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* and other copyright owners as documented in the project's IP log.
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package org.eclipse.jgit.diff;
import java.util.ArrayList;
import java.util.List;
/**
* An extended form of Bram Cohen's patience diff algorithm.
* <p>
* This implementation was derived by using the 4 rules that are outlined in
* Bram Cohen's <a href="http://bramcohen.livejournal.com/73318.html">blog</a>,
* and then was further extended to support low-occurrence common elements.
* <p>
* The basic idea of the algorithm is to create a histogram of occurrences for
* each element of sequence A. Each element of sequence B is then considered in
* turn. If the element also exists in sequence A, and has a lower occurrence
* count, the positions are considered as a candidate for the longest common
* subsequence (LCS). After scanning of B is complete the LCS that has the
* lowest number of occurrences is chosen as a split point. The region is split
* around the LCS, and the algorithm is recursively applied to the sections
* before and after the LCS.
* <p>
* By always selecting a LCS position with the lowest occurrence count, this
* algorithm behaves exactly like Bram Cohen's patience diff whenever there is a
* unique common element available between the two sequences. When no unique
* elements exist, the lowest occurrence element is chosen instead. This offers
* more readable diffs than simply falling back on the standard Myers' O(ND)
* algorithm would produce.
* <p>
* To prevent the algorithm from having an O(N^2) running time, an upper limit
* on the number of unique elements in a histogram bucket is configured by
* {@link #setMaxChainLength(int)}. If sequence A has more than this many
* elements that hash into the same hash bucket, the algorithm passes the region
* to {@link #setFallbackAlgorithm(DiffAlgorithm)}. If no fallback algorithm is
* configured, the region is emitted as a replace edit.
* <p>
* During scanning of sequence B, any element of A that occurs more than
* {@link #setMaxChainLength(int)} times is never considered for an LCS match
* position, even if it is common between the two sequences. This limits the
* number of locations in sequence A that must be considered to find the LCS,
* and helps maintain a lower running time bound.
* <p>
* So long as {@link #setMaxChainLength(int)} is a small constant (such as 64),
* the algorithm runs in O(N * D) time, where N is the sum of the input lengths
* and D is the number of edits in the resulting EditList. If the supplied
* {@link SequenceComparator} has a good hash function, this implementation
* typically out-performs {@link MyersDiff}, even though its theoretical running
* time is the same.
* <p>
* This implementation has an internal limitation that prevents it from handling
* sequences with more than 268,435,456 (2^28) elements.
*/
public class HistogramDiff extends LowLevelDiffAlgorithm {
/** Algorithm to use when there are too many element occurrences. */
DiffAlgorithm fallback = MyersDiff.INSTANCE;
/**
* Maximum number of positions to consider for a given element hash.
*
* All elements with the same hash are stored into a single chain. The chain
* size is capped to ensure search is linear time at O(len_A + len_B) rather
* than quadratic at O(len_A * len_B).
*/
int maxChainLength = 64;
/**
* Set the algorithm used when there are too many element occurrences.
*
* @param alg
* the secondary algorithm. If null the region will be denoted as
* a single REPLACE block.
*/
public void setFallbackAlgorithm(DiffAlgorithm alg) {
fallback = alg;
}
/**
* Maximum number of positions to consider for a given element hash.
*
* All elements with the same hash are stored into a single chain. The chain
* size is capped to ensure search is linear time at O(len_A + len_B) rather
* than quadratic at O(len_A * len_B).
*
* @param maxLen
* new maximum length.
*/
public void setMaxChainLength(int maxLen) {
maxChainLength = maxLen;
}
public <S extends Sequence> void diffNonCommon(EditList edits,
HashedSequenceComparator<S> cmp, HashedSequence<S> a,
HashedSequence<S> b, Edit region) {
new State<S>(edits, cmp, a, b).diffRegion(region);
}
private class State<S extends Sequence> {
private final HashedSequenceComparator<S> cmp;
private final HashedSequence<S> a;
private final HashedSequence<S> b;
private final List<Edit> queue = new ArrayList<Edit>();
/** Result edits we have determined that must be made to convert a to b. */
final EditList edits;
State(EditList edits, HashedSequenceComparator<S> cmp,
HashedSequence<S> a, HashedSequence<S> b) {
this.cmp = cmp;
this.a = a;
this.b = b;
this.edits = edits;
}
void diffRegion(Edit r) {
diffReplace(r);
while (!queue.isEmpty())
diff(queue.remove(queue.size() - 1));
}
private void diffReplace(Edit r) {
Edit lcs = new HistogramDiffIndex<S>(maxChainLength, cmp, a, b, r)
.findLongestCommonSequence();
if (lcs != null) {
// If we were given an edit, we can prove a result here.
//
if (lcs.isEmpty()) {
// An empty edit indicates there is nothing in common.
// Replace the entire region.
//
edits.add(r);
} else {
queue.add(r.after(lcs));
queue.add(r.before(lcs));
}
} else if (fallback instanceof LowLevelDiffAlgorithm) {
LowLevelDiffAlgorithm fb = (LowLevelDiffAlgorithm) fallback;
fb.diffNonCommon(edits, cmp, a, b, r);
} else if (fallback != null) {
SubsequenceComparator<HashedSequence<S>> cs = subcmp();
Subsequence<HashedSequence<S>> as = Subsequence.a(a, r);
Subsequence<HashedSequence<S>> bs = Subsequence.b(b, r);
EditList res = fallback.diffNonCommon(cs, as, bs);
edits.addAll(Subsequence.toBase(res, as, bs));
} else {
edits.add(r);
}
}
private void diff(Edit r) {
switch (r.getType()) {
case INSERT:
case DELETE:
edits.add(r);
break;
case REPLACE:
if (r.getLengthA() == 1 && r.getLengthB() == 1)
edits.add(r);
else
diffReplace(r);
break;
case EMPTY:
default:
throw new IllegalStateException();
}
}
private SubsequenceComparator<HashedSequence<S>> subcmp() {
return new SubsequenceComparator<HashedSequence<S>>(cmp);
}
}
}