Multi-Level Testing of Conversational AI Systems
Abstract
Conversational AI systems combine AI-based solutions with the flexibility of conversational interfaces. However, most existing testing solutions do not straightforwardly adapt to the characteristics of conversational interaction or to the behavior of AI components. To address this limitation, this Ph.D. thesis investigates a new family of testing approaches for conversational AI systems, focusing on the validation of their constituent elements at different levels of granularity, from the integration between the language and the AI components, to individual conversational agents, up to multi-agent implementations of conversational AI systems
Cite
@article{arxiv.2602.03311,
title = {Multi-Level Testing of Conversational AI Systems},
author = {Elena Masserini},
journal= {arXiv preprint arXiv:2602.03311},
year = {2026}
}
Comments
3 pages, 1 figure, Accepted at IEEE/ACM International Conference on Software Engineering (ICSE) - Doctoral Symposium Track, 2026