Test Case Generation for Dialogflow Task-Based Chatbots

Chatbots are software typically embedded in Web and Mobile applications designed to assist the user in a plethora of activities, from chit-chatting to task completion. They enable diverse forms of interactions, like text and voice commands. As any software, even chatbots are susceptible to bugs, and their pervasiveness in our lives, as well as the underlying technological advancements, call for tailored quality assurance techniques. However, test case generation techniques for conversational chatbots are still limited. In this paper, we present Chatbot Test Generator (CTG), an automated testing technique designed for task-based chatbots. We conducted an experiment comparing CTG with state-of-the-art BOTIUM and CHARM tools with seven chatbots, observing that the test cases generated by CTG outperformed the competitors, in terms of robustness and effectiveness.

Publication Details

Journal
ArXiv.org
Published
2025-03-07
Primary Topic
AI in Service Interactions
Type
article
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article

Test Case Generation for Dialogflow Task-Based Chatbots

ArXiv.org
AI in Service Interactions
article

Test Case Generation for Dialogflow Task-Based Chatbots

article en

Abstract

Chatbots are software typically embedded in Web and Mobile applications designed to assist the user in a plethora of activities, from chit-chatting to task completion. They enable diverse forms of interactions, like text and voice commands. As any software, even chatbots are susceptible to bugs, and their pervasiveness in our lives, as well as the underlying technological advancements, call for tailored quality assurance techniques. However, test case generation techniques for conversational chatbots are still limited. In this paper, we present Chatbot Test Generator (CTG), an automated testing technique designed for task-based chatbots. We conducted an experiment comparing CTG with state-of-the-art BOTIUM and CHARM tools with seven chatbots, observing that the test cases generated by CTG outperformed the competitors, in terms of robustness and effectiveness.

ArXiv.org
Quality Education
Openalex Percentile: Top 73%
AI in Service Interactions
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Test Case Generation for Dialogflow Task-Based Chatbots · ArXiv.org (2025) | TGRS Research Map | TGRS