About the Journal

 

Revista de Informática Teórica e Aplicada (RITA) is a peer-reviewed, open-access journal published quarterly by the Institute of Informatics at the Federal University of Rio Grande do Sul (UFRGS), Brazil. Dedicated to the advancement of computer science, RITA publishes high-quality original research articles, reviews, and technical notes that contribute to both theoretical and applied aspects of the field. Since 2010, RITA has been published exclusively online (ISSN 2175-2745), ensuring broad accessibility and rapid dissemination of its content to researchers and practitioners worldwide

Free Access Policy: RITA adheres to a Diamond Open Access model, ensuring immediate and permanent free access to all its content. This commitment reflects our belief in the democratization of knowledge, making research freely available to readers worldwide without any financial barriers. Authors are not required to pay any article processing charges (APCs), ensuring an inclusive platform for the dissemination of high-quality research.

Use of Artificial Intelligence. RITA recognizes the continuous evolution and adoption of Large Language Models (LLMs), Generative Artificial Intelligence, and AI-assisted technologies in the scientific research ecosystem.  To ensure the academic integrity, transparency, accountability, and scientific rigor of its publications, RITA establishes the following Guidelines on the Use of Artificial Intelligence

Mission: RITA is dedicated to fostering a dynamic exchange of ideas within the computer science community. Our mission is to:
Cultivate an interdisciplinary environment where researchers can share cutting-edge findings in both theoretical and applied informatics.
Accelerate the global dissemination of knowledge by providing immediate open access to all published works.
Ensure the efficient and timely publication of high-quality research that advances the field of computer science.

Goals: Contribute to the advancement of knowledge in theoretical and applied informatics by the publication of works that show state of the art and trends of the areas. RITA is committed to: a) Disseminating high-quality research that showcases the latest advancements and emerging trends in computer science; b) Fostering innovation and collaboration by providing a platform for researchers to share their work and engage in interdisciplinary dialogue; c) Promoting the application of informatics to address real-world challenges and drive societal progress.

Focus Areas and Topics of Interest: RITA publishes research in a broad range of computer science fields, including:
Software and Systems: Software Engineering, Information Systems, Embedded Systems
Artificial Intelligence: Artificial Intelligence, Machine Learning, Robotics
Hardware and Architecture: Microelectronics, Integrated Circuits Design, Computer Networks, High-Performance Computing
Theory and Foundations: Computer Fundamentals, Formal Methods, Optimization
Applications: Bioinformatics, Computational Graphics, Computer Science in Medicine, Computational Nanotechnology and Nanocomputing

Index by: DBLP; SCOPUS; LATINDEX; BASE; CARINIANA; LIVRE; GOOGLE SCHOOLAR; CITE FACTOR; DIADORIM; CROSSREF

Current Issue

Vol. 33 No. 4 (2026)

Editor-in-Chief: Prof. Dr. Márcio Dorn - Federal University of Rio Grande do Sul - Brazil

Associate Editors:

Prof. Dr. Lucinéia Heloisa Thom - Federal University of Rio Grande do Sul - Brazil
Prof. Dr. María Encarnación Sosa Sánchez - University of Extremadura - Spain

Editorial support: Gustavo Zahorcsak Matias Silvano - Federal University of Rio Grande do Sul - Brazil

Published: 2026-08-10

Regular Papers

  • Performance Evaluation of Supervised Machine Learning Models for Heart Disease Prediction Using Clinical Survey Data

    Md. Nasim Ali, Mahir Bin Ayub, Sohel Rana
    11-20
    DOI: https://doi.org/10.22456/2175-2745.153722
  • Efficiency Analysis of Fine-Tuning Compact Language Models for Biomedical Information Retrieval Systems

    Martony Demes da Silva
    21-31
    DOI: https://doi.org/10.22456/2175-2745.153249
  • Performance of Machine Learning Algorithms in Predicting Sheep Weight Based on Morphometric Measurements

    Leonardo Antunes, Ana Flávia da Guia Miranda, João Batista Gonçalves Costa Júnior, Caroline Lima Amorim, Maria Eduarda Garcia Corrêa, Adrielly Kamile Silva Bezerra, Kauane Ferreira da Silva, Shara Luzia Cavalcante Souza, Juliana Fonseca Antunes
    32-43
    DOI: https://doi.org/10.22456/2175-2745.154217
  • Computational Method for Continuous Monitoring of Ocular Artifacts in Electroencephalography Data

    Yuri Silveira Pereira, Daniel Dargelio Ferrão Luft, Matheus Gularte Tavares, Tadeu Vargas, Samuel dos Santos Cardoso
    44-52
    DOI: https://doi.org/10.22456/2175-2745.150325
  • Fault Injection via Code Mutation for Dependability Assessment in Cloud Environments

    Guilherme Silva, Erica Sousa
    53-67
    DOI: https://doi.org/10.22456/2175-2745.149183
  • Behavioral Insights of SARSA-Based Reinforcement Learning for IPv6 Intrusion Classification

    April Firman Daru, Alauddin Maulana Hirzan, Zainab Senan Mahmod Attar Bashi, Fajriannoor Fanani
    68-81
    DOI: https://doi.org/10.22456/2175-2745.148437
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