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List of binary codes
List of binary codes
from Wikipedia

This is a list of some binary codes that are (or have been) used to represent text as a sequence of binary digits "0" and "1". Fixed-width binary codes use a set number of bits to represent each character in the text, while in variable-width binary codes, the number of bits may vary from character to character.

Five-bit binary codes

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Several different five-bit codes were used for early punched tape systems.

Five bits per character only allows for 32 different characters, so many of the five-bit codes used two sets of characters per value referred to as FIGS (figures) and LTRS (letters), and reserved two characters to switch between these sets. This effectively allowed the use of 60 characters.

Standard five-bit standard codes are:

The following early computer systems each used its own five-bit code:

The steganographic code, commonly known as Bacon's cipher uses groups of 5 binary-valued elements to represent letters of the alphabet.

Six-bit binary codes

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Six bits per character allows 64 distinct characters to be represented.

Examples of six-bit binary codes are:

See also: Six-bit character codes

Seven-bit binary codes

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Examples of seven-bit binary codes are:

Eight-bit binary codes

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10-bit binary codes

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  • AUTOSPEC – Also known as Bauer code. AUTOSPEC repeats a five-bit character twice, but if the character has odd parity, the repetition is inverted.[4]
  • Decabit – A datagram of electronic pulses which are transmitted commonly through power lines. Decabit is mainly used in Germany and other European countries.

16-bit binary codes

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32-bit binary codes

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Variable-length binary codes

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  • UTF-8 – Encodes characters in a way that is mostly compatible with ASCII but can also encode the full repertoire of Unicode characters with sequences of up to four 8-bit bytes.
  • UTF-16 – Extends UCS-2 to cover the whole of Unicode with sequences of one or two 16-bit elements
  • GB 18030 – A full-Unicode variable-length code designed for compatibility with older Chinese multibyte encodings
  • Huffman coding – A technique for expressing more common characters using shorter bit strings than are used for less common characters

Data compression systems such as Lempel–Ziv–Welch can compress arbitrary binary data. They are therefore not binary codes themselves but may be applied to binary codes to reduce storage needs.

Other

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  • Morse code is a variable-length telegraphy code, which traditionally uses a series of long and short pulses to encode characters. It relies on gaps between the pulses to provide separation between letters and words, as the letter codes do not have the "prefix property". This means that Morse code is not necessarily a binary system, but in a sense may be a ternary system, with a 10 for a "dit" or a "dot", a 1110 for a dash, and a 00 for a single unit of separation. Morse code can be represented as a binary stream by allowing each bit to represent one unit of time. Thus a "dit" or "dot" is represented as a 1 bit, while a "dah" or "dash" is represented as three consecutive 1 bits. Spaces between symbols, letters, and words are represented as one, three, or seven consecutive 0 bits. For example, "NO U" in Morse code is "— .   — — —       . . —", which could be represented in binary as "1110100011101110111000000010101110". If, however, Morse code is represented as a ternary system, "NO U" would be represented as "1110|10|00|1110|1110|1110|00|00|00|10|10|1110".

See also

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Binary codes are systems for representing or symbols using sequences of binary digits (0s and 1s), forming the fundamental language of digital electronics, , and transmission. These codes map elements from a source —such as digits, letters, or instructions—into fixed- or variable-length binary strings, enabling efficient storage, processing, and communication while accommodating specific requirements like detection or minimal hardware changes during transitions. A comprehensive list of binary codes spans several categories, each designed for particular applications in digital systems. Weighted binary codes, such as (BCD or 8421 code), , and 2421 code, encode decimal numbers using fixed weights assigned to bit positions, allowing straightforward decimal-to-binary conversion but often with redundancy for arithmetic operations. Non-weighted codes like the assign binary values to minimize the number of bit changes between consecutive numbers, reducing errors in mechanical or rotary encoders. For alphanumeric representation, character encoding schemes include ASCII (American Standard Code for Information Interchange), which uses 7 or 8 bits to encode 128 basic Latin characters and control symbols, its extensions like for legacy mainframe systems, and modern standards like , which employs variable-length encodings to support a wide range of scripts and characters worldwide. In error management, error-detecting and correcting codes add redundancy to detect or repair transmission errors; parity bits enable simple even- or odd-parity checks for single-error detection, while provide single-error correction in block formats like the (7,4) binary , which uses 3 parity bits for 4 data bits. Advanced types include cyclic codes for burst error correction and convolutional codes for , widely applied in and storage media. Compression-oriented codes, such as , generate variable-length prefix-free binary strings based on symbol probabilities to optimize data efficiency. These diverse binary codes underpin modern technologies, from microprocessors to satellite communications, balancing factors like code rate, minimum distance, and decoding complexity.

