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//! Rust implementation of the L* active automata learning algorithm.
//!
//! This crate provides:
//! - Core automata data structures (`Automata`, `State`, `Transition`)
//! - Knowledge base abstractions for answering membership queries
//! - Multiple equivalence-test strategies
//! - An `LSTAR` learner that infers Mealy-style automata from observations
/// Automata model and DOT import/export helpers.
/// Equivalence-test strategies used by the learner.
/// Knowledge-base traits and implementations for query resolution.
/// Letter/symbol representation.
/// Main L* learner implementation.
/// Observation-table implementation used by L*.
/// Query data model.
/// Word abstraction built from letters.
// `automata` now contains `state`, `transition`, and `dot_parser` submodules
/// Deterministic transducer representation.
pub use Automata;
/// Automaton state.
pub use State;
/// Automaton transition.
pub use Transition;
/// Parse a DOT graph into an [`Automata`].
pub use ;
/// BDist equivalence testing strategy.
pub use BDistMethod;
/// Trait implemented by equivalence testing strategies.
pub use EquivalenceTest;
/// Composition of multiple equivalence testing strategies.
pub use MultipleEqtests;
/// Random-walk equivalence testing strategy.
pub use RandomWalkMethod;
/// W-method equivalence testing strategy.
pub use WMethodEQ;
/// Alias for [`WMethodEQ`].
pub use WpMethodEQ;
/// Default caching knowledge base.
pub use KnowledgeBase;
/// Knowledge tree data structures used by knowledge bases.
pub use ;
/// Letter model and empty-letter marker.
pub use ;
/// L* learner entry point.
pub use LSTAR;
/// Observation table used by the learner.
pub use ObservationTable;
/// Membership query structure.
pub use OutputQuery;
/// Word model.
pub use Word;