cPanel is a web hosting control panel software developed by cPanel, L.L.C. It provides a graphical interface (GUI) and automation tools designed to simplify the process of hosting a web site for the website owner or "end user". It enables administration through a standard web browser using a three-tier structure. While cPanel is limited to managing a single hosting account, cPanel & WHM allow the administration of the entire server. In addition to the GUI, cPanel also has command line and API-based access that allows third-party software vendors, web hosting organizations, and developers to automate standard system administration processes. cPanel & WHM is designed to function either as a dedicated server or virtual private server. The latest cPanel & WHM version supports installation on AlmaLinux, Rocky Linux, CloudLinux OS, and Ubuntu. == History == cPanel is currently developed by cPanel, L.L.C., a privately owned company headquartered in Houston, Texas, United States. WebPros is the parent company of cPanel, L.L.C. It was originally designed in 1996 as the control panel for Speed Hosting, a now-defunct web hosting company. The original author of cPanel, J. Nick Koston, had a stake in Speed Hosting. Webking quickly began using cPanel after its merger with Speed Hosting. The new company moved its servers to Virtual Development Inc. (VDI), a now-defunct hosting facility. Following an agreement between Koston and VDI, cPanel was only available to customers hosted directly at VDI. At the time, there was little competition in the control panel market, with the main choices being VDI and Alabanza. Eventually, due to Koston leaving for college, he and William Jensen signed an agreement in which cPanel was split into a separate program called WebPanel; this version was run by VDI. Without the lead programmer, VDI was not able to continue any work on cPanel and eventually stopped supporting it completely. Koston kept working on cPanel while also working at BurstNET. Eventually, he left BurstNET to focus fully on cPanel. cPanel 3 was released in 1999: main additions over cPanel 2 were an automatic upgrade and the Web Host Manager (WHM). The interface was also improved when Carlos Rego of WizardsHosting made what became the default theme of cPanel. With the release of cPanel 11, cPanel adopted a four-tier versioning system, "Parent.Major.Minor.Patch" (e.g., 11.32.0.3). As of version 11.52, the "Parent" representation is deprecated, with 11.54 stylized as "Version 54." cPanel 11.30 is the last major version to support FreeBSD. On August 20, 2018 cPanel L.L.C. announced that it had signed an agreement to be acquired by a group led by Oakley Capital (who also own Plesk and SolusVM). While Koston sold his interest in cPanel, he will continue to be an owner of the company that owns cPanel. In April 2026, a severe vulnerability was discovered that affected all cPanel and WHM versions after 11.40, affectively allowing unauthenticated remote attackers to access the control panel. According to some web hosters the vulnerability was already being actively exploited, with some attempts even dating back to late February 2026. == Add-ons == cPanel provides front-ends for a number of common operations, including the management of PGP keys, crontab tasks, mail and FTP accounts, and mailing lists. Several add-ons exist, some for an additional fee, including auto installers such as Installatron, Fantastico, Softaculous, and WHMSonic (SHOUTcast/radio Control Panel Add-on). The add-ons need to be enabled by the server administrator in WHM to be accessible to the cPanel user. WHM manages some software packages separately from the underlying operating system, applying upgrades to Apache, PHP, MySQL and MariaDB, Exim, FTP, and related software packages automatically. This ensures that these packages are kept up-to-date and compatible with WHM, but makes it more difficult to install newer versions of these packages. It also makes it difficult to verify that the packages have not been tampered with, since the operating system's package management verification system cannot be used to do so. == WHM == WHM, short for WebHost Manager, is a web-based tool which is used for server administration. There are at least two tiers of WHM, often referred to as "root WHM", and non-root WHM (or Reseller WHM). Root WHM is used by server administrators and non-root WHM (with fewer privileges) is used by others, like entity departments, and resellers to manage hosting accounts often referred to as cPanel accounts on a web server. WHM is also used to manage SSL certificates (both server self generated and CA provided SSL certificates), cPanel users, hosting packages, DNS zones, themes, and authentication methods. The default automatic SSL (AutoSSL) provided by cPanel is powered by Let's Encrypt. Additionally, WHM can also be used to manage FTP, Mail (POP, IMAP, and SMTP) and SSH services on the server. As well as being accessible by the root administrator, WHM is also accessible to users with reseller privileges. Reseller users of cPanel have a smaller set of features than the root user, generally limited by the server administrator, to features which they determine will affect their customers' accounts rather than the server as a whole. From root WHM, the server administrator can perform maintenance operations such as upgrading and recompiling Apache and PHP, installing Perl modules, and upgrading RPMs installed on the system. == Enkompass == A version of cPanel & WHM for Microsoft Windows, called Enkompass, was declared end-of-life as of February 2014. Version 3 remained available for download, but without further development or support. In the preceding years, Enkompass had been available for free as product development slowed. == Pricing == On June 27, 2019 cPanel announced a new account-based pricing structure. After backlash from their customers, cPanel issued a second announcement but did not change the new structure.