Fundamentals of Binary Codes

Definition and Classification

Binary codes are numerical representations of using sequences of binary digits, known as bits, where each bit is either 0 or 1, serving as the fundamental unit of in digital systems. These codes encode characters, numbers, symbols, or instructions to facilitate storage, processing, and transmission in computers and other digital devices, aligning with the binary states of electronic circuits such as on and off. In essence, binary codes translate abstract into a machine-readable format that underpins all modern computing operations. Binary codes are broadly classified into fixed-length and variable-length types based on the number of bits assigned to each symbol. Fixed-length codes allocate a constant number of bits to every symbol, such as 7 or 8 bits per character in the ASCII standard, enabling straightforward encoding and decoding. Variable-length codes, in contrast, assign varying bit lengths to symbols, typically shorter codes to more frequent symbols for greater efficiency, as seen in or representations. Fixed-length codes offer advantages in , as both encoders and decoders know the exact bit count per in advance, facilitating easy alignment, parallel transmission, and reduced risk of errors without needing additional separators. However, they can waste space for infrequently used symbols, as all symbols receive equal bit allocation regardless of usage frequency, leading to inefficiency in data compression. Variable-length codes address this by optimizing average code length but introduce complexity in decoding, requiring mechanisms like prefix properties or stop bits to identify symbol boundaries and avoid framing errors. Common bit widths for binary codes range from 4 bits, used for basic representations, to 32 bits for more complex data types in early computing architectures. In applications like , 5-bit fixed-length codes such as Baudot enabled efficient transmission of text over limited bandwidth, while variable-length schemes like (up to 4-5 bits per character) minimized signaling time. These widths laid the groundwork for digital communication and computing systems, balancing simplicity with the need for representing diverse symbols.

Historical Evolution

The development of binary codes traces its roots to 19th-century telegraphy, where introduced in the 1830s as a variable-length binary signaling system using dots and dashes to represent letters and numbers for electrical transmission over wires. This precursor to fixed binary encodings enabled efficient long-distance communication but lacked standardization for mechanical processing. In the 1870s, advanced the field with his 5-bit code for telegraphic , assigning fixed combinations of five binary units (mark or space) to characters, which supported simultaneous transmission of multiple messages and marked the shift toward compact, machine-readable formats. The transition to computing in the late 19th and early 20th centuries built on these foundations through Herman Hollerith's punched cards for the 1890 U.S. Census, which used 12 binary positions (hole or no hole) per column to encode demographic data, enabling automated tabulation and processing of over 60 million cards. By the 1940s, early electronic computers like (completed in 1945) used decimal representations with ring counters for numerical handling. Subsequent machines, such as , adopted binary representations, with many employing 6- to 7-bit codes derived from (BCD) for character and numerical handling, facilitating programmable operations in scientific and military applications. Post-World War II efforts focused on standardization to support interoperable systems. In , the American Standards Association published (ASA X3.4-1963) as a 7-bit code encoding 128 characters, including letters, digits, and controls, to unify data exchange across teleprinters, computers, and networks. Concurrently, developed the 8-bit in the 1960s for its System/360 mainframes, extending BCD principles to 256 characters while prioritizing punch-card compatibility and internal efficiency. In the , the limitations of fixed-length codes for global languages prompted the Unicode Consortium's formation in 1991, introducing a universal standard with variable- and fixed-width encodings up to 21 bits per character to encompass over 140,000 symbols across scripts. This evolved into in 1992, a backward-compatible variable-length encoding using 1 to 4 bytes, designed by and to optimize ASCII storage while supporting multilingual text. Key events included ARPANET's adoption of ASCII in the early 1970s for protocols like , enabling standardized text transmission across its growing nodes. Meanwhile, persisted in mainframes through the 1970s and beyond, sustaining legacy applications in enterprise computing despite the rise of ASCII-based systems.

