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7z (file Format)
7z is a compressed archive file format that supports several different data compression, encryption and pre-processing algorithms. The 7z format initially appeared as implemented by the 7-Zip archiver. The 7-Zip program is publicly available under the terms of the GNU Lesser General Public License. The LZMA SDK 4.62 was placed in the public domain in December 2008. The latest stable version of 7-Zip and LZMA SDK is version 24.09. The 7z file format specification is distributed with 7-Zip's source code since 2015. The specification can be found in plain text format in the "doc" sub-directory of the source code distribution. Features and enhancements The 7z format provides the following main features: * Open, modular architecture that allows any compression, conversion, or encryption method to be stacked. * High compression ratios (depending on the compression method used). * AES-256 bit encryption. * Zip 2.0 (Legacy) Encryption * Large file support (up to approximately 1 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Igor Pavlov (programmer)
7-Zip is a free and open-source file archiver, a utility used to place groups of files within compressed containers known as "archives". It is developed by Igor Pavlov and was first released in 1999. 7-Zip has its own archive format called 7z introduced in 2001, but can read and write several others. The program can be used from a Windows graphical user interface that also features shell integration, or from a command-line interface as the command 7z that offers cross-platform support (see versions for details). An obsolete port of 7-Zip to POSIX systems was called p7zip. Most of the 7-Zip source code is under the LGPL-2.1-or-later license; the unRAR code, however, is under the LGPL-2.1-or-later license with an "unRAR restriction", which states that developers are not permitted to use the code to reverse-engineer the RAR compression algorithm. Since version 21.01 alpha, Linux support has been added to the 7zip project. Archive formats 7z By default, 7-Zip creates 7z-fo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Header (computing)
In information technology, header is supplemental data placed at the beginning of a block of data being stored or transmitted. In data transmission, the data following the header is sometimes called the ''Payload (computing), payload'' or ''HTML element#body, body''. It is vital that header composition follows a clear and unambiguous specification or format, to allow for parsing. Examples * E-mail header: The text (body) is preceded by header lines indicating sender, recipient, subject, sending time stamp, receiving time stamps of all intermediate and the final mail transfer agents, and much more. * Similar headers are used in Usenet (NNTP) messages, and HTTP headers. * In a data packet sent via the Internet, the data (payload) are preceded by header information such as the sender's and the recipient's IP addresses, the Communications protocol, protocol governing the format of the payload and several other formats. The header's format is specified in the Internet Protocol, see IP h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bzip
bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm. It only compresses single files and is not a file archiver. It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting. bzip2 was initially released in 1996 by Julian Seward. It compresses most files more effectively than older LZW and Deflate compression algorithms but is slower. bzip2 is particularly efficient for text data, and decompression is relatively fast. The algorithm uses several layers of compression techniques, such as run-length encoding (RLE), Burrows–Wheeler transform (BWT), move-to-front transform (MTF), and Huffman coding. bzip2 compresses data in blocks between 100 and 900 kB and uses the Burrows–Wheeler transform to convert frequently recurring character sequences into strings of identical letters. The move-to-front transform and Huffman coding are then a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Huffman Coding
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression. The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Doctor of Science, Sc.D. student at Massachusetts Institute of Technology, MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". The output from Huffman's algorithm can be viewed as a variable-length code table for encoding a source symbol (such as a character in a file). The algorithm derives this table from the estimated probability or frequency of occurrence (''weight'') for each possible value of the source symbol. As in other entropy encoding methods, more common symbols are generally represented using fewer bits than less common symbols. Huffman's method can be efficiently implemented, finding a code in time linear time, linear to the number of input weigh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Move To Front
The move-to-front (MTF) transform is an encoding of data (typically a stream of bytes) designed to improve the performance of entropy encoding techniques of compression. When efficiently implemented, it is fast enough that its benefits usually justify including it as an extra step in data compression algorithm. This algorithm was first published by Boris Ryabko under the name of "book stack" in 1980. Subsequently, it was rediscovered by J.K. Bentley et al. in 1986, as attested in the explanatory note. The transform The main idea is that each symbol in the data is replaced by its index in the stack of “recently used symbols”. For example, long sequences of identical symbols are replaced by as many zeroes, whereas when a symbol that has not been used in a long time appears, it is replaced with a large number. Thus at the end the data is transformed into a sequence of integers; if the data exhibits a lot of local correlations, then these integers tend to be small. Let us giv ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Burrows–Wheeler Transform
