Abstract: There is provided a computer implemented method of compressing a baseline dataset comprising a sequence of a plurality of instances of a plurality of unique data elements, the method comprising: providing a weight function that calculates an increasing value for a weight for each one of the plurality of instances of each one of the plurality of unique data elements in the baseline dataset, as a function of increasing number of previously processed sequential locations of each of the plurality of instances of each respective unique data element within the baseline dataset relative to a current sequential location of the baseline dataset, computing an encoding for the baseline dataset according to a distribution of the weight function computed for the plurality of unique data elements in the baseline dataset, and creating a compressed dataset according to the encoding.

Abstract: A method for a compression scheme comprising encryption, comprising: receiving, as input, data comprising a plurality of data elements; constructing a Huffman tree coding representation of the input data based on a known encryption key, wherein the Huffman tree comprises nodes that are compression codes having compression code lengths corresponding to respective occurrence probabilities of the data elements, and wherein the encryption key specifies a subset of the nodes to be selected for an encryption process; selecting the subset of nodes in the Huffman tree for the encryption process, based on the encryption key; applying, to each sub-tree of the Huffman tree that is rooted at one of the nodes in the subset, a specified transformation, based on the encryption key; and generating an output data file based, at least in part, on the applying.

Abstract: There is provided a computer implemented method of compressing a baseline dataset comprising a sequence of a plurality of instances of a plurality of unique data elements, the method comprising: providing a weight function that calculates an increasing value for a weight for each one of the plurality of instances of each one of the plurality of unique data elements in the baseline dataset, as a function of increasing number of previously processed sequential locations of each of the plurality of instances of each respective unique data element within the baseline dataset relative to a current sequential location of the baseline dataset, computing an encoding for the baseline dataset according to a distribution of the weight function computed for the plurality of unique data elements in the baseline dataset, and creating a compressed dataset according to the encoding.

Abstract: There is provided a computer-implemented method of compressing a baseline dataset, comprising: creating a weight function that calculates a weight for each instance of each unique data elements in the baseline dataset, as a function of sequential locations of each of the instances of each respective unique data element within the baseline dataset, creating an output dataset storing a codeword for each one of the unique data elements, wherein codewords are according to a compression rule defining data elements associated with a relatively higher weight as being associated with codewords that are relatively shorter, dynamically creating the compressed dataset by sequentially iterating, for each current sequential location of the baseline dataset: determining an encoded data element mapped to the respective data element of the current sequential location according to the weight function, and adjusting the codewords of the output dataset according to the current weights to maintain the compression rule.

Abstract: There is provided a computer-implemented method of compressing a baseline dataset, comprising: creating a weight function that calculates a weight for each instance of each unique data elements in the baseline dataset, as a function of sequential locations of each of the instances of each respective unique data element within the baseline dataset, creating an output dataset storing a codeword for each one of the unique data elements, wherein codewords are according to a compression rule defining data elements associated with a relatively higher weight as being associated with codewords that are relatively shorter, dynamically creating the compressed dataset by sequentially iterating, for each current sequential location of the baseline dataset: determining an encoded data element mapped to the respective data element of the current sequential location according to the weight function, and adjusting the codewords of the output dataset according to the current weights to maintain the compression rule.

Abstract: The present invention relates to a system and method of generating an encoded bidirectional delta file to be used for reconstructing target and source files by decoding said bidirectional delta file, each of said target and source files comprising one or more substantially identical substrings, wherein each of said substrings is encoded within said bidirectional delta file by using a single pointer.

Abstract: To enhance the distribution or backup of data similar to previously distributed or backed up data, to provide similarity testing, and other benefits, a first body of data T of size n is compressed with respect to a second body of data S of size m in-place; that is, the memory containing S is overwritten from left to right so that at no time is more than a total of MAX{m,n}+O(1) memory used.

Abstract: To enhance the distribution or backup of data similar to previously distributed or backed up data, to provide similarity testing, and other benefits, a first body of data T of size n is compressed with respect to a second body of data S of size m in-place; that is, the memory containing S is overwritten from left to right so that at no time is more than a total of MAX{m,n}+O(1) memory used.