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For more * information on the Apache Software Foundation, please see * <http://www.apache.org/>. * */ package org.apache.commons.jrcs.diff; import java.util.*; /** * Implements a simple differencing algortithm.<p> * * @date $Date: 2010-11-03 09:15:52 -0400 (Wed, 03 Nov 2010) $ * @version $Revision: 84222 $ * @author <a href="mailto:juanco@suigeneris.org">Juanco Anez</a> * * <p><b>Overview of Algorithm</b></p> * * <p><i>by <a * href='http://www.topmeadow.net/bwm'> bwm</a> * </p> * * <p>The algorithm is optimised for situations where the input sequences * have few repeated objects. If it is given input with many repeated * objects it will report sub-optimal changes. However, given appropriate * input, it is fast, and linear in memory usage.</p> * * <p>The algorithm consists of the following steps:</p> * <ul> * <li>compute an equivalence set for the input data</li> * <li>translate each element of the orginal * and revised input sequences to a member of the equivalence set * </li> * <li>match the the input sequences to determine the deltas, i.e. * the differences between the original and revised sequences.</li> * </ul> * * <p>The first step is to compute a an equivalence set for the input data. * The equivalence set is computed from objects that are in the original * input sequence</p> * <pre> * eq(x) = the index of the first occurence of x in the original sequence. * </pre> * * <p>With this equivalence function, the algorithm can compare integers rather * than strings, which is considerably more efficient.</p> * * <p>The second step is to compute the datastructure on which the * algorithm will operate. Having computed the equivalence function * in the previous step, we can compute two arrays where * indx[i] = eqs(orig[i]) and jndx[i] = eqs(rev[i]). The algorithm can * now operate on indx and jndx instead of orig and rev. Thus, comparisons * are then on O(int == int) instead of O(Object.equals(Object)). * </p> * * <p>The algorithm now matches indx and jndx. Whilst indx[i] == jndx[i] * it skips matching objects in the sequence. In seeking to match objects * in the input sequence it assumes that each object is likely to be unique. * It uses the known characteristics of the unique equivalence function. It can * tell from the eq value if this object appeared in the other sequence * at all. If it did not, there is no point in searching for a match.</p> * * <p>Recall that the eq function value is the index earliest occurrence in * the orig sequence. This information is used to search efficiently for * the next match. The algorithm is perfect when all input objects are * unique, but degrades when input objects are not unique. When input * objects are not unique an optimal match may not be found, but a * correct match will be.</p> * * <p>Having identified common matching objects in the orig and revised * sequences, the differences between them are easily computed. * </p> * * @see Delta * @see Revision * Modifications: * * 27/Apr/2003 bwm * Added some comments whilst trying to figure out the algorithm * * 03 May 2003 bwm * Created this implementation class by refactoring it out of the Diff * class to enable plug in difference algorithms * */ public class SimpleDiff implements DiffAlgorithm { static final int NOT_FOUND_i = -2; static final int NOT_FOUND_j = -1; static final int EOS = Integer.MAX_VALUE; public SimpleDiff() { } protected int scan(int[] ndx, int i, int target) { while (ndx[i] < target) { i++; } return i; } /** * Compute the difference between original and revised sequences. * * @param orig The original sequence. * @param rev The revised sequence to be compared with the original. * @return A Revision object describing the differences. * @throws DifferenciationFailedException if the diff could not be computed. */ public Revision diff(Object[] orig, Object[] rev) throws DifferentiationFailedException { // create map eqs, such that for each item in both orig and rev // eqs(item) = firstOccurrence(item, orig); Map eqs = buildEqSet(orig, rev); // create an array such that // indx[i] = NOT_FOUND_i if orig[i] is not in rev // indx[i] = firstOccurrence(orig[i], orig) int[] indx = buildIndex(eqs, orig, NOT_FOUND_i); // create an array such that // jndx[j] = NOT_FOUND_j if orig[j] is not in rev // jndx[j] = firstOccurrence(rev[j], orig) int[] jndx = buildIndex(eqs, rev, NOT_FOUND_j); // what in effect has been done is to build a unique hash // for each item that is in both orig and rev // and to label each item in orig and new with that hash value // or a marker that the item is not common to both. eqs = null; // let gc know we're done with this Revision deltas = new Revision(); //!!! new Revision() int i = 0; int j = 0; // skip matching // skip leading items that are equal // could be written // for (i=0; indx[i] != EOS && indx[i] == jndx[i]; i++); // j = i; for (; indx[i] != EOS && indx[i] == jndx[j]; i++, j++) { /* void */ } while (indx[i] != jndx[j]) { // only equal if both == EOS // they are different int ia = i; int ja = j; // size of this delta do { // look down rev for a match // stop at a match // or if the FO(rev[j]) > FO(orig[i]) // or at the end while (jndx[j] < 0 || jndx[j] < indx[i]) { j++; } // look down orig for a match // stop at a match // or if the FO(orig[i]) > FO(rev[j]) // or at the end while (indx[i] < 0 || indx[i] < jndx[j]) { i++; } // this doesn't do a compare each line with each other line // so it won't find all matching lines } while (indx[i] != jndx[j]); // on exit we have a match // they are equal, reverse any exedent matches // it is possible to overshoot, so count back matching items while (i > ia && j > ja && indx[i - 1] == jndx[j - 1]) { --i; --j; } deltas.addDelta(Delta.newDelta(new Chunk(orig, ia, i - ia), new Chunk(rev, ja, j - ja))); // skip matching for (; indx[i] != EOS && indx[i] == jndx[j]; i++, j++) { /* void */ } } return deltas; } /** * create a <code>Map</code> from each common item in orig and rev * to the index of its first occurrence in orig * * @param orig the original sequence of items * @param rev the revised sequence of items */ protected Map buildEqSet(Object[] orig, Object[] rev) { // construct a set of the objects that orig and rev have in common // first construct a set containing all the elements in orig Set items = new HashSet(Arrays.asList(orig)); // then remove all those not in rev items.retainAll(Arrays.asList(rev)); Map eqs = new HashMap(); for (int i = 0; i < orig.length; i++) { // if its a common item and hasn't been found before if (items.contains(orig[i])) { // add it to the map eqs.put(orig[i], Integer.valueOf(i)); // and make sure its not considered again items.remove(orig[i]); } } return eqs; } /** * build a an array such each a[i] = eqs([i]) or NF if eqs([i]) undefined * * @param eqs a mapping from Object to Integer * @param seq a sequence of objects * @param NF the not found marker */ protected int[] buildIndex(Map eqs, Object[] seq, int NF) { int[] result = new int[seq.length + 1]; for (int i = 0; i < seq.length; i++) { Integer value = (Integer) eqs.get(seq[i]); if (value == null || value.intValue() < 0) { result[i] = NF; } else { result[i] = value.intValue(); } } result[seq.length] = EOS; return result; } }