FSM Builder: A tool for writing autograded finite automata questions

Eliot Wong Robson*, Samuel Ruggerio*, and Jeff Erickson.

To appear in Proceedings of the 29th Annual ACM Conference on Innovation and Technology in Computer Science Education, 2024.


Abstract:
Deterministic and nondeterministic finite automata (DFAs and NFAs) are abstract models of computation commonly taught in introductory computing theory courses. These models have important applications (such as fast regular expression matching), and are used to introduce formal language theory. Undergraduate students often struggle with understanding these models at first, due to the level of abstraction. As a result, various pedagogical tools have been developed to allow students to practice with these models.

We introduce the FSM Builder, a new pedagogical tool enabling students to practice constructing DFAs and NFAs with a graphical editor, giving personalized feedback and partial credit. The algorithms used for generating these are heavily inspired by previous works. The key advantages to its competitors are greater flexibility and scalability. This is because the FSM Builder is implemented using efficient algorithms from an open source package, allowing for easy extension and question creation.

We discuss the implementation of the tool, how it stands out from previous tools, and takeaways from experiences of using the tool in multiple large courses. Survey results indicate the interface and feedback provided by the tool were useful to students.


Publications - Jeff Erickson (jeffe@illinois.edu) 16 Apr 2024