/**
 * A trie data structure optimized for approximate string matching,
 * allowing for flexible yet controlled searches based on lexicographical
 * distance.
 *
 * This class provides methods to add items with associated search strings and
 * to perform searches within a specified maximum Levenshtein distance.
 *
 * Levenshtein distance is a metric used in computer science and information
 * theory to measure the difference between two sequences of characters.
 * It's also known as the edit distance.
 *
 * Specifically, the Levenshtein distance between two words is the minimum
 * number of single-character edits (insertions, deletions, or substitutions)
 * required to change one word into the other.
 *
 * For example:
 *
 * The Levenshtein distance between "kitten" and "sitting" is 3:
 *
 * kitten → sitten (substitution of "s" for "k")
 * sitten → sittin (substitution of "i" for "e")
 * sittin → sitting (insertion of "g" at the end)
 * The Levenshtein distance between "book" and "back" is 2:
 *
 * book → bock (substitution of "c" for "o")
 * bock → back (substitution of "a" for "o")
 *
 * Using Levenshtein distance in this class allows the search to return
 * results that are close matches to the search term, even if they're
 * not exact matches. The results are then sorted based on this distance,
 * with the closest matches (lowest Levenshtein distance) appearing first
 * in the results array.
 *
 * This approach is particularly useful for implementing features like
 * autocorrect, spell-checking, or fuzzy search functionality where you
 * want to find close matches to a given input string.
 *
 * ------------------------------------------------------------------------
 *
 * Usage:
 * 1. Create an instance of FuzzyTrie:
 *    const trie = new FuzzyTrie<YourItemType>();
 *
 * 2. Add items to the trie:
 *    trie.addItemToTrie("search string", yourItem);
 *    You can add multiple items with the same or different search strings.
 *
 * 3. Perform a fuzzy search:
 *    const results = trie.searchItems("query string", maxAllowedDistance);
 *    - "query string" is the search term
 *    - maxAllowedDistance is the maximum Levenshtein distance allowed (default is 2)
 *
 * 4. The search returns an array of items sorted by their Levenshtein distance
 *    from the query string, with the closest matches first.
 *
 * Example:
 * const trie = new FuzzyTrie<string>();
 * trie.addItemToTrie("apple", "Apple fruit");
 * trie.addItemToTrie("banana", "Banana fruit");
 * const results = trie.searchItems("aple", 1);
 * // results will contain ["Apple fruit"]
 */
declare class FuzzyTrie<T> {
    private rootNode;
    private calculateLevenshteinDistance;
    addItemToTrie(searchString: string, itemToAdd: T): void;
    searchItems(queryString: string, maxAllowedDistance?: number): T[];
}
export { FuzzyTrie };