Automata Learning for React Web Applications

Peter Grubelnik, Franz Wotawa

Abstract: Testing is an inevitable part of any software engineering process to ensure quality and reliability. Model-based testing is a successful approach for the automated generation of test cases but requires a model of the system under test. Constructing such models can take time and effort. Hence, there is even a need to automate model generation, where automata learning is a promising approach. In this paper, we address the application of automata learning for React web forms used in a wide range of web applications. We provide information regarding a tool we developed to couple web forms to automata learning for obtaining a model. In addition, we discuss the application of the tool, limitations, challenges, and solutions for reducing the state space and making the approach feasible for practical applications.