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go-code

Gocode is a helper tool which is intended to be integrated with your source code editor, like vim, neovim and emacs. It provides several advanced capabilities, which currently includes: Context-sensitive autocompletion.

go-code.pl

 

 

In information theory and computer science, a code is usually considered as an algorithm that uniquely represents symbols from some source alphabet, by encoded strings, which may be in some other target alphabet. An extension of the code for representing sequences of symbols over the source alphabet is obtained by concatenating the encoded strings. Before giving a mathematically precise definition, this is a brief example. The mapping {\displaystyle C=\{\,a\mapsto 0,b\mapsto 01,c\mapsto 011\,\}}C = \{\, a\mapsto 0, b\mapsto 01, c\mapsto 011\,\} is a code, whose source alphabet is the set {\displaystyle \{a,b,c\}}\{a,b,c\} and whose target alphabet is the set {\displaystyle \{0,1\}}\{0,1\}. Using the extension of the code, the encoded string 0011001011 can be grouped into codewords as 0 011 0 01 011, and these in turn can be decoded to the sequence of source symbols acabc. Using terms from formal language theory, the precise mathematical definition of this concept is as follows: let S and T be two finite sets, called the source and target alphabets, respectively. A code {\displaystyle C:\,S\to T^{*}}C:\, S \to T^* is a total function mapping each symbol from S to a sequence of symbols over T, and the extension of {\displaystyle C}C to a homomorphism of {\displaystyle S^{*}}S^{*} into {\displaystyle T^{*}}T^{*}, which naturally maps each sequence of source symbols to a sequence of target symbols, is referred to as its extension. Variable-length codes Main article: Variable-length code In this section, we consider codes that encode each source (clear text) character by a code word from some dictionary, and concatenation of such code words give us an encoded string. Variable-length codes are especially useful when clear text characters have different probabilities; see also entropy encoding. A prefix code is a code with the "prefix property": there is no valid code word in the system that is a prefix (start) of any other valid code word in the set. Huffman coding is the most known algorithm for deriving prefix codes. Prefix codes are widely referred to as "Huffman codes" even when the code was not produced by a Huffman algorithm. Other examples of prefix codes are country calling codes, the country and publisher parts of ISBNs, and the Secondary Synchronization Codes used in the UMTS WCDMA 3G Wireless Standard. Kraft's inequality characterizes the sets of codeword lengths that are possible in a prefix code. Virtually any uniquely decodable one-to-many code, not necessary a prefix one, must satisfy Kraft's inequality. Error-correcting codes Main article: Error detection and correction See also: Block code Codes may also be used to represent data in a way more resistant to errors in transmission or storage. This so-called error-correcting code works by including carefully crafted redundancy with the stored (or transmitted) data. Examples include Hamming codes, Reed–Solomon, Reed–Muller, Walsh–Hadamard, Bose–Chaudhuri–Hochquenghem, Turbo, Golay, Goppa, low-density parity-check codes, and space–time codes. Error detecting codes can be optimised to detect burst errors, or random errors. Examples Codes in communication used for brevity A cable code replaces words (e.g. ship or invoice) with shorter words, allowing the same information to be sent with fewer characters, more quickly, and less expensively. Codes can be used for brevity. When telegraph messages were the state of the art in rapid long-distance communication, elaborate systems of commercial codes that encoded complete phrases into single mouths (commonly five-minute groups) were developed, so that telegraphers became conversant with such "words" as BYOXO ("Are you trying to weasel out of our deal?"), LIOUY ("Why do you not answer my question?"), BMULD ("You're a skunk!"), or AYYLU ("Not clearly coded, repeat more clearly."). Code words were chosen for various reasons: length, pronounceability, etc. Meanings were chosen to fit perceived needs: commercial negotiations, military terms for military codes, diplomatic terms for diplomatic codes, any and all of the preceding for espionage codes. Codebooks and codebook publishers proliferated, including one run as a front for the American Black Chamber run by Herbert Yardley between the First and Second World Wars. The purpose of most of these codes was to save on cable costs. The use of data coding for data compression predates the computer era; an early example is the telegraph Morse code where more-frequently used characters have shorter representations. Techniques such as Huffman coding are now used by computer-based algorithms to compress large data files into a more compact form for storage or transmission. Character encodings Main article: Character encoding Character encodings are representations of textual data. A given character encoding may be associated with a specific character set (the collection of characters which it can represent), though some character sets have multiple character encodings and vice versa. Character encodings may be broadly grouped according to the number of bytes required to represent a single character: there are single byte encodings, multibyte (also called wide) encodings, and variable-width (also called variable-length) encodings. The earliest character encodings were single-byte, the best known example of which is ASCII. ASCII remains in use today, for example in HTTP headers. However, single-byte encodings cannot model character sets with more than 256 characters. Scripts which require large character sets such as Chinese, Japanese and Korean must be represented with multibyte encodings. Early multibyte encodings were fixed-length, meaning that although each character was represented by more than one byte, all characters used the same number of bytes ("word length"), making them suitable for decoding with a lookup table. The final group, variable-width encodings, is a subset of multibyte encodings. These use more complex encoding and decoding logic to efficiently represent large character sets while keeping the representations of more commonly used characters shorter or maintaining backwards compatibility properties. This group includes UTF-8, an encoding of the Unicode character set; UTF-8 is the most common encoding of text media on the Internet.

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