http://repositorio.ufc.br/handle/riufc/24020 2026-08-14T22:44:19Z http://repositorio.ufc.br/handle/riufc/87406 Título: Reestruturação de um processo de desenvolvimento com a implantação de metodologias ágeis: um estudo de caso no projeto de extensão Nerds Autor(es): Silva, Patrick Glauber Oliveira da Abstract: The inherent complexity of contemporary software development, marked by requirement volatility and the need for frequent value delivery, imposes severe limitations on traditional management approaches based on fixed scope. In this scenario, productivity and quality management pose a critical challenge, especially in academic environments where turnover rates and learning curves are high. This study aims to analyze the impact of the systematic application of agile practices on the productivity of a development team involved in a university extension project at the Federal University of Ceará. The adopted methodology was based on the Scrum and Kanban frameworks, integrating advanced software engineering techniques such as consensus-based effort estimation through Planning Poker. Distinguishing itself from purely qualitative approaches, this research employed a rigorous quantitative analysis: productivity data were submitted to inferential statistical tests using the JASP tool, enabling the validation of the statistical significance of performance variations observed throughout the sprints. The results demonstrate that the transition from an ad hoc model to a metrics-based agile process not only stabilized the delivery flow but also increased role clarity and team satisfaction. It is concluded that the combination of agile ceremonies with a data-driven culture and statistical control is decisive for mitigating uncertainties and raising the maturity of the development process, even in the context of newly formed teams. Tipo: TCC 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/87395 Título: Aplicações de blockchain na rastreabilidade de requisitos de software Autor(es): Oliveira, José Evamberto Lima Abstract: This work presents a critical-analytical literature review, with a qualitative approach, on the application of blockchain technology in software requirements traceability. The main objective is to identify and critically analyze the architectures proposed in the literature and evaluate how they address the inherent technical challenges of the technology. The search was conducted in the IEEE Xplore, Scopus, and Google Scholar databases, resulting in the selection of nine primary studies published between 2021 and 2025. The results indicate a predominant use of smart contracts on the Ethereum platform, alongside innovative approaches using neural blockchains and graph databases, generally adopting hybrid storage strategies (on-chain and off-chain via IPFS) to mitigate costs. Although blockchain offers immutability, transparency, and auditability for requirements tracking, the research field is still in its early stages of maturity. The studies are predominantly prototypes in controlled environments, with significant gaps regarding interoperability with market tools (such as Jira and GitHub), insufficient scalability analyses in real-world scenarios, and superficial treatment of privacy. In conclusion, while the theoretical potential is substantial, the industrial adoption of blockchain in requirements traceability still requires empirical validation of its cost-benefit ratio compared to traditional solutions. Tipo: TCC 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/87342 Título: Análise de Desempenho entre Docker e KVM: Um Estudo de Caso em Microsserviços Web sob Restrição de Recursos Autor(es): Dutra, Italo Fernando Silva Abstract: This work presents a comparative performance analysis between Docker container technology and KVM hypervisor-based virtualization, focusing on the execution of web microservices under hardware resource constraints of 1 vCPU and 1 GB of RAM. The study is motivated by the relevance of low-cost VPS environments and edge computing scenarios, in which the overhead imposed by the virtualization layer can directly affect the application service capacity. For this purpose, a RESTful API was developed in Node.js v22.22.2 with Express.js, specifically implemented for this study and exposing dedicated endpoints designed to stress different computational resources. The application was submitted to four experimental scenarios: baseline and cold start, network stress, CPU saturation, and memory pressure, using Grafana k6 as the load testing tool. Each scenario was executed with 15 independent repetitions per evaluated configuration, allowing the analysis of metrics such as latency, throughput, CPU utilization, memory consumption, and startup time. The results show that Docker presents a significant advantage in cold start, being 5.2 times faster than KVM. Under moderate load, both technologies presented similar performance in latency and throughput. Under more intensive workloads, KVM demonstrated better behavior in tail latency, throughput under CPU saturation, and performance under memory pressure, although the latter scenario must be interpreted considering the experimental configuration adopted. The findings indicate that the historical overhead of KVM has been reduced in modern environments, making it competitive for stable transactional workloads, while Docker remains superior in scenarios requiring fast startup and higher instance density. Tipo: TCC 2026-01-01T00:00:00Z http://repositorio.ufc.br/handle/riufc/87312 Título: Algoritmo genético aplicado ao problema de corte bidimensional e guilhotinado em placas de madeira Autor(es): Maia, Deusiane Kaylane Moreira Abstract: Modern industries seek to continuously optimize their production processes, whether by reducing waste of raw materials and manufacturing time or by increasing efficiency and the quantity of products produced. The furniture industry is no exception, as it repeatedly faces high levels of raw material waste, particularly when cutting wooden panels. In this regard, this study aims to identify a strategy capable of finding a solution for cutting pieces from wooden panels to maximize material utilization in a timely manner. This study addresses two-dimensional cutting and nesting problems, as it considers the width and height dimensions of the wood panels, with straight cuts into rectangular pieces that follow geometric patterns and do not undergo rotation due to the furniture’s design. Initially, a systematic literature review is conducted to identify and analyze existing approaches related to this topic. Subsequently, six configurations of a genetic algorithm are implemented and evaluated, obtained from combinations of the Roulette Wheel and Tournament selection operators, and the One-Point, Two-Point, and Single-Parent crossover operators, with the aim of obtaining high-quality solutions within a feasible computational time. Among the six configurations evaluated, Algorithm 6, consisting of the Tournament Selection and Single-Parent Crossover operators, demonstrated the best scalability and overall performance in terms of execution time and GPU utilization. For small-scale instances, such as m0_i1 (10 pieces), Algorithms 4, 5, and 6 showed an approximately 50% reduction in execution time compared to Algorithms 1, 2, and 3, with Algorithm 6 recording the shortest execution time of approximately 0.1136 seconds. In the most complex instance (m5_i40, with 4,240 pieces), Algorithm 6 ran in approximately 25.0 seconds, maintaining the best performance among the evaluated configurations. Furthermore, Algorithm 6 demonstrated the greatest stability, with the narrowest interquartile range (IQR) among the boxplots analyzed. Thus, Algorithm 6 emerges as the configuration proposed in this study that is best suited for real-world industrial scenarios, where the high volume of parts demands fast and reliable responses. Tipo: TCC 2026-01-01T00:00:00Z