LongestCommonSubsequence.java
- /*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements. See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
- package org.apache.commons.text.similarity;
- /**
- * A similarity algorithm indicating the length of the longest common subsequence between two strings.
- *
- * <p>
- * The Longest common subsequence algorithm returns the length of the longest subsequence that two strings have in
- * common. Two strings that are entirely different, return a value of 0, and two strings that return a value
- * of the commonly shared length implies that the strings are completely the same in value and position.
- * <i>Note.</i> Generally this algorithm is fairly inefficient, as for length <i>m</i>, <i>n</i> of the input
- * <code>CharSequence</code>'s <code>left</code> and <code>right</code> respectively, the runtime of the
- * algorithm is <i>O(m*n)</i>.
- * </p>
- *
- * <p>
- * This implementation is based on the Longest Commons Substring algorithm
- * from <a href="https://en.wikipedia.org/wiki/Longest_common_subsequence_problem">
- * https://en.wikipedia.org/wiki/Longest_common_subsequence_problem</a>.
- * </p>
- *
- * <p>For further reading see:</p>
- *
- * <p>Lothaire, M. <i>Applied combinatorics on words</i>. New York: Cambridge U Press, 2005. <b>12-13</b></p>
- *
- * @since 1.0
- */
- public class LongestCommonSubsequence implements SimilarityScore<Integer> {
- /**
- * Calculates longestCommonSubsequence similarity score of two <code>CharSequence</code>'s passed as
- * input.
- *
- * @param left first character sequence
- * @param right second character sequence
- * @return longestCommonSubsequenceLength
- * @throws IllegalArgumentException
- * if either String input {@code null}
- */
- @Override
- public Integer apply(final CharSequence left, final CharSequence right) {
- // Quick return for invalid inputs
- if (left == null || right == null) {
- throw new IllegalArgumentException("Inputs must not be null");
- }
- return logestCommonSubsequence(left, right).length();
- }
- /**
- *
- * Computes the longestCommonSubsequence between the two <code>CharSequence</code>'s passed as
- * input.
- *
- * <p>
- * Note, a substring and
- * subsequence are not necessarily the same thing. Indeed, <code>abcxyzqrs</code> and
- * <code>xyzghfm</code> have both the same common substring and subsequence, namely <code>xyz</code>. However,
- * <code>axbyczqrs</code> and <code>abcxyzqtv</code> have the longest common subsequence <code>xyzq</code> because a
- * subsequence need not have adjacent characters.
- * </p>
- *
- * <p>
- * For reference, we give the definition of a subsequence for the reader: a <i>subsequence</i> is a sequence that can be
- * derived from another sequence by deleting some elements without changing the order of the remaining elements.
- * </p>
- *
- * @param left first character sequence
- * @param right second character sequence
- * @return lcsLengthArray
- * @throws IllegalArgumentException
- * if either String input {@code null}
- */
- public CharSequence logestCommonSubsequence(final CharSequence left, final CharSequence right) {
- // Quick return
- if (left == null || right == null) {
- throw new IllegalArgumentException("Inputs must not be null");
- }
- StringBuilder longestCommonSubstringArray = new StringBuilder(Math.max(left.length(), right.length()));
- int[][] lcsLengthArray = longestCommonSubstringLengthArray(left, right);
- int i = left.length() - 1;
- int j = right.length() - 1;
- int k = lcsLengthArray[left.length()][right.length()] - 1;
- while (k >= 0) {
- if (left.charAt(i) == right.charAt(j)) {
- longestCommonSubstringArray.append(left.charAt(i));
- i = i - 1;
- j = j - 1;
- k = k - 1;
- } else if (lcsLengthArray[i + 1][j] < lcsLengthArray[i][j + 1]) {
- i = i - 1;
- } else {
- j = j - 1;
- }
- }
- return longestCommonSubstringArray.reverse().toString();
- }
- /**
- *
- * Computes the lcsLengthArray for the sake of doing the actual lcs calculation. This is the
- * dynamic programming portion of the algorithm, and is the reason for the runtime complexity being
- * O(m*n), where m=left.length() and n=right.length().
- *
- * @param left first character sequence
- * @param right second character sequence
- * @return lcsLengthArray
- */
- public int[][] longestCommonSubstringLengthArray(final CharSequence left, final CharSequence right) {
- int[][] lcsLengthArray = new int[left.length() + 1][right.length() + 1];
- for (int i=0; i < left.length(); i++) {
- for (int j=0; j < right.length(); j++) {
- if (i == 0) {
- lcsLengthArray[i][j] = 0;
- }
- if (j == 0) {
- lcsLengthArray[i][j] = 0;
- }
- if (left.charAt(i) == right.charAt(j)) {
- lcsLengthArray[i + 1][j + 1] = lcsLengthArray[i][j] + 1;
- } else {
- lcsLengthArray[i + 1][j + 1] = Math.max(lcsLengthArray[i + 1][j], lcsLengthArray[i][j + 1]);
- }
- }
- }
- return lcsLengthArray;
- }
- }