Short Fixed-Length Binary Codes

Five-Bit Binary Codes

Five-bit binary codes represent one of the earliest forms of structured binary encoding, utilizing 32 possible combinations (2^5) to encode a limited set of characters, primarily for alphanumeric representation in and . These codes emerged in the as conceptual tools and evolved into practical systems by the late , enabling efficient transmission over wire-based networks despite the constraints of only 32 distinct symbols, which necessitated mechanisms like shifting to access additional characters. An early precursor to modern binary codes is Francis Bacon's bilateral cipher, introduced in his 1623 work De Augmentis Scientiarum, which employed a 5-bit binary system for steganographic purposes. In this method, each letter of the Roman alphabet (excluding J and V, with I/J and U/V combined to fit 24 symbols) is assigned a unique 5-bit sequence using 'A' for 0 and 'B' for 1, hidden within innocuous text by varying typefaces or patterns to conceal the message. For example, 'A' is encoded as AAAAA (00000 in binary), while 'B' is AAAAB (00001), allowing the secret to blend seamlessly with carrier text for covert communication. This approach marked an innovative use of binary principles in long before electrical transmission. The practical application of 5-bit codes in communication began with Émile Baudot's system, patented in 1874 and detailed in 1877 publications, which introduced uniform-length binary sequences for letters, figures, and controls over telegraph lines. Standardized as International Telegraph Alphabet No. 1 (ITA1) in 1929 by the International Telegraph Union (now ITU), it supported 32 symbols including 26 uppercase letters, basic punctuation, and shift controls, with four positions reserved for national variants to accommodate limited non-Latin characters. This was superseded by International Telegraph Alphabet No. 2 (ITA2), also known as the Baudot-Murray code, adopted internationally in 1931 following Donald Murray's 1901 improvements to Baudot's design, which rearranged codes for more efficient printing on paper tape. ITA2's structure relies on a 5-bit serial transmission, where shift mechanisms double the effective character set beyond 32 symbols: the Letters shift (LTRS, binary 11111) selects alphabetic mode for the subsequent characters until overridden, while the Figures shift (FIGS, binary 11011) switches to numerals, punctuation, and symbols. Controls such as Null (NUL, 00000), Line Feed (LF, 11110), and (CR, 01011) occupy dedicated codes, ensuring compatibility with early teletypewriters and allowing transmission speeds up to 100 on shared lines. A representative encoding in ITA2 letters mode assigns 'A' the binary sequence 00011, transmitted as five sequential marks or spaces on a 5-unit tape or wire signal. In the mid-20th century, 5-bit codes like ITA2 were adapted for early computing peripherals, particularly punch tape systems that stored and input data for machines such as the series in the , where 11/16-inch tape accommodated five-hole patterns for the 32 combinations. This limited encoding supported only the basic Latin alphabet and numerals, restricting applications to text-based without diacritics or extended symbols, and was common in systems like the IAS computer family for interfacing with teleprinters. The inherent 32-symbol constraint highlighted the need for more bits in later codes but provided a reliable medium for transfer in resource-limited environments. Telegraph transmissions using these 5-bit codes faced notable error rates due to on long-distance lines, with historical measurements on circuits up to 100 showing character error probabilities often exceeding 1 in 1,000 under adverse conditions, necessitating parity checks or manual retransmissions for accuracy. This vulnerability underscored the codes' legacy in prompting advancements in error detection, while their simplicity facilitated widespread adoption in global telegraph networks until the .

Six-Bit Binary Codes

Six-bit binary codes emerged in the mid-20th century as an advancement over five-bit encodings, providing 64 possible character combinations to support expanded alphanumeric representations in and communication systems. These codes facilitated the inclusion of uppercase letters, digits, and a range of symbols without relying on shift mechanisms, which were common limitations in earlier five-bit telegraph codes like the International Telegraph Alphabet No. 2. This increased capacity proved essential for handling more complex data in military and early commercial applications, where efficiency in transmission and storage was paramount. The Fieldata code, developed by the U.S. Army Signal Corps in the late , exemplifies early six-bit encodings designed for military use. It encoded 64 characters, encompassing uppercase letters, digits 0-9, and various punctuation and mathematical symbols, to standardize and transmission in secure communications. Fieldata was integral to projects like the MOBIDIC (MObile DIgital Computer), a portable system deployed in the for operations, including the processing and relay of . Its adoption across compatible hardware from multiple manufacturers ensured in data links, supporting applications such as data transmission where rapid, error-resistant encoding was critical. In the , variants like Transcode extended six-bit principles for teletypewriter and remote systems, incorporating additional control characters for efficient message handling. Transcode, utilized in IBM's communication protocols such as those for the 2780 Remote Job Entry station, optimized transmission by reducing overhead compared to longer codes, transmitting alphanumeric data with 26 uppercase letters, 10 digits, and 28 symbols plus controls. Similarly, Control Data Corporation's (CDC) six-bit display code, introduced with the in , served as a Transcode-like variant for peripherals and teletype interfaces in CDC computers, enabling direct control in print heads for six-bit alphabets. These codes prioritized compactness, allowing six-bit words to represent full characters in early peripherals like punch card readers and teleprinters. IBM's early six-bit variants, known as Interchange Code (BCDIC), were tailored for punch card systems before the transition to eight-bit standards in the late 1960s. Employed in machines like the from 1959, BCDIC used six bits per character to encode zones and numeric values, supporting business with uppercase letters, digits, and basic symbols. For instance, the letter 'A' was encoded as 100001 in binary, corresponding to the B (zone) and 1 (numeric) bits in the 1401's bit weighting scheme. This format bridged mechanics—where 12-row columns mapped to six bits—with binary computation, enhancing throughput in early peripherals without the need for multi-column representations. The advantages of six-bit codes over five-bit predecessors were evident in these applications: they doubled the symbol set to 64, accommodating radar telemetry and peripheral I/O for and commercial tabulation without introducing complex shifting, thereby improving data density and operational speed.

