/**
 * Levenshtein Distance
 * src/metric/Levenshtein.ts
 *
 * @see https://en.wikipedia.org/wiki/Levenshtein_distance
 *
 * The Levenshtein distance is a classic metric for measuring the minimum number
 * of single-character edits (insertions, deletions, or substitutions) required
 * to change one string into another.
 *
 * It is widely used in approximate string matching, spell checking, and natural
 * language processing.
 *
 * @module Metric
 * @name LevenshteinDistance
 * @author Paul Köhler (komed3)
 * @license MIT
 */
import type { MetricCompute, MetricInput, MetricOptions } from '../utils/Types';
import { Metric } from './Metric';
export interface LevenshteinRaw {
    dist: number;
    maxLen: number;
}
/**
 * LevenshteinDistance class extends the Metric class to implement the Levenshtein distance algorithm.
 */
export declare class LevenshteinDistance extends Metric<LevenshteinRaw> {
    /**
     * Constructor for the Levenshtein class.
     *
     * Initializes the Levenshtein metric with two input strings
     * or arrays of strings and optional options.
     *
     * Metric is symmetrical.
     *
     * @param {MetricInput} a - First input string or array of strings
     * @param {MetricInput} b - Second input string or array of strings
     * @param {MetricOptions} [opt] - Options for the metric computation
     */
    constructor(a: MetricInput, b: MetricInput, opt?: MetricOptions);
    /**
     * Calculates the Levenshtein distance between two strings.
     *
     * @param {string} a - First string
     * @param {string} b - Second string
     * @param {number} m - Length of the first string
     * @param {number} n - Length of the second string
     * @param {number} maxLen - Maximum length of the strings
     * @return {MetricCompute< LevenshteinRaw >} - Object containing the similarity result and raw distance
     */
    protected compute(a: string, b: string, m: number, n: number, maxLen: number): MetricCompute<LevenshteinRaw>;
}