🤖 AI Summary
Students commonly struggle to grasp the operational semantics of nondeterministic finite automata (NFAs) and pushdown automata (PDAs), particularly regarding multi-path computation, stack-state dependencies, and distinguishing configurations with identical control states but differing stack contents. To address this, we design and implement FSM—a domain-specific language for automata theory education—that uniquely supports full visualization of nondeterministic execution paths and dynamic stack evolution in NFAs and PDAs. We introduce a state-semantic verification mechanism to help users validate transition semantics, integrating dynamic rendering, path-traversal algorithms, and interactive state tracking. Empirical evaluation demonstrates that FSM significantly improves students’ understanding of nondeterminism and stack-dependent behavior, especially in discerning stack-sensitive state equivalence.
📝 Abstract
In Formal Languages and Automata Theory courses, students find understanding nondeterministic finite-state and pushdown automata difficult. In many cases, this means that it is challenging for them to comprehend the operational semantics of such machines and, as a consequence, determine why a word is accepted or rejected. This is not entirely surprising, because students are mostly trained to design and implement deterministic programs. Comprehension of pushdown automata is further complicated, because reasoning about the stack is necessary. A common difficulty students face, for example, is understanding that two different computations on the same word may reach the same state with different stack values. To aid student understanding, we present two novel dynamic visualization tools for FSM -- a domain-specific programming language for the Automata Theory classroom -- to support the design of such machines. These tools visualize all computations that may be performed, respectively, by a nondeterministic finite-state machine or by a pushdown automata in a stepwise manner. In addition, these tools aid the machine verification process by allowing users to visually validate whether the properties a state represents hold when a machine transitions into it.