TCC - Bacharelado em Sistemas da Informação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/427
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5 resultados
Resultados da Pesquisa
Item Análise comparativa de ferramentas de testes automatizados de ponta a ponta em ambientes de aplicações web(2024-03-11) Farias, Guilherme Carneiro de; Monteiro, Cleviton Vinicius Fonsêca; http://lattes.cnpq.br/9362573782715504In a context where software occupies an increasingly relevant and complex space in society, it is extremely important to enable means for it to be developed with quality. One of these means is automated testing, and in the current scenario, we observe the emergence of a variety of tools in this area, each with its own nuances and unique functionalities. Faced with this diversity of options, this research compares the main end-to-end testing automation tools in web application environments, aiming to facilitate the choice of the most suitable for each project. The theoretical foundation includes concepts of Software Quality, Software Testing, and Architecture and Automation Testing Tools. Three tools were identified and evaluated: Selenium WebDriver, Cypress, and Playwright. The research method is exploratory and descriptive, combining qualitative and quantitative approaches. The results indicate that Playwright presents the best combination of features for end-to-end automated testing in web applications.Item Construção de pipelines de dados sobre obras públicas em Pernambuco: abordagem prática com o Apache Airflow(2023-09-21) Silva, Henrique César José da; Albuquerque Júnior, Gabriel Alves de; http://lattes.cnpq.br/1399502815770584This study presents a practical approach to building data pipelines focused on collecting, transforming, and storing information related to public works in the state of Pernambuco. The central objective is to develop efficient and automated workflows for extracting data from public transparency portals and subsequently consolidating this information. Based on Data Engineering technologies, the Apache Airflow framework was chosen to orchestrate the processes, enabling the scheduling and monitoring of these workflows.Item Construção de uma solução para automatização de processos manuais de um assistente virtual(2024-04-27) Araujo, Thales Gabriel dos Anjos; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505Item Análise de dados coletados para a melhoria de uma suite de testes em um site de e-commerce(2024-03-08) Lubambo, Manoela Timossi; Monteiro, Cleviton Vinicius Fonsêca; http://lattes.cnpq.br/9362573782715504; http://lattes.cnpq.br/5743969633597802Quality is important in Software Engineering so that systems maintain and meet specified requirements, are reliable, efficient and free from defects. This is guaranteed through a series of standards, practices and processes. As an essential part of the quality assurance process, software testing aims to verify the software’s compliance with established functional and non-functional requirements, such as performance, security, usability, reliability, among others. They are conducted by running the software under controlled conditions, using specific techniques and strategies to detect problems and ensure their correction. One of its diverse approaches is through test automation. In this work, a detailed report is made on the process of automating a test suite, highlighting the challenges faced throughout this process. And, a thorough analysis of the data collected regarding automation is carried out and, through this analysis, we seek identify the root of the problems related to the lack of effectiveness of the automation presented, where possible improvements are identified based on the results obtained, aiming to optimize the effectiveness of the test automation process.Item Uso de machine learning para previsão de valores de apartamentos no município do Recife(2023-09-12) Silva, Thiago César de Miranda; Monteiro, Cleviton Vinicius Fonsêca; Soares, Rodrigo Gabriel Ferreira; http://lattes.cnpq.br/2526739219416964; http://lattes.cnpq.br/9362573782715504; http://lattes.cnpq.br/8285740572952516The COVID-19 pandemic has brought with it a series of economic effects and transformations related to behavior and the way people live, which, in turn, have had repercussions on property prices and real estate demand. In this context, property price forecasting assumes an extremely important role, contributing to more informed decisions, mitigating risks, and promoting greater transparency in the real estate sector. The implementation of automation in price forecasting further enhances this dynamic, significantly improving accuracy, efficiency, and reliability of predictions, while providing adaptability to economic fluctuations with greater agility. Utilizing listings available on OLX, a georeferenced database was created to generate a residential apartment price prediction model in Recife, using machine learning models in AutoML. This tool automates the development of machine learning models, enabling rapid experimentation and a focus on problem-solving. The work indicates that the poor geographical distribution of the data has biased the results of the models. Furthermore, it was concluded that the data found on online buying and selling platforms are insufficient for generating a machine learning model that achieves an acceptable level of accuracy in Recife, mainly because transaction values for the properties are not provided, only the advertised prices. However, this current work provides significant contributions to the advancement of research related to automation in real estate price prediction.