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``` for f in $(find . \( -path ./.git -o -path ./tests/fuzz/corpora -o -path ./tests/regression/data-cache -o -path ./tests/regression/cache \) -prune -o -type f); do sed -i '/Copyright .* \(Yann Collet\)\|\(Meta Platforms\)/ s/Copyright .*/Copyright (c) Meta Platforms, Inc. and affiliates./' $f; done git checkout HEAD -- build/VS2010/libzstd-dll/libzstd-dll.rc build/VS2010/zstd/zstd.rc tests/test-license.py contrib/linux-kernel/test/include/linux/xxhash.h examples/streaming_compression_thread_pool.c lib/legacy/zstd_v0*.c lib/legacy/zstd_v0*.h nano ./programs/windres/zstd.rc nano ./build/VS2010/zstd/zstd.rc nano ./build/VS2010/libzstd-dll/libzstd-dll.rc ``` |
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| .. | ||
| README.md | ||
| zstd_edist.c | ||
| zstd_edist.h | ||
Edit Distance Match Finder
/* This match finder leverages techniques used in file comparison algorithms
* to find matches between a dictionary and a source file.
*
* The original motivation for studying this approach was to try and optimize
* Zstandard for the use case of patching: the most common scenario being
* updating an existing software package with the next version. When patching,
* the difference between the old version of the package and the new version
* is generally tiny (most of the new file will be identical to
* the old one). In more technical terms, the edit distance (the minimal number
* of changes required to take one sequence of bytes to another) between the
* files would be small relative to the size of the file.
*
* Various 'diffing' algorithms utilize this notion of edit distance and
* the corresponding concept of a minimal edit script between two
* sequences to identify the regions within two files where they differ.
* The core algorithm used in this match finder is described in:
*
* "An O(ND) Difference Algorithm and its Variations", Eugene W. Myers,
* Algorithmica Vol. 1, 1986, pp. 251-266,
* <https://doi.org/10.1007/BF01840446>.
*
* Additional algorithmic heuristics for speed improvement have also been included.
* These we inspired from implementations of various regular and binary diffing
* algorithms such as GNU diff, bsdiff, and Xdelta.
*
* Note: after some experimentation, this approach proved to not provide enough
* utility to justify the additional CPU used in finding matches. The one area
* where this approach consistently outperforms Zstandard even on level 19 is
* when compressing small files (<10 KB) using an equally small dictionary that
* is very similar to the source file. For the use case that this was intended,
* (large similar files) this approach by itself took 5-10X longer than zstd-19 and
* generally resulted in 2-3X larger files. The core advantage that zstd-19 has
* over this approach for match finding is the overlapping matches. This approach
* cannot find any.
*
* I'm leaving this in the contrib section in case this ever becomes interesting
* to explore again.
* */