M. Denisov, A. Anikin, O. Sychev, A. Katyshev (2021)
.
1184 pp. 256-269. Springer Science and Business Media Deutschland GmbH.
@ARTICLE{Denisov2021256,
author={Denisov, M. and Anikin, A. and Sychev, O. and Katyshev, A.},
title={Program execution comprehension modelling for algorithmic languages learning using ontology-based techniques},
journal={Advances in Intelligent Systems and Computing},
year={2021},
volume={1184},
pages={256-269},
doi={10.1007/978-981-15-5859-7_25},
url={https://link.springer.com/chapter/10.1007%2F978-981-15-5859-7_25},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation; Software Engineering School, Volgograd, Russian Federation},
abstract={In this paper, we propose an ontology-based approach to model a program execution comprehension so to be able to explain to the novice programmer the essence of his/her error. We have studied the algorithmic languages model operating with actions and basic control structures (“sequence,” “branching,” and “looping”) and designed the rules to capture any deviation from the permissible. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.},
correspondence_address1={Anikin, A.; Software Engineering SchoolRussian Federation; эл. почта: Anton@Anikin.name},
publisher={Springer Science and Business Media Deutschland GmbH},
issn={21945357},
language={English},
abbrev_source_title={Adv. Intell. Sys. Comput.},
thanks = {rfbr-18-07-00032}
}