Date of Completion
Spring 5-1-2018
Thesis Advisor(s)
Parasara S Duggirala
Honors Major
Computer Science
Disciplines
Theory and Algorithms
Abstract
Symbolic finite automata (SFAs) are generalizations of classical finite state automata. Whereas the transitions of classical automata are labeled by characters from some alphabet, the transitions of symbolic automata are labeled by predicates over a Boolean algebra defined on the alphabet. This allows for SFAs to be efficiently constructed over extremely large, and possibly infinite, alphabets. This thesis examines an existing incremental algorithm for the minimization of deterministic finite automata. Several extensions of this algorithm to de- terministic symbolic automata are introduced. Although more efficient algorithms already exist for deterministic SFA minimization, the presented algorithms are uniquely designed to minimize an automaton incrementally. That is, the algorithms may be halted at any time, for computations to be run on a partially minimized SFA that accepts the same language as the input, and then resumed later.
Recommended Citation
Homburg, Jonathan, "Minimization Techniques for Symbolic Automata" (2018). Honors Scholar Theses. 565.
https://digitalcommons.lib.uconn.edu/srhonors_theses/565