Scenario-Based Testing of Online Learning Programs

Maxence Demougeot, Sylvie Trouilhet, Jean-Paul Arcangeli, Françoise Adreit

2025

Abstract

Testing is a solution for verification and validation of systems based on Machine Learning (ML). This paper focuses on testing functional requirements of programs that learn online. Online learning programs build and update ML models throughout their execution. Testing allows domain experts to measure how well they work, identify favorable or unfavorable use cases, compare different versions or settings, or reveal defects. Testing programs which learn online has particular features. To deal with them, a scenario-based approach and a testing process are defined. This solution is implemented and automates test execution and quality measurements. It is applied to a program that learns online the end-user’s preferences in an ambient environment, confirming the viability of the approach.

Paper Citation

in Harvard Style

Demougeot M., Trouilhet S., Arcangeli J. and Adreit F. (2025). Scenario-Based Testing of Online Learning Programs. In Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT; ISBN 978-989-758-757-3, SciTePress, pages 99-110. DOI: 10.5220/0013503100003964

in Bibtex Style

@conference{icsoft25,
author={Maxence Demougeot and Sylvie Trouilhet and Jean-Paul Arcangeli and Françoise Adreit},
title={Scenario-Based Testing of Online Learning Programs},
booktitle={Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT},
year={2025},
pages={99-110},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013503100003964},
isbn={978-989-758-757-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Software Technologies - Volume 1: ICSOFT
TI - Scenario-Based Testing of Online Learning Programs
SN - 978-989-758-757-3
AU - Demougeot M.
AU - Trouilhet S.
AU - Arcangeli J.
AU - Adreit F.
PY - 2025
SP - 99
EP - 110
DO - 10.5220/0013503100003964
PB - SciTePress