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Doreatha Conneely
The process of encoding converts information from a source into symbols for communication or storage. Decoding is the reverse process, converting code symbols back into a form that the recipient understands, such as English or/and Spanish.
One reason for coding is to enable communication in places where ordinary plain language, spoken or written, is difficult or impossible. For example, semaphore, where the configuration of flags held by a signaler or the arms of a semaphore tower encodes parts of the message, typically individual letters, and numbers. Another person standing a great distance away can interpret the flags and reproduce the words sent.
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.
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 necessarily a prefix one, must satisfy Kraft's inequality.
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 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 that 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 backward 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.
Biological organisms contain genetic material that is used to control their function and development. This is DNA, which contains units named genes from which messenger RNA is derived. This in turn produces proteins through a genetic code in which a series of triplets (codons) of four possible nucleotides can be translated into one of twenty possible amino acids. A sequence of codons results in a corresponding sequence of amino acids that form a protein molecule; a type of codon called a stop codon signals the end of the sequence.
There are codes using colors, like traffic lights, the color code employed to mark the nominal value of the electrical resistors or that of the trashcans devoted to specific types of garbage (paper, glass, organic, etc.).
Secret codes intended to obscure the real messages, ranging from serious (mainly espionage in military, diplomacy, business, etc.) to trivial (romance, games) can be any kind of imaginative encoding: flowers, game cards, clothes, fans, hats, melodies, birds, etc., in which the sole requirement is the pre-agreement on the meaning by both the sender and the receiver.
International Air Transport Association airport codes are three-letter codes used to designate airports and used for bag tags. Station codes are similarly used on railways but are usually national, so the same code can be used for different stations if they are in different countries.
Occasionally, a code word achieves an independent existence (and meaning) while the original equivalent phrase is forgotten or at least no longer has the precise meaning attributed to the code word. For example, '30' was widely used in journalism to mean "end of story", and has been used in other contexts to signify "the end".[1][2]
The Delaware Code appearing on this site is prepared by the Delaware Code Revisors and the editorial staff of LexisNexis in cooperation with the Division of Research of Legislative Council of the General Assembly, and is considered an official version of the State of Delaware statutory code. This version includes all acts enacted as of October 18, 2023, up to and including 84 Del. Laws, c. 240.
QR Code is a two-dimensional version of the barcode, typically made up of black and white pixel patterns. Denso Wave, a Japanese subsidiary of the Toyota supplier Denso, developed them for marking components in order to accelerate logistics processes for their automobile production. Now, it has found its way into mobile marketing with the widespread adoption of smartphones. "QR" stands for "Quick Response", which refers to the instant access to the information hidden in the Code.
We got our first glance at the FTX codebase on Friday. The prosecution brought out Github screenshots as they questioned cooperating witness Gary Wang, the former CTO of FTX who at various times was responsible for the codebases powering both FTX and Alameda Research. Wang has pleaded guilty to four charges.
Much of the conversation revolved around the allow_negative flag that was introduced to the FTX codebase on August 1, 2019. Wang testified that Sam Bankman-Fried had asked him and Nishad Singh (former FTX engineering director, who has also pleaded guilty) to add the flag. Github screenshots show Singh making a code change to add the column in the database, and adding logic to exempt accounts with the flag from checks that would otherwise determine if they had sufficient funds to withdraw.
Code snippets shown to the jury demonstrated how Nishad Singh wrote some code that would update the insurance fund amount by adding to it the daily trading volume, multiplied by a randomish number around 7,500, and dividing it by a billion, thus making it appear as though the website was referencing a real account balance that was fluctuating as the exchange added funds or withdrew from it to cover losses. In reality, it was all made up.
Also, having some programming experience myself, I agree with your footnote that you probably aren't the best judge of how readable this code is to Joe Q. Public. I enjoyed your suggestion to write messier code when planning to Do Crimes, regardless. ;-)
Although there is some risk of confusing the jury when presenting them with code snippets, prosecutors had Wang step through what the code is doing in a way that seemed pretty clear to me.1 It probably helped that FTX\u2019s engineers wrote decently clean code, with descriptive variable names and concise functions, and chose a very human-readable language (Python).
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