Merge "Fix Javadoc formatting of org.eclipse.jgit.diff package"
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88eb017c6c
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@ -64,7 +64,7 @@
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/**
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* Supplies the content of a file for {@link DiffFormatter}.
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*
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* <p>
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* A content source is not thread-safe. Sources may contain state, including
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* information about the last ObjectLoader they returned. Callers must be
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* careful to ensure there is no more than one ObjectLoader pending on any
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@ -45,7 +45,7 @@
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/**
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* Compares two {@link Sequence}s to create an {@link EditList} of changes.
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*
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* <p>
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* An algorithm's {@code diff} method must be callable from concurrent threads
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* without data collisions. This permits some algorithms to use a singleton
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* pattern, with concurrent invocations using the same singleton. Other
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@ -45,11 +45,11 @@
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/**
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* Wraps a {@link Sequence} to assign hash codes to elements.
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*
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* <p>
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* This sequence acts as a proxy for the real sequence, caching element hash
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* codes so they don't need to be recomputed each time. Sequences of this type
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* must be used with a {@link HashedSequenceComparator}.
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*
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* <p>
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* To construct an instance of this type use {@link HashedSequencePair}.
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*
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* @param <S>
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@ -45,11 +45,11 @@
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/**
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* Wrap another comparator for use with {@link HashedSequence}.
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*
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* <p>
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* This comparator acts as a proxy for the real comparator, evaluating the
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* cached hash code before testing the underlying comparator's equality.
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* Comparators of this type must be used with a {@link HashedSequence}.
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*
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* <p>
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* To construct an instance of this type use {@link HashedSequencePair}.
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*
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* @param <S>
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@ -45,7 +45,7 @@
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/**
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* Wraps two {@link Sequence} instances to cache their element hash codes.
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*
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* <p>
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* This pair wraps two sequences that contain cached hash codes for the input
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* sequences.
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*
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@ -45,11 +45,11 @@
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/**
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* An extended form of Bram Cohen's patience diff algorithm.
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*
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* <p>
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* This implementation was derived by using the 4 rules that are outlined in
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* Bram Cohen's <a href="http://bramcohen.livejournal.com/73318.html">blog</a>,
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* and then was further extended to support low-occurrence common elements.
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*
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* <p>
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* The basic idea of the algorithm is to create a histogram of occurrences for
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* each element of sequence A. Each element of sequence B is then considered in
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* turn. If the element also exists in sequence A, and has a lower occurrence
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@ -58,34 +58,34 @@
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* lowest number of occurrences is chosen as a split point. The region is split
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* around the LCS, and the algorithm is recursively applied to the sections
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* before and after the LCS.
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*
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* <p>
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* By always selecting a LCS position with the lowest occurrence count, this
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* algorithm behaves exactly like Bram Cohen's patience diff whenever there is a
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* unique common element available between the two sequences. When no unique
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* elements exist, the lowest occurrence element is chosen instead. This offers
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* more readable diffs than simply falling back on the standard Myers' O(ND)
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* algorithm would produce.
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*
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* <p>
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* To prevent the algorithm from having an O(N^2) running time, an upper limit
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* on the number of unique elements in a histogram bucket is configured by
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* {@link #setMaxChainLength(int)}. If sequence A has more than this many
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* elements that hash into the same hash bucket, the algorithm passes the region
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* to {@link #setFallbackAlgorithm(DiffAlgorithm)}. If no fallback algorithm is
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* configured, the region is emitted as a replace edit.
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*
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* <p>
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* During scanning of sequence B, any element of A that occurs more than
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* {@link #setMaxChainLength(int)} times is never considered for an LCS match
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* position, even if it is common between the two sequences. This limits the
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* number of locations in sequence A that must be considered to find the LCS,
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* and helps maintain a lower running time bound.
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*
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* <p>
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* So long as {@link #setMaxChainLength(int)} is a small constant (such as 64),
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* the algorithm runs in O(N * D) time, where N is the sum of the input lengths
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* and D is the number of edits in the resulting EditList. If the supplied
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* {@link SequenceComparator} has a good hash function, this implementation
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* typically out-performs {@link MyersDiff}, even though its theoretical running
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* time is the same.
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*
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* <p>
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* This implementation has an internal limitation that prevents it from handling
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* sequences with more than 268,435,456 (2^28) elements.
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*/
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@ -47,7 +47,7 @@
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/**
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* Support {@link HistogramDiff} by computing occurrence counts of elements.
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*
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* <p>
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* Each element in the range being considered is put into a hash table, tracking
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* the number of times that distinct element appears in the sequence. Once all
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* elements have been inserted from sequence A, each element of sequence B is
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@ -51,56 +51,60 @@
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import org.eclipse.jgit.util.LongList;
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/**
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* Diff algorithm, based on "An O(ND) Difference Algorithm and its
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* Variations", by Eugene Myers.
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*
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* Diff algorithm, based on "An O(ND) Difference Algorithm and its Variations",
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* by Eugene Myers.
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* <p>
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* The basic idea is to put the line numbers of text A as columns ("x") and the
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* lines of text B as rows ("y"). Now you try to find the shortest "edit path"
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* from the upper left corner to the lower right corner, where you can
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* always go horizontally or vertically, but diagonally from (x,y) to
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* (x+1,y+1) only if line x in text A is identical to line y in text B.