Seven-Bit Binary Codes

Seven-bit binary codes utilize seven bits to represent 128 unique combinations (2^7), serving as a foundational standard for encoding text characters and control signals in early and transmission systems. These codes emerged as an advancement over earlier six-bit encodings used in systems like IBM's BCD, providing sufficient capacity for basic alphanumeric and punctuation sets while conserving bandwidth in telegraphic and applications. The American Standard Code for Information Interchange (ASCII), first published in 1963 by the X3.2 subcommittee of the American Standards Association (ASA), standardized 128 codes for the , digits, , and special symbols. It allocates codes 0–31 for non-printable control characters (such as NULL, BEL, and ESC), 33–126 for 94 printable characters (including uppercase and lowercase letters, digits 0–9, and symbols like ! and @), and 127 for the delete () character. This structure ensured among diverse hardware from manufacturers like , Honeywell, and RCA, facilitating data exchange in and computing. In 1967, the (ISO) introduced Recommendation 646 (later formalized as ISO/IEC 646) as an international adaptation of ASCII, maintaining core compatibility while permitting national variants to replace certain invariant symbols with locale-specific characters. For instance, the British variant (ISO-IR-4) substitutes the symbol (£) for the (#) at code 35, and the () for the (|) at code 124, allowing better support for regional currencies and without altering the fundamental 128-code framework. These variants, such as ISO-IR-6 for French (replacing certain symbols with è, à, and û) and ISO-IR-8 for German (with § and ß), numbered over 20 by the , promoting global standardization while accommodating linguistic diversity. In terms of encoding, seven-bit codes assign each character a unique binary sequence across bit positions b6 (most significant) to b0 (least significant), with no inherent parity but often paired with an eighth bit for even or odd parity in transmission to detect single-bit errors. A representative example is the uppercase letter 'A', encoded as 1000001 in binary (bit positions b6=1, b5=0, ..., b0=1), which corresponds to decimal value 65. This binary-to-decimal mapping enabled straightforward implementation in hardware like teleprinters and early computers. The enduring legacy of seven-bit codes lies in their role as the bedrock for protocols in (e.g., SMTP) and the , where ASCII ensures reliable text handling in headers and basic content, paving the way for subsequent eight-bit extensions in systems requiring multilingual support.

Medium Fixed-Length Binary Codes

Eight-Bit Binary Codes

Eight-bit binary codes represent an expansion of the 7-bit ASCII framework, utilizing all 256 possible combinations to encode extended character sets including accented letters, symbols, and control characters for diverse linguistic needs. The Extended Binary Coded Decimal Interchange Code (EBCDIC), developed by IBM in 1963–1964 and announced alongside the System/360 mainframe computers, stands as one of the pioneering 8-bit encoding schemes. EBCDIC organizes its 256 code points into distinct zones for numeric digits (hex F0–F9), uppercase letters (hex C1–C9, D1–D9, and E2–E9), lowercase letters (hex 81–89, 91–99, and A2–A9), and punctuation, featuring a non-contiguous alphabetic ordering that evolved from earlier 6-bit BCDIC systems. For instance, the uppercase 'A' is assigned the binary code 11000001 (hex C1), separating letters from numerals to facilitate legacy punched-card compatibility. IBM produced over 57 national variants of EBCDIC to accommodate regional scripts, though its irregular layout posed challenges for interoperability with ASCII-based systems. In response to the need for international standardization, the ISO/IEC 8859 series emerged starting in 1987, providing 8-bit extensions to ASCII by reserving the upper 128 code points (hex 80–FF) for language-specific characters while preserving the lower 128 for basic ASCII compatibility. The inaugural part, ISO/IEC 8859-1 (Latin-1), targets Western European languages and incorporates diacritics such as á, ç, and ñ, enabling support for up to 191 graphic characters across French, German, Spanish, and similar tongues. Subsequent parts in the series, like 8859-2 for Central European languages, followed this model, promoting uniform data exchange in computing and . Microsoft's , introduced in the early 1990s as part of its system, serves as a proprietary extension of ISO/IEC 8859-1, filling undefined gaps in Latin-1 with additional printable symbols such as curly quotes, em dashes, and the (€ at hex 80). This encoding became the default for Windows applications and web content in Western locales until the widespread adoption of in the late 2000s, supporting legacy text processing in environments like and . These 8-bit codes found primary applications in mainframe computing ( on systems), early personal computers, and internationalized software, where their 256 slots facilitated the inclusion of diacritics, line-drawing , and box characters essential for regional text rendering and terminal displays. Despite their limitations in handling non-Latin scripts, they bridged the gap between 7-bit ASCII and modern universal encodings, influencing data interchange in legacy systems through the 1990s.

