71 lines
3.2 KiB
C
71 lines
3.2 KiB
C
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/*
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* Copyright (c) 2016-present, Yann Collet, Facebook, Inc.
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* All rights reserved.
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*
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* This source code is licensed under both the BSD-style license (found in the
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* LICENSE file in the root directory of this source tree) and the GPLv2 (found
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* in the COPYING file in the root directory of this source tree).
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* You may select, at your option, one of the above-listed licenses.
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*/
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/* This match finder leverages techniques used in file comparison algorithms
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* to find matches between a dictionary and a source file.
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*
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* The original motivation for studying this approach was to try and optimize
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* Zstandard for the use case of patching: the most common scenario being
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* updating an existing software package with the next version. When patching,
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* the difference between the old version of the package and the new version
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* is generally tiny (most of the new file will be identical to
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* the old one). In more technical terms, the edit distance (the minimal number
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* of changes required to take one sequence of bytes to another) between the
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* files would be small relative to the size of the file.
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*
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* Various 'diffing' algorithms utilize this notion of edit distance and
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* the corrensponding concept of a minimal edit script between two
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* sequences to identify the regions within two files where they differ.
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* The core algorithm used in this match finder is described in:
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*
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* "An O(ND) Difference Algorithm and its Variations", Eugene W. Myers,
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* Algorithmica Vol. 1, 1986, pp. 251-266,
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* <https://doi.org/10.1007/BF01840446>.
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*
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* Additional algorithmic heuristics for speed improvement have also been included.
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* These we inspired from implementations of various regular and binary diffing
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* algorithms such as GNU diff, bsdiff, and Xdelta.
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*
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* Note: after some experimentation, this approach proved to not provide enough
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* utility to justify the additional CPU used in finding matches. The one area
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* where this approach consistenly outperforms Zstandard even on level 19 is
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* when compressing small files (<10 KB) using a equally small dictionary that
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* is very similar to the source file. For the use case that this was intended,
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* (large similar files) this approach by itself took 5-10X longer than zstd-19 and
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* generally resulted in 2-3X larger files. The core advantage that zstd-19 has
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* over this appraoch for match finding is the overlapping matches. This approach
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* cannot find any.
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*
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* I'm leaving this in the contrib section in case this ever becomes interesting
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* to explore again.
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* */
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#ifndef ZSTD_EDIST_H
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#define ZSTD_EDIST_H
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/*-*************************************
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* Dependencies
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***************************************/
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#include <stddef.h>
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#include "zstd_internal.h" /* ZSTD_Sequence */
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/*! ZSTD_eDist_genSequences() :
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* Will populate the provided ZSTD_Sequence buffer with sequences
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* based on the optimal or near-optimal (depending on 'useHeuristics')
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* edit script between 'dict' and 'src.'
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* @return : the number of sequences found */
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size_t ZSTD_eDist_genSequences(ZSTD_Sequence* sequences,
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const void* dict, size_t dictSize,
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const void* src, size_t srcSize,
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int useHeuristics);
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#endif
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