoms of poor design, leading to future problems, such as reduced maintainability. Except for anecdotal cases (e. g. code dropout), a code smell survives until it gets explicitly refactored or removed. This paper presents a longitudinal study on the survival of code smells for web apps built with PHP. Objectives: RQ: (i) code smells survival depends on their scope? (ii) practitioners attitudes towards code smells removal in web apps have changed throughout time? (iii) how long code smells survive in web applications? (iv) are there sudden variations (anomalies) in the density of code smells through the evolution of web apps? Method: We analyze the evolution of 6 code smells in 8 web applications written in PHP at the server side, across several years, using the survival analysis technique. We classify code smells according to scope in two categories: scattered and localized. Scattered code smells are expected to be more harmful since their influence is not circumscribed as in localized code smells. We split the observations for each web app into two equal and consecutive timeframes, to test the hypothesis that code smells awareness has increased throughout time. As for the anomalies, we standardize their detection criteria. Results: We present some evidence that code smells survival depends on their scope: the average survival rate decreases in some of them, while the opposite is observed for the remainder. The survival of localized code smells is around 4 years, while the scattered ones live around 5 years. Around 60% of the smells are removed, and some live through all the application life. We also show how a graphical representation of anomalies found in the evolution of code smells allows unveiling the story of a development project and make managers aware of the need for enforcing regular refactoring practices.

cs.SE↗

arXiv2020

Crowdsmelling: The use of collective knowledge in code smells detection

Code smells are seen as major source of technical debt and, as such, should be detected and removed. However, researchers argue that the subjectiveness of the code smells detection process is a major hindrance to mitigate the problem of smells-infected code. We proposed the crowdsmelling approach based on supervised machine learning techniques, where the wisdom of the crowd (of software developers) is used to collectively calibrate code smells detection algorithms, thereby lessening the subjectivity issue. This paper presents the results of a validation experiment for the crowdsmelling approach. In the context of three consecutive years of a Software Engineering course, a total "crowd" of around a hundred teams, with an average of three members each, classified the presence of 3 code smells (Long Method, God Class, and Feature Envy) in Java source code. These classifications were the basis of the oracles used for training six machine learning algorithms. Over one hundred models were generated and evaluated to determine which machine learning algorithms had the best performance in detecting each of the aforementioned code smells. Good performances were obtained for God Class detection (ROC=0.896 for Naive Bayes) and Long Method detection (ROC=0.870 for AdaBoostM1), but much lower for Feature Envy (ROC=0.570 for Random Forrest). Obtained results suggest that crowdsmelling is a feasible approach for the detection of code smells, but further validation experiments are required to cover more code smells and to increase external validity.

cs.SE↗

arXiv2020

Code smells detection and visualization: A systematic literature review

Context: Code smells (CS) tend to compromise software quality and also demand more effort by developers to maintain and evolve the application throughout its life-cycle. They have long been catalogued with corresponding mitigating solutions called refactoring operations. Objective: This SLR has a twofold goal: the first is to identify the main code smells detection techniques and tools discussed in the literature, and the second is to analyze to which extent visual techniques have been applied to support the former. Method: Over 83 primary studies indexed in major scientific repositories were identified by our search string in this SLR. Then, following existing best practices for secondary studies, we applied inclusion/exclusion criteria to select the most relevant works, extract their features and classify them. Results: We found that the most commonly used approaches to code smells detection are search-based (30.1%), and metric-based (24.1%). Most of the studies (83.1%) use open-source software, with the Java language occupying the first position (77.1%). In terms of code smells, God Class (51.8%), Feature Envy (33.7%), and Long Method (26.5%) are the most covered ones. Machine learning techniques are used in 35% of the studies. Around 80% of the studies only detect code smells, without providing visualization techniques. In visualization-based approaches several methods are used, such as: city metaphors, 3D visualization techniques. Conclusions: We confirm that the detection of CS is a non trivial task, and there is still a lot of work to be done in terms of: reducing the subjectivity associated with the definition and detection of CS; increasing the diversity of detected CS and of supported programming languages; constructing and sharing oracles and datasets to facilitate the replication of CS detection and visualization techniques validation experiments.

