Authors:
Maxence Demougeot
1
;
Sylvie Trouilhet
1
;
Jean-Paul Arcangeli
1
and
Françoise Adreit
2
Affiliations:
1
IRIT, Université de Toulouse, Toulouse, France
;
2
IRIT, Université de Toulouse, UT2J, Toulouse, France
Keyword(s):
Online Machine Learning, Learning Program, Test, Test Scenario, Functional Testing, Testing Process.
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.