Lempel-Ziv Algorithms. LZ77 (Sliding Window). Variants: LZSS (Lempel-Ziv- Storer-Szymanski); Applications: gzip, Squeeze, LHA, PKZIP, ZOO. LZ78 ( Dictionary. version of LZ77, called LZSS, and one improved version of LZ78, called LZW. The base of the LZ77 algorithm is a sliding window technique with two buffers, one. CULZSS algorithm proposed in [7] parallelizes the LZSS algorithm at two levels. The first level is to split the input data into equally sized chunks and each chunk.

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After writing my version 0. The pointers are for each node’s left child, right child, and parent. The key algorithm is supposed to be the same algorithm used by gzip and may be implemented using the following C fragment:.

Archived on January 10, So, to keep things simple, my first implementation used a brute force sequential search to match the string to be encoded to strings in the dictionary.

In order to be able to use smaller tables, I needed a key that would distribute M long strings fairly evenly through the hash table. As with everything else that I’ve written, my LZSS implementation left and still leaves room for improvement.

In general earlier versions are simpler maybe easier to follow and later versions are easier to use as libraries and better suited for projects taking advantage of the LGPL.


The source code implementing a binary tree search is contained in the file tree.


Accessed on August 3, The worst case occurs when the binary search tree resembles lzds linked list and each node only has one child. There’s only one additional complication. By using this site, you agree to the Terms of Use and Privacy Policy. The first search I implemented was a sequential search.

LZSS (LZ77) Discussion and Implementation

As stated above, one of my goals was to provide an LZSS implementation that is easy to read and easy to debug. By not encoding strings that offer less than one byte of savings, the minimum encoded length is three characters.

If I encode the offset and length of a string in a 16 bit word, that leaves me with 4 bits for the length. If the first characters match, I check the characters that follow. The larger Nthe longer it takes to search the whole dictionary for a match and the more bits will be required to store the offset into the dictionary.

I don’t know who to credit with the discovery of this technique, but akgorithm allowed my version 0. Further discussion of LZSS with links to other documentation and libraries may be found at http: Uses new bit algorihtm library integer based get and put bits functions, making it easier to change the dictionary size. If I don’t have a match, I move to the next character in the sliding window. In actuality, the linked lists approach, is a solution involving hash tables where the hash key is the first character of the string and collisions are stored in a linked list.


While I was studying the algorithm, I came across some implementations that stored encoded flags in groups of eight followed by the characters or encoded strings that algorihhm represent.

c – understanding this LZSS based decompression algorithm – Stack Overflow

Similarly writing an encoded string would require 17 bits, 1 bit for the flag and 16 bits for the code. The rest of this section documents some of what I have tried so far. In my implementation, all pointers left, right, and parent are all unsigned int indices into the sliding window dictionary.

Haruhiko Okumura implementation of My e-mail address is: If you need to use 9 bits, you might as well have a symbol dictionary so that you can have more entries.

Shift a copy of the symbols algoritym to the decoded output into the dictionary.

For example, encoding a string from a dictionary of symbols, algofithm allowing for matches of up to 15 symbols, will require 16 bits to store an offset and a length. KMP is smart enough to skip ahead and resume by comparing string[0] to dictionary[3]which happens to be a match in this example.

Linked lists are a natural choice for implementing such dynamic lists. None of the archives contain executable programs.