cs.SE↗

arXiv2020

Unveiling process insights from refactoring practices

Context : Software comprehension and maintenance activities, such as refactoring, are said to be negatively impacted by software complexity. The methods used to measure software product and processes complexity have been thoroughly debated in the literature. However, the discernment about the possible links between these two dimensions, particularly on the benefits of using the process perspective, has a long journey ahead. Objective: To improve the understanding of the liaison of developers' activities and software complexity within a refactoring task, namely by evaluating if process metrics gathered from the IDE, using process mining methods and tools, are suitable to accurately classify different refactoring practices and the resulting software complexity. Method: We mined source code metrics from a software product after a quality improvement task was given in parallel to (117) software developers, organized in (71) teams. Simultaneously, we collected events from their IDE work sessions (320) and used process mining to model their processes and extract the correspondent metrics. Results: Most teams using a plugin for refactoring (JDeodorant) reduced software complexity more effectively and with simpler processes than the ones that performed refactoring using only Eclipse native features. We were able to find moderate correlations (43%) between software cyclomatic complexity and process cyclomatic complexity. The best models found for the refactoring method and cyclomatic complexity level predictions, had an accuracy of 92.95% and 94.36%, respectively. Conclusions: Our approach agnostic to programming languages, geographic location, or development practices. Initial findings are encouraging, and lead us to suggest practitioners may use our method in other development tasks, such as, defect analysis and unit or integration tests.

cs.SE↗

arXiv2012

An Eclipse Plugin to Support Code Smells Detection

Eradication of code smells is often pointed out as a way to improve readability, extensibility and design in existing software. However, code smell detection in large systems remains time consuming and error-prone, partly due to the inherent subjectivity of the detection processes presently available. In view of mitigating the subjectivity problem, this paper presents a tool that automates a technique for the detection and assessment of code smells in Java source code, developed as an Eclipse plug-in. The technique is based upon a Binary Logistic Regression model and calibrated by expert's knowledge. A short overview of the technique is provided and the tool is described.

cs.SE↗

arXiv2012

The cloud paradigm: Are you tuned for the lyrics?

Major players, business angels and opinion-makers are broadcasting beguiled lyrics on the most recent IT hype: your software should ascend to the clouds. There are many clouds and the stake is high. Distractedly, many of us became assiduous users of the cloud, but perhaps due to the legacy systems and legacy knowledge, IT professionals, mainly those many that work in business information systems for the long tail, are not as much plunged into producing cloud-based systems for their clients. This keynote will delve into several aspects of this cloud paradigm, from more generic concerns regarding security and value for money, to more specific worries that reach software engineers in general. Do we need a different software development process? Are development techniques and tools mature enough? What about the role of open-source in the cloud? How do we assess the quality in cloud-based development? Please stay tuned for more!

cs.DC↗

arXiv2011

SLALOM: a Language for SLA specification and monitoring

IT services provisioning is usually underpinned by service level agreements (SLAs), aimed at guaranteeing services quality. However, there is a gap between the customer perspective (business oriented) and that of the service provider (implementation oriented) that becomes more evident while defining and monitoring SLAs. This paper proposes a domain specific language (SLA Language for specificatiOn and Monitoring - SLALOM) to bridge the previous gap. The first step in SLALOM creation was factoring out common concepts, by composing the BPMN metamodel with that of the SLA life cycle, as described in ITIL. The derived metamodel expresses the SLALOM abstract syntax model. The second step was to write concrete syntaxes targeting different aims, such as SLA representation in process models. An example of SLALOM's concrete syntax model instantiation for an IT service sup-ported by self-service financial terminals is presented.

cs.SE↗

arXiv2011

An overview of metrics-based approaches to support software components reusability assessment

Objective: To present an overview on the current state of the art concerning metrics-based quality evaluation of software components and component assemblies. Method: Comparison of several approaches available in the literature, using a framework comprising several aspects, such as scope, intent, definition technique, and maturity. Results: The identification of common shortcomings of current approaches, such as ambiguity in definition, lack of adequacy of the specifying formalisms and insufficient validation of current quality models and metrics for software components. Conclusions: Quality evaluation of components and component-based infrastructures presents new challenges to the Experimental Software Engineering community.

cs.SE↗