Traceability
Traceability is the capability to trace something. In some cases, it is interpreted as the ability to verify the history, location, or application of an item by means of documented recorded identification. Other common definitions include the capability (and implementation) of keeping track of a given set or type of information to a given degree, or the ability to chronologically interrelate uniquely identifiable entities in a way that is verifiable. Traceability is applicable to measurement, supply chain, software development, healthcare and security. == Measurement == The term measurement traceability or metrological traceability is used to refer to an unbroken chain of comparisons relating an instrument's measurements to a known standard. Calibration to a traceable standard can be used to determine an instrument's bias, precision, and accuracy. It may also be used to show a chain of custody—from current interpretation of evidence to the actual evidence in a legal context, or history of handling of any information. In many countries, national standards for weights and measures are maintained by a National Metrological Institute (NMI) which provides the highest level of standards for the calibration / measurement traceability infrastructure in that country. Examples of government agencies include the National Physical Laboratory, UK (NPL) the National Institute of Standards and Technology (NIST) in the USA, the Physikalisch-Technische Bundesanstalt (PTB) in Germany, the Instituto Nazionale di Ricerca Metrologica (INRiM) in Italy, and the National Research Council of Canada (NRC). As defined by NIST, "Traceability of measurement requires the establishment of an unbroken chain of comparisons to stated references each with a stated uncertainty." A clock providing traceable time is traceable to a time standard such as Coordinated Universal Time or International Atomic Time. The Global Positioning System is a source of traceable time. === Food processing === In food processing (meat processing, fresh produce processing), the term traceability refers to the recording through means of barcodes or RFID tags and other tracking media, all movement of product and steps within the production process. One of the key reasons this is such a critical point is in instances where an issue of contamination arises, and a recall is required. Where traceability has been closely adhered to, it is possible to identify, by precise date/time and exact location which goods must be recalled, and which are safe, potentially saving millions of dollars in the recall process. Traceability within the food processing industry is also utilised to identify key high production and quality areas of a business, versus those of low return, and where points in the production process may be improved. In food processing software, traceability systems imply the use of a unique piece of data (e.g., order date/time or a serialized sequence number, generally through the use of a barcode / RFID) which can be traced through the entire production flow, linking all sections of the business, including suppliers and future sales through the supply chain. Messages and files at any point in the system can then be audited for correctness and completeness, using the traceability software to find the particular transaction and/or product within the supply chain. In food systems, ISO 22005, as part of the ISO 22000 family of standards, has been developed to define the principles for food traceability and specifies the basic requirements for the design and implementation of a feed and food traceability system. It can be applied by an organization operating at any step in the feed and food chain. The European Union's General Food Law came into force in 2002, making traceability compulsory for food and feed operators and requiring those businesses to implement traceability systems. The EU introduced its Trade Control and Expert System, or TRACES, in April 2004. The system provides a central database to track movement of animals within the EU and from third countries. Australia has its National Livestock Identification System to keep track of livestock from birth to slaughterhouse. India has started taking initiatives for setting up traceability systems at Government and Corporate levels. Grapenet, an initiative by Agriculture and Processed Food Products Export Development Authority (APEDA), Ministry of Commerce, Government of India is an example in this direction. GrapeNet is an internet based traceability software system for monitoring fresh grapes exported from India to the European Union. GrapeNet is a first of its kind initiative in India that has put in place an end-to-end system for monitoring pesticide residue, achieve product standardization and facilitate tracing back from pallets to the farm of the Indian grower, through the various stages of sampling, testing, certification and packing. Grapenet won the National Award (Gold), in the winners announced for the best e-Governance initiatives undertaken in India in 2007. The Directorate Generate Foreign Trade (DGFT), Government of India, through its notification dated 04.02.2009 relating to Amendment in Foreign Trade Policy (RE2008)has mandated that Export to the European Union is permitted subject to registration with APEDA, thereby making Grapenet mandatory for all exports of fresh grapes from India to Europe. Uruguay has also designed a system called "Traceability & Electronic Information System of the Beef Industry". Traceability in food supply can also refer to practices employed by individual companies, including Ritual and Amway's Nutrilite. In the case of Nutrilite's supplements, ingredients are documented and tested throughout farming, processing, and manufacturing to ensure traceability at each stage of production. == Systems and software development == In systems and software development, the term traceability (or requirements traceability) refers to the ability to link product requirements back to stakeholders' rationales and forward to corresponding design artifacts, code, and test cases. Traceability supports numerous software engineering activities such as change impact analysis, compliance verification or traceback of code, regression test selection, and requirements validation. It is usually accomplished in the form of a matrix created for the verification and validation of the project. Unfortunately, the practice of constructing and maintaining a requirements trace matrix (RTM) can be very arduous and over time the traces tend to erode into an inaccurate state unless date/time stamped. Alternate automated approaches for generating traces using information retrieval methods have been developed. The IEEE defines traceability as "(1)The degree to which a relationship can be established between two or more products of the development process, especially products having a predecessor, successor or master-subordinate relationship to one another. For example, the degree to which the requirements and design of a given software component match. See also: consistency. " and "(2) The degree to which each element in a software development product establishes its reason for existing; for example, the degree to which each element in a bubble chart references the requirement that it satisfies." In transaction processing software, traceability implies use of a unique piece of data (e.g., order date/time or a serialized sequence number) which can be traced through the entire software flow of all relevant application programs. Messages and files at any point in the system can then be audited for correctness and completeness, using the traceability key to find the particular transaction. This is also sometimes referred to as the transaction footprint. == Health care == Patient safety during healthcare service plays an important role in preventing delayed recovery or even mortality, by increasing and improving the quality of life of citizens, and is considered an indicator of the quality status of health services Maintaining patient safety is a complex task and involves factors inherent to the environment and human actions. New technologies facilitate the traceability tools of patients and medications. This is particularly relevant for drugs that are considered high risk and cost. Recent research in the healthcare industry emphasizes the significant impact of Blockchain Technology (BCT) on improving the performance of healthcare supply chain management. It highlights BCT's role in enhancing transparency, data immutability, and efficient management, leading to better cooperation among stakeholders and effective risk mitigation in healthcare services. The World Health Organization has recognized the importance of traceability for medical products of human origin (MPHO) and urged member states "to encourage the implementation of globally consistent coding systems to facilitate national and international traceability". == Security and cri
Controlled natural language
Controlled natural languages (CNLs) are subsets of natural languages that are obtained by restricting the grammar and vocabulary in order to reduce or eliminate ambiguity and complexity. Traditionally, controlled languages fall into two major types: those that improve readability for human readers (e.g. non-native speakers), and those that enable reliable automatic semantic analysis of the language. The first type of languages (often called "simplified" or "technical" languages), for example ASD Simplified Technical English, Caterpillar Technical English, IBM's Easy English, are used in the industry to increase the quality of technical documentation, and possibly simplify the semi-automatic translation of the documentation. These languages restrict the writer by general rules such as "Keep sentences short", "Avoid the use of pronouns", "Only use dictionary-approved words", and "Use only the active voice". The second type of languages have a formal syntax and formal semantics, and can be mapped to an existing formal language, such as first-order logic. Thus, those languages can be used as knowledge representation languages, and writing of those languages is supported by fully automatic consistency and redundancy checks, query answering, etc. == Languages == Existing controlled natural languages include: == Encoding == IETF has reserved simple as a BCP 47 variant subtag for simplified versions of languages.
AppValley
AppValley is an independent American digital distribution service operated and trademarked by AppValley LLC. It serves as an alternative app store for the iOS mobile operating system, which allows users to download applications that are not available on the App Store, most commonly tweaked "++" apps, jailbreak apps, and apps including paid apps on the app store. == Legality == AppValley is among several services that violate enterprise developer certificates from Apple. The terms under which these are granted make clear that they are for companies who wish to distribute apps to their employees. AppValley uses these certificates to distribute software directly to non-employees, thereby bypassing the AppStore. AppValley's conduct had implications in U.S. sanctioned markets like Iran, Iraq, North Korea, Cuba, and Venezuela, which have all been subject to commercial sanctions. Among the software offered by AppValley and other services is pirated software, including paid apps on the app store and premium versions of Instagram, Spotify, Pokémon Go, and others. For instance, AppValley distributes an ad-free version of the music streaming app Spotify even on