Ten-Bit Binary Codes

Ten-bit binary codes emerged as a specialized extension in mid-20th-century data transmission, bridging the gap between shorter fixed-length codes and emerging standards by providing enhanced for reliability in noisy channels. These codes were particularly suited to radioteleprinter systems, where the additional bits enabled error detection without resorting to more complex variable-length schemes. Unlike the 32-symbol capacity of 5-bit International Telegraph Alphabet No. 2 (ITA2) codes or the 128 symbols of 7-bit ASCII, ten-bit formats allowed for structured repetition to support industrial applications requiring robust communication over long distances. A key example is the Bauer code, developed in the 1960s and also referred to as AUTOSPEC or Autospec-Bauer. This synchronous code was classified under the U10 family of ten-unit radioteleprinter systems by the International Radio Consultative Committee (CCIR) in 1966, emphasizing its role in single-channel data transmission for automatic reception testing. It was primarily used in high-frequency (HF) radio links, operating at baud rates such as 62.3, 68.5, 102.7, or 137 Bd with (FSK) modulation and a 270 Hz shift. The structure of the Bauer code consists of 10 bits per character: the first five bits encode an ITA2 symbol, while the second five bits repeat this sequence, inverted if the original has odd parity to enable . For instance, an even-parity ITA2 character like the letter "A" (binary 11000) would be transmitted as 11000 followed by 11000; an odd-parity character like "B" (binary 10011) becomes 10011 followed by 01100 (inverted). This repetition-based design improved transmission integrity in industrial settings without introducing variable complexity. In practice, AUTOSPEC facilitated industrial data transmission, notably by British coastal stations communicating with rigs starting in the late , where reliable messaging was critical for operational specifications and coordination. The code's fixed 10-bit length offered advantages over 8-bit predecessors by incorporating built-in redundancy for error-prone environments like offshore radio paths, achieving higher effective density for specialized symbols. However, its adoption remained limited due to the widespread shift toward 7- and 8-bit standards like ASCII in the , which better supported general and international interoperability.

Long Fixed-Length Binary Codes

Sixteen-Bit Binary Codes

Sixteen-bit binary codes emerged to overcome the constraints of eight-bit encodings, which could only represent 256 characters and struggled with diverse non-Latin scripts requiring thousands of glyphs. These 16-bit schemes expanded capacity to code points, enabling broader multilingual support in computing systems. The Universal Character Set-2 (UCS-2), formalized in 1993 under ISO/IEC 10646-1, provides a straightforward fixed-length 16-bit encoding for the initial code points of the Universal Character Set. Each character is represented by two bytes, with options for big-endian or little-endian byte to ensure across platforms. UTF-16, introduced in 1996 as part of 2.0, builds on UCS-2 by adding surrogate pairs to access the complete Unicode space of 1,114,112 code points. It encodes most characters in a single 16-bit unit but uses two 16-bit units (32 bits total) for others via high surrogates (U+D800 to U+DBFF) paired with low surrogates (U+DC00 to U+DFFF), allowing representation of characters in supplementary planes without altering legacy UCS-2 processing for the Basic Multilingual Plane. This mechanism ensures while extending coverage. UCS-2 and UTF-16 found prominent applications in the 1990s kernel for internal text handling and in Java's implementations, where UTF-16 serves as the native format for efficient manipulation of international text.

Thirty-Two-Bit Binary Codes

Thirty-two-bit binary codes represent a category of fixed-length encodings capable of addressing vast character spaces, particularly suited for comprehensive coverage of the standard without the need for surrogate pairs required in shorter formats. These codes allocate 32 bits (4 bytes) per character, enabling direct mapping of any code point to a single code unit and simplifying internal processing tasks. Unlike 16-bit encodings that pair units for extended ranges, 32-bit codes offer straightforward indexing and uniform memory usage, though at the cost of higher storage demands. The primary example is UTF-32, a Unicode encoding form that directly encodes all Unicode scalar values from U+0000 to U+10FFFF using a single 32-bit unsigned integer per , formalized in Unicode Technical Report #19 and incorporated into the Standard starting with version 3.1 in 2001. This approach ensures a one-to-one correspondence between code points and code units, making it ideal for applications requiring fixed-width access, such as string manipulation in programming languages. However, its fixed 4-byte length per character results in significant memory overhead, approximately four times that of ASCII for Latin text, limiting its use primarily to in-memory representations rather than storage or transmission. As of 17.0 (released September 2025), the standard continues to expand within the defined code space. In the 1980s, ISO working groups began developing a 32-bit character code as an extension of national and regional standards, predating the formalization of UCS-4, the 31-bit (padded to 32-bit) precursor defined in ISO/IEC 10646-1:1993. In practice, UTF-32 finds application in internal software processing, such as XML parsers that convert variable-length inputs to fixed-width formats for efficient parsing and validation. Endianness poses a key consideration, with UTF-32BE (big-endian) placing the most significant byte first and UTF-32LE (little-endian) reversing this order; a byte order mark (BOM, U+FEFF) is often prepended to resolve ambiguity in cross-platform environments. Languages like Python 3 and C (via char32_t) leverage UTF-32 internally for Unicode string operations, prioritizing simplicity over compactness. The theoretical capacity of a 32-bit code is 4,294,967,296 distinct values (2^{32}), far exceeding Unicode's current limit of 1,114,112 assigned . For example, the Latin capital 'A' (U+0041) encodes as the 32-bit value 0x00000041, or in binary:

00000000 00000000 01000001

00000000 00000000 01000001

This direct padding of the code point value exemplifies the encoding's transparency, contrasting with surrogate mechanisms in 16-bit precursors like UTF-16.

Variable-Length Binary Codes

Prefix and Huffman Codes

Prefix codes are a class of variable-length binary codes designed for instantaneous decodability, meaning that no codeword is a prefix of another codeword in the set. This allows the decoder to identify the end of a codeword as soon as it is fully received, without needing to look ahead at subsequent bits. The validity of such codes is governed by the Kraft inequality, which states that for a prefix code with codeword lengths lil_i (where ii indexes the symbols), the sum 2li1\sum 2^{-l_i} \leq 1 must hold; this condition ensures that the code can be represented by a binary tree without overlaps. Huffman coding, introduced by David A. Huffman in 1952, provides an optimal method for constructing prefix codes that minimize the average codeword length for a given symbol probability distribution. The algorithm builds a binary tree by starting with leaf nodes for each symbol weighted by its frequency, then repeatedly merging the two nodes with the lowest frequencies into a parent node until a single root remains; bits 0 and 1 are assigned to the branches leading to the children. This greedy approach yields codewords whose lengths are inversely proportional to symbol probabilities, achieving the theoretical minimum average length bounded by the entropy. The resulting code is uniquely decodable and satisfies the Kraft inequality with equality for complete trees. For example, in encoding English text using letter frequencies, typically assigns shorter codes to common letters like 'e' (appearing about 12.7% of the time) and longer codes to rare letters such as 'z' or 'q', achieving an average of approximately 4.3 bits per letter compared to 5 bits in fixed-length coding, reducing redundancy by closely approximating the source H=pilog2piH = -\sum p_i \log_2 p_i. serves as a related variant that encodes an entire sequence into a single fractional number between 0 and 1, allowing even finer granularity than integer-bit prefix codes like Huffman. Huffman codes find widespread application in lossless data compression, such as in the algorithm used by ZIP files, where dynamic Huffman trees encode literals and distances to achieve efficient reduction in file sizes. They are also integral to fax transmission standards, like ITU-T T.4 Group 3, which employs fixed Huffman tables for of black-and-white images to minimize bandwidth over telephone lines. Unlike fixed-length codes, which waste bits on infrequent symbols, prefix codes like Huffman adapt to source statistics for substantial savings in storage and transmission.

