AI Testing for Intelligent Chatbots—A Case Study

Abstract

The decision tree test method works as a flowchart structure for conversational flow. It has predetermined questions and answers that guide the user through specific tasks. Inspired by principles of the decision tree test method in software engineering, this paper discusses intelligent AI test modeling chat systems, including basic concepts, quality validation, test generation and augmentation, testing scopes, approaches, and needs. The paper’s novelty lies in an intelligent AI test modeling chatbot system built and implemented based on an innovative 3-dimensional AI test model for AI-powered functions in intelligent mobile apps to support model-based AI function testing, test data generation, and adequate test coverage result analysis. As a result, a case study is provided using a mental health and emotional intelligence chatbot system, Wysa. It helps in tracking and analyzing mood and helps in sentiment analysis.