Gutek: Intelligent Revision Algorithms

This paper introduces Gutek, a novel open-source framework designed to optimize the learning process through intelligent revision algorithms. Gutek is built on a low-code architecture that facilitates rapid customization and extension with minimal alterations to the core codebase. By leveraging the Spring Framework, the system automates essential processes such as dependency injection, component management, and database operations via Spring Data JPA, while employing reflection to dynamically integrate new revision algorithms, charts, and custom card types. The framework supports bidirectional revision interfaces, offering both conventional and reverse revision modes to enhance memory retention and accommodate diverse learning strategies. Comparative evaluations with established open-source systems, including Anki, Mnemosyne, and OpenCards, reveal that Gutek maintains lower code complexity and superior maintainability, as demonstrated by comprehensive software quality metrics and user-based extensibility assessments. Specifically, Gutek exhibits up to 80% fewer lines of code compared to Anki and Mnemosyne and achieves the lowest number of critical issues reported in SonarQube analysis. These results indicate that Gutek provides extensive customization capabilities with minimal coding effort, making it especially suitable for educators, developers, and practitioners seeking a flexible yet robust learning tool.