Abstract
To improve algorithmic problem solving skills and thus coding skills, we need to practice algorithms. In that regard, databases like algoBank and websites provide algorithmic exercises with solutions but with contents that may or may not be semantically structured to be queried efficiently. To better exploit the potential of exercise databases, research suggests to represent their content using ontologies. Nevertheless, such research focuses mainly on representing and querying exercises as well as algorithmic skills or specific programming languages. In this work, we choose to represent, through the ontology CodOnto, the solutions of exercises in pseudocode to enhance understanding and querying of algorithms for learners and facilitate translation into the programming languages.
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Diatta, B., Basse, A., Ndiaye, N.M. (2019). Framework and Ontology for Modeling and Querying Algorithms. In: Auer, M., Tsiatsos, T. (eds) The Challenges of the Digital Transformation in Education. ICL 2018. Advances in Intelligent Systems and Computing, vol 917. Springer, Cham. https://doi.org/10.1007/978-3-030-11935-5_51
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