Unicode Variable Encodings

Unicode variable encodings are standardized methods for representing the character set using variable-length binary sequences, enabling efficient storage and transmission of multilingual text while optimizing for common scripts like ASCII. These encodings prioritize , security, and compactness, with byte structures that allow decoders to determine sequence lengths from lead bytes. They form the backbone of global text handling in , particularly on the web and in internationalized software. UTF-8, devised by in September 1992 at , encodes code points using 1 to 4 bytes per character, with the number of bytes determined by the code point's value. It maintains full ASCII compatibility by using a single 8-bit byte (ranging from 0x00 to 0x7F) for the first 128 code points (U+0000 to U+007F), ensuring seamless integration with legacy systems. Subsequent bytes in multi-byte sequences are continuation bytes, always starting with the bits 10xxxxxx to distinguish them from lead bytes. For example, the (€, U+20AC) is encoded as the three-byte sequence 11100010 10000010 10101100 ( E2 82 AC). UTF-8 decoding relies on the lead byte to specify the sequence length: bytes starting with 0xxxxxxx are single-byte (1 byte total), 110xxxxx indicate two bytes, 1110xxxx three bytes, and 11110xxx four bytes, followed by the appropriate number of continuation bytes. To enhance security, overlong encodings—where a uses more bytes than necessary, such as representing U+0000 as a two-byte sequence—are strictly forbidden, preventing potential exploits like buffer overflows or attacks in string processing. By 2025, UTF-8 dominates web content, used by 98.8% of websites with known character encodings due to its efficiency and universal support. UTF-16, defined in 1996 and standardized in RFC 2781 (2000), is a variable-length encoding that represents code points using one or two 16-bit units (2 or 4 bytes). Code points from U+0000 to U+FFFF are encoded directly in a single 16-bit unit (BMP or Basic Multilingual Plane). For code points beyond U+FFFF (Supplementary Planes), UTF-16 uses surrogate pairs: a high surrogate (U+D800 to U+DBFF) followed by a low surrogate (U+DC00 to U+DFFF), allowing representation of the full Unicode range up to 1,114,112 code points. UTF-16 is widely used internally in many programming languages (e.g., strings) and operating systems (e.g., Windows), balancing efficiency for common characters with support for rare ones, though it lacks ASCII byte-level compatibility. GB 18030, introduced as a national standard in in 2000 (GB 18030-2000) and made mandatory for operating systems sold in starting September 1, 2001, is a variable-length encoding that extends the earlier GBK standard to provide full support for the character set, particularly emphasizing Chinese ideographs. The current version, GB/T 18030-2022 (published 2022, effective August 1, 2023), aligns with 11.0 and supports over 87,000 Han ideographs. It uses 1 to 4 bytes per character: single bytes for ASCII, double bytes for legacy GBK characters, and four-byte sequences (two 16-bit words) for additional Unicode mappings not covered by GBK, ensuring compatibility while expanding coverage. UTF-7, developed in the mid-1990s as a 7-bit-safe transformation format for , encodes text to use only ASCII characters, making it suitable for protocols like that traditionally restrict to 7-bit data. It employs a base64-like scheme for non-ASCII characters, embedding them within ASCII-safe sequences delimited by '+' and '-' characters, while direct ASCII (A-Z, a-z, 0-9, and select symbols) remains unencoded. Standardized in RFC 2152 (1997), UTF-7 was designed for human readability and transport safety but has largely been superseded by in modern applications due to its added complexity.

Specialized Binary Codes

Numeric and Positional Codes

(BCD) is a method of encoding each digit using four binary bits, representing values from 0000 (for 0) to 1001 (for 9), with unused codes from 1010 to 1111 typically ignored or reserved. Developed in the for early computing systems like the , which employed ring counters equivalent to BCD arithmetic on 4-bit words, it became a standard in computer design during the and early . Packed BCD optimizes storage by combining two digits into an 8-bit byte, such as 12 encoded as 0001 0010. This approach is particularly valued in financial applications and calculators, where it prevents rounding errors inherent in pure binary floating-point representations by maintaining exact precision. In digital circuits, decimal adder counters for BCD require special design to handle the limited valid states. A standard 4-bit binary synchronous counter cycles through all 16 states from 0000 (0) to 1111 (15). However, BCD operation uses only the 10 valid states from 0000 (0) to 1001 (9), treating 1010 to 1111 as invalid. To enforce a modulo-10 cycle and skip these invalid states, additional combinational logic is incorporated to detect when the counter reaches 1010 and reset it to 0000 or apply corrections, ensuring reliable decimal counting without entering undefined states. A variant of BCD, the code, adds a fixed of 0011 to each standard BCD digit, resulting in representations like 0011 for , 0100 for 1, and 1100 for 9. This self-complementing property simplifies arithmetic operations, as the 1's complement of an number yields the code for its 9's complement, facilitating subtraction without dedicated hardware. Developed as a non-weighted BCD extension for easier complementation in early digital systems, it was used in some older computers to streamline computations. The , also known as reflected , is a positional where successive values differ by exactly one bit, minimizing errors from transient states in mechanical or electrical transitions. Invented by at and patented in 1953 for use in shaft encoders, it addresses issues in rotary and linear position sensing by ensuring that only one bit flips between adjacent positions, such as 000 to 001 or 011 to 010. Applications include rotary encoders for angle measurement and floor indicators, where Gray code tapes with magnetic encoding and sensor heads prevent erroneous multi-bit readings during position changes. Conversion from Gray to binary involves a chain of XOR operations, starting from the most significant bit: each binary bit is the XOR of the corresponding Gray bit and the previous binary bit.