The Burrows–Wheeler transform (BWT) rearranges a character string into runs of similar characters, in a manner that can be reversed to recover the original string. Since compression techniques such as move-to-front transform and run-length encoding are more effective when such runs are present, the BWT can be used as a preparatory step to improve the efficiency of a compression algorithm, and is used this way in software such as bzip2. The algorithm can be implemented efficiently using a suffix array thus reaching linear time complexity. It was invented by David Wheeler in 1983, and later published by him and Michael Burrows in 1994. Their paper included a compression algorithm, called the Block-sorting Lossless Data Compression Algorithm or BSLDCA, that compresses data by using the BWT followed by move-to-front coding and Huffman coding or arithmetic coding. Description The transform is done by constructing a matrix (known as the Burrows-Wheeler Matrix) whose rows are the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bzip2
bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm. It only compresses single files and is not a file archiver. It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting. bzip2 was initially released in 1996 by Julian Seward. It compresses most files more effectively than older LZW and Deflate compression algorithms but is slower. bzip2 is particularly efficient for text data, and decompression is relatively fast. The algorithm uses several layers of compression techniques, such as run-length encoding (RLE), Burrows–Wheeler transform (BWT), move-to-front transform (MTF), and Huffman coding. bzip2 compresses data in blocks between 100 and 900 kB and uses the Burrows–Wheeler transform to convert frequently recurring character sequences into strings of identical letters. The move-to-front transform and Huffman coding are then ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lempel–Ziv–Markov Chain Algorithm
The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. It has been used in the 7z format of the 7-Zip archiver since 2001. This algorithm uses a Dictionary coder, dictionary compression scheme somewhat similar to the LZ77 algorithm published by Abraham Lempel and Jacob Ziv in 1977 and features a high compression ratio (generally higher than bzip2) - LZMA Unix Port was finally replaced by xz which features better and faster compression; from here we know even LZMA Unix Port was a lot better than gzip and bzip2. and a variable compression-dictionary size (up to 4 Gigabyte, GB), while still maintaining decompression speed similar to other commonly used compression algorithms. LZMA2 is a simple container format that can include both uncompressed data and LZMA data, possibly with multiple different LZMA encoding parameters. LZMA2 supports arbitrarily scalable multithreaded compression and decompression and efficient compression ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Tree
In computer science, a binary tree is a tree data structure in which each node has at most two children, referred to as the ''left child'' and the ''right child''. That is, it is a ''k''-ary tree with . A recursive definition using set theory is that a binary tree is a triple , where ''L'' and ''R'' are binary trees or the empty set and ''S'' is a singleton (a single–element set) containing the root. From a graph theory perspective, binary trees as defined here are arborescences. A binary tree may thus be also called a bifurcating arborescence, a term which appears in some early programming books before the modern computer science terminology prevailed. It is also possible to interpret a binary tree as an undirected, rather than directed graph, in which case a binary tree is an ordered, rooted tree. Some authors use rooted binary tree instead of ''binary tree'' to emphasize the fact that the tree is rooted, but as defined above, a binary tree is always rooted. In ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Range Encoding
Range coding (or range encoding) is an entropy coding method defined by G. Nigel N. Martin in a 1979 paper,G. Nigel N. Martin, ''Range encoding: An algorithm for removing redundancy from a digitized message'' Video & Data Recording Conference, , UK, July 24–27, 1979. which effectively rediscovered the FIFO arithmetic code first introduced by Richard Clark Pasco in 1976. Given a stream of symbols and their probabilities, a range coder produces a space-efficient stream of bits to represent these symbols and, given the stream and the probabilities, a range decoder re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Markov Chain
In probability theory and statistics, a Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs ''now''." A countably infinite sequence, in which the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain (CTMC). Markov processes are named in honor of the Russian mathematician Andrey Markov. Markov chains have many applications as statistical models of real-world processes. They provide the basis for general stochastic simulation methods known as Markov chain Monte Carlo, which are used for simulating sampling from complex probability distributions, and have found application in areas including Bayesian statistics, biology, chemistry, economics, fin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Coding
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have an expected code length greater than or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \operatorname E_ ell(d(x))\geq \operatorname E_ \log_b(P(x))/math>, where \ell is the function specifying the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simple ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
