Work

Assessing Task-based Chatbots: Snapshot and Curated Datasets for Dialogflow

Year: 2026

Type: conference-paper

Abstract: In recent years, chatbots have gained widespread adoption thanks to their ability to assist users at any time and across diverse domains. However, the lack of large-scale curated datasets limits research on their quality and reliability. This paper presents TOFU-D, a snapshot of 1,788 Dialogflow chatbots from GitHub, and COD, a curated subset of TOFU-D including 185 validated chatbots. The two datasets capture a wide range of domains, languages, and implementation patterns, offering a sound basis for empirical studies on chatbot quality and security. A preliminary assessment using the Botium testing framework and the Bandit static analyzer revealed gaps in test coverage and frequent security vulnerabilities in several chatbots, highlighting the need for systematic, multi-platform research on chatbot quality and security.

Source: International Conference on Mining Software Repositories (MSR)

DOI: 10.1145/3793302.3793325

Authors: Elena Masserini, Diego Clerissi, Daniela Micucci, Leonardo Mariani

Institution: University of Milano-Bicocca

Language: English

Topic: Speech and dialogue systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7125947876

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