Error-Correcting Binary Codes

Error-correcting binary codes incorporate redundancy into the encoded data to detect and correct transmission or storage errors, enhancing reliability in digital systems. These codes operate by adding parity bits or symbols that allow the receiver to identify and, in some cases, repair bit flips caused by or interference. A fundamental concept in their design is the , defined as the minimum number of bit positions that differ between any two valid codewords in the code; a code with a minimum of dd can detect up to d1d-1 errors and correct up to (d1)/2\lfloor (d-1)/2 \rfloor errors. The , introduced by in 1950, is a seminal binary linear error-correcting code that encodes 4 data bits into 7 total bits using 3 parity bits positioned at powers of 2 (bits 1, 2, 4). It achieves single-error correction and double-error detection with a minimum of 3. The parity bits are computed via even parity checks over specific data bit combinations: for the (7,4) Hamming code, p1=d1d2d4p_1 = d_1 \oplus d_2 \oplus d_4, p2=d1d3d4p_2 = d_1 \oplus d_3 \oplus d_4, and p4=d2d3d4p_4 = d_2 \oplus d_3 \oplus d_4, where \oplus denotes the XOR operation. Upon reception, syndrome bits derived from parity checks pinpoint the error position for correction. Hamming codes are widely applied in memory storage, such as error-correcting code (ECC) RAM in servers and workstations, where they mitigate soft errors from cosmic rays or electrical noise. Reed-Solomon codes, developed by Irving Reed and Gustave Solomon in 1960, are non-binary defined over finite fields like GF(256), treating byte sequences as polynomials to add redundancy for error correction. A Reed-Solomon code of length nn with kk data symbols and 2t2t parity symbols can correct up to tt symbol errors (or erasures), leveraging BCH decoding algorithms for efficiency. These codes excel in burst-error correction and are integral to in compact discs (CDs), where they recover from scratches, and in two-dimensional barcodes like QR codes, enabling readability despite damage. In communications, Reed-Solomon codes protect satellite transmissions against channel fading and interference, as seen in systems like NASA's Deep Space Network. Cyclic redundancy checks (CRCs), emerging in the early , provide robust error detection through division in GF(2), appending a to the data block without correction capability but with high detection rates for burst errors. The CRC process treats the message as a polynomial multiplied by xrx^r (where rr is the degree) and divides by a generator g(x)g(x), using the remainder as the CRC. A prominent example is CRC-32, using the generator polynomial x32+x26+x23+x22+x16+x12+x11+x10+x8+x7+x5+x4+x2+x+1x^{32} + x^{26} + x^{23} + x^{22} + x^{16} + x^{12} + x^{11} + x^{10} + x^8 + x^7 + x^5 + x^4 + x^2 + x + 1, which detects all single- and double-bit errors and most multi-bit errors up to 32 bits. CRC-32 is standardized in Ethernet frames per for network integrity verification.

Other Notable Binary Codes

Morse code, developed by Samuel F. B. Morse and in 1837, represents an early example of a variable-length binary signaling system used for . It encodes characters using sequences of short signals (dots) and long signals (dashes), which function as binary elements—typically interpreted as 0 for dots and 1 for dashes in digital transmissions—along with specific timing intervals for clarity: a dot lasts one unit of time, a dash three units, intra-character spaces one unit, inter-character spaces three units, and inter-word spaces seven units. This international standard, refined through global adoption and formalized in the International Morse Code by 1865, enabled efficient long-distance communication and remains influential in emergency signaling, such as the distress call "" rendered as ... --- .... Bacon's cipher, devised by around 1605 and detailed in his 1623 work De Augmentis Scientiarum, is a steganographic method that embeds messages within ordinary using a binary-like encoding for the 24 letters of the Latin alphabet (combining I/J and U/V). Each letter is represented by a unique 5-bit sequence of two symbols, conventionally A (0) and B (1), which are disguised by varying typefaces, fonts, or letter forms in the carrier text—for instance, "A" might use one style and "B" another, allowing the hidden message to be extracted by reading the sequence. This approach predates modern binary systems and demonstrates early use of binary principles for covert communication, requiring no special tools beyond careful transcription. Base64 encoding, emerging in the late 1980s to facilitate transmission over text-based protocols, converts 8-bit bytes into 6-bit groups represented by 64 ASCII characters: A–Z (0–25), a–z (26–51), 0–9 (52–61), + (62), and / (63). First specified in the (PEM) protocol via RFC 989 in 1987 and later standardized for in RFC 2045 (1996), it expands data by approximately 33% to ensure safe inclusion in email attachments and , with padding using "=" to align incomplete 6-bit groups at the end. This scheme avoids binary-unfriendly characters like null bytes, making it essential for protocols, though variants like URL-safe substitute - and _ for + and / to prevent encoding conflicts. In the 2020s, quantum binary codes such as surface codes have gained prominence for encoding classical binary states (|0⟩ and |1⟩) into logical qubits within noisy quantum hardware, enabling fault-tolerant computation through topological correction on a 2D lattice of physical qubits. Post-2023 developments include advanced decoding algorithms using transformer-based neural networks to achieve high-fidelity suppression in large-scale surface code implementations, as demonstrated in experiments scaling to over 100 physical qubits per logical qubit with logical rates below 10^{-3}. These codes, which detect and correct bit-flip and phase errors via stabilizer measurements, represent a key step toward practical quantum computers, with recent integrations in platforms like Google's Sycamore processor showing exponential reduction as code distance increases. As of November 2025, announced new quantum processors and a roadmap to fault-tolerant by 2029, leveraging advanced correction techniques including surface codes to achieve quantum advantage.

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