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*
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* Myers' fundamental concept is the "furthest reaching D-path on diagonal k":
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* a D-path is an edit path starting at the upper left corner and containing
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* exactly D non-diagonal elements ("differences"). The furthest reaching
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* D-path on diagonal k is the one that contains the most (diagonal) elements
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* which ends on diagonal k (where k = y - x).
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*
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* lines of text B as rows ("y"). Now you try to find the shortest "edit path"
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* from the upper left corner to the lower right corner, where you can always go
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* horizontally or vertically, but diagonally from (x,y) to (x+1,y+1) only if
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* line x in text A is identical to line y in text B.
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* <p>
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* Myers' fundamental concept is the "furthest reaching D-path on diagonal k": a
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* D-path is an edit path starting at the upper left corner and containing
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* exactly D non-diagonal elements ("differences"). The furthest reaching D-path
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* on diagonal k is the one that contains the most (diagonal) elements which
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* ends on diagonal k (where k = y - x).
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* <p>
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* Example:
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*
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* <pre>
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* H E L L O W O R L D
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* ____
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* L \___
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* O \___
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* W \________
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*
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* Since every D-path has exactly D horizontal or vertical elements, it can
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* only end on the diagonals -D, -D+2, ..., D-2, D.
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*
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* Since every furthest reaching D-path contains at least one furthest
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* reaching (D-1)-path (except for D=0), we can construct them recursively.
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*
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* </pre>
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* <p>
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* Since every D-path has exactly D horizontal or vertical elements, it can only
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* end on the diagonals -D, -D+2, ..., D-2, D.
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* <p>
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* Since every furthest reaching D-path contains at least one furthest reaching
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* (D-1)-path (except for D=0), we can construct them recursively.
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* <p>
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* Since we are really interested in the shortest edit path, we can start
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* looking for a 0-path, then a 1-path, and so on, until we find a path that
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* ends in the lower right corner.
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*
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* <p>
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* To save space, we do not need to store all paths (which has quadratic space
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* requirements), but generate the D-paths simultaneously from both sides.
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* When the ends meet, we will have found "the middle" of the path. From the
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* end points of that diagonal part, we can generate the rest recursively.
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*
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* requirements), but generate the D-paths simultaneously from both sides. When
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* the ends meet, we will have found "the middle" of the path. From the end
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* points of that diagonal part, we can generate the rest recursively.
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* <p>
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* This only requires linear space.
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* <p>
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* The overall (runtime) complexity is:
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*
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* The overall (runtime) complexity is
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*
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* O(N * D^2 + 2 * N/2 * (D/2)^2 + 4 * N/4 * (D/4)^2 + ...)
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* = O(N * D^2 * 5 / 4) = O(N * D^2),
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*
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* (With each step, we have to find the middle parts of twice as many regions
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* as before, but the regions (as well as the D) are halved.)
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*
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* So the overall runtime complexity stays the same with linear space,
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* albeit with a larger constant factor.
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* <pre>
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* O(N * D^2 + 2 * N/2 * (D/2)^2 + 4 * N/4 * (D/4)^2 + ...)
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* = O(N * D^2 * 5 / 4) = O(N * D^2),
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* </pre>
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* <p>
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* (With each step, we have to find the middle parts of twice as many regions as
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* before, but the regions (as well as the D) are halved.)
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* <p>
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* So the overall runtime complexity stays the same with linear space, albeit
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* with a larger constant factor.
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*
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* @param <S>
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* type of sequence.
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@ -46,15 +46,15 @@
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/**
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* Arbitrary sequence of elements.
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*
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* <p>
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* A sequence of elements is defined to contain elements in the index range
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* <code>[0, {@link #size()})</code>, like a standard Java List implementation.
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* Unlike a List, the members of the sequence are not directly obtainable.
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*
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* <p>
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* Implementations of Sequence are primarily intended for use in content
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* difference detection algorithms, to produce an {@link EditList} of
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* {@link Edit} instances describing how two Sequence instances differ.
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*
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* <p>
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* To be compared against another Sequence of the same type, a supporting
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* {@link SequenceComparator} must also be supplied.
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*/
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@ -45,11 +45,11 @@
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/**
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* Equivalence function for a {@link Sequence} compared by difference algorithm.
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*
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* <p>
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* Difference algorithms can use a comparator to compare portions of two
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* sequences and discover the minimal edits required to transform from one
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* sequence to the other sequence.
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*
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* <p>
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* Indexes within a sequence are zero-based.
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*
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* @param <S>
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@ -45,7 +45,7 @@
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/**
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* Wraps a {@link Sequence} to have a narrower range of elements.
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*
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* <p>
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* This sequence acts as a proxy for the real sequence, translating element
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* indexes on the fly by adding {@code begin} to them. Sequences of this type
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* must be used with a {@link SubsequenceComparator}.
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@ -45,7 +45,7 @@
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/**
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* Wrap another comparator for use with {@link Subsequence}.
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*
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* <p>
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* This comparator acts as a proxy for the real comparator, translating element
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* indexes on the fly by adding the subsequence's begin offset to them.
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* Comparators of this type must be used with a {@link Subsequence}.
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