http://hdl.handle.net/11422/56 2026-04-13T13:20:32Z 2026-04-13T13:20:32Z Barroso, Bruno Lemos http://hdl.handle.net/11422/29062 2026-04-12T03:00:14Z 2025-08-27T00:00:00Z

Title: Mitigando a carga cognitiva em testes unitários: uma abordagem focada em processos de trabalho Author(s)/Inventor(s): Barroso, Bruno Lemos Advisor: Mello, Rafael Maiani de Abstract: Software quality is a central aspect of software engineering projects, as it influences reliability, maintainability, and user satisfaction. In this context, unit tests verify the behavior of small units of code and enable early fault identification. However, their adoption may be hindered by factors that make the practice costly or, at times, neglected. Among the elements that may compromise unit testing is cognitive load, understood as the mental effort required to understand and perform tasks. This load tends to increase in the absence of planning, in the presence of redundant processes, gaps in automation, uncertainties about validation criteria, and pressure for quantitative metrics. In such scenarios, delays, rework, and lower adherence to desired practices may occur. This dissertation aims to propose strategies and recommendations to mitigate the cognitive load faced by developers during unit testing and to identify characteristics that favor their adaptation to different development contexts. The research adopts a qualitative approach based on Grounded Theory, focusing on work-process aspects, drawing on semi-structured interviews with developers. As an outcome of the analysis, a set of recommendations is presented and organized into four stages of the testing process — conception, writing, execution, and validation — formulated as suggestions for flexible application. The proposals aim to make criteria more explicit, support the standardization of decisions, and guide the required automation, providing a starting point for local adjustments according to each team’s context. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação

2025-08-27T00:00:00Z Jesus, Valquire da Silva de http://hdl.handle.net/11422/29061 2026-04-12T03:00:14Z 2025-05-29T00:00:00Z

Title: Autonomia de meios operativos para apoio à decisão em sistemas de comando e controle: uma abordagem preditiva e conceitual utilizando aprendizado de máquina Author(s)/Inventor(s): Jesus, Valquire da Silva de Advisor: Lopes, Giseli Rabello Abstract: In complex military scenarios, such as those faced by the Brazilian Navy (MB) in naval op- erations, logistical planning demands rigor, especially regarding the autonomy of operational elements, understood as the ability to operate without external resupply. This autonomy depends on factors such as supply consumption, the number of embarked personnel, and the operational conditions of naval platforms, acting in contexts supported by Command and Control (C2) systems. Although Machine Learning (ML) techniques are used to anticipate logistical demands, the semantic data heterogeneity and the lack of contextual domain un derstanding limit the effectiveness of purely quantitative approaches. To address these chal lenges, this work proposes the ATOp (Autonomia de Meios Operativos) approach, which integrates Ontology-Driven Conceptual Modeling (ODCM) and ML to enhance autonomy prediction. Grounded in the Unified Foundational Ontology (UFO), ATOp makes domain knowledge explicit and enables semantic data segmentation through the ontological meta category Situation, which represents contexts relevant to operational behavior. This seg mentation supports a regression pipeline with an ensemble of models, coordinating multiple specialized algorithms. The research included the development of the ATOp-NavalOntology, a well-founded ontology, data engineering from heterogeneous MB sources, and experiments involving Bayesian hyperparameter optimization and k-fold cross-validation, aimed at con structing the ATOp-PredictiveModel. The evaluation used metrics (R2 and RMSE) and statistical tests (Friedman and Durbin-Conover) to ensure reliable comparisons. The results show that combining well-founded ontologies and ML structures the data in a way that re veals relevant patterns, improves the quality of predictions, and outperforms individual mod els such as Gradient Boosting when applied directly to raw data. The ATOp-PredictiveModel achieved the best performance, with higher accuracy and lower computational cost, present ing statistically significant differences. As a contribution, ATOp offers a replicable model that integrates semantic knowledge into decision support in operational domains sustained by C2 systems. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação

2025-05-29T00:00:00Z Almeida, Saulo Andrade http://hdl.handle.net/11422/29060 2026-04-12T03:00:14Z 2025-03-31T00:00:00Z

Title: Estratégias de paralelização para o algoritmo Feature Space Partition Author(s)/Inventor(s): Almeida, Saulo Andrade Advisor: Rossetto, Silvana Abstract: This dissertation presents the parallelization of the supervised learning algorithm Feature Space Partition (FSP), originally implemented sequentially in the Python language. Although FSP has proven to be efficient in small datasets, it has presented a high execution time when used in largers amount of data. The parallelization process investigates more than one parallelization approach, including parallel programming on CPU and GPU, maintaining the original sequence of steps of the sequential version of the algorithm, in order to evaluate which is the most appropriate strategy for paralleli- zation, but without losing its accuracy. One of the premises of the project is to try to use parallelization resources and libraries already existing in the vast and heterogeneous environment of the Python language. At the end of the experiment, the best scenario exe- cuted was the multiprocess CPU parallelization, which presented a 36.44% improvement in performance, when compared to its initial implementation, without decreasing its accuracy. Publisher: Universidade Federal do Rio de Janeiro Type: Dissertação

2025-03-31T00:00:00Z Camilo, Márcio da Silva http://hdl.handle.net/11422/29059 2026-04-12T03:00:14Z 2025-02-27T00:00:00Z

Title: Abordagem sistêmica na educação em saúde: metodologia de construção de jogos para promover a colaboração em equipes interdisciplinares Author(s)/Inventor(s): Camilo, Márcio da Silva Advisor: Motta, Claudia Lage Rebello da Abstract: Communication problems and fragmentation in teamwork can lead to adverse events in healthcare services. Interdisciplinary training of healthcare professionals may hold the key to improving the quality of hospital work. However, how can we provide experiences that raise awareness of the benefits of cooperation? Interdisciplinary collaboration is understood here as a complex phenomenon, essential for building more efficient teams and improving healthcare outcomes. For this reason, an approach that goes beyond classical systems is necessary. This research investigated the design of games with educational purposes to sensitize participants to the importance of teamwork and the integration of knowledge. A methodology was developed for the creation of sensitizing games aimed at integrating different health areas, promoting skills such as communication, collaboration, and joint problem-solving. The methodology was designed to be simple and flexible, with educational and scientific objectives. As a case study, the methodology was applied in the adaptation of an RPG game focused on collaboration among healthcare professionals. Game sessions were qualitatively analyzed to evaluate the effectiveness of the game in promoting the proposed educational objectives. The results indicated that participants showed improvements in teamwork and assertive communication skills. During the game sessions, players combined their complementary problem-solving skills, demonstrating that the game contributed to the creation of a collaborative environment. The analysis revealed that the game methodology may be promising for the development of fundamental behavioral skills necessary for joint action in health teams. Although the research was limited by the small number of participants and the lack of resources to expand the study, the results point to the potential of games as a tool in professional training, as well as to improving the dynamics of healthcare teams. Considering health education as a constantly evolving field and the use of playful resources as an alternative to overcome the limitations of traditional approaches, future perspectives include conducting additional studies to deepen the analysis of educational games and explore issues such as ethics in games and conflict mediation, aiming to refine the methodology and expand its application in the training of interdisciplinary healthcare teams. Publisher: Universidade Federal do Rio de Janeiro Type: Tese

2025-02-27T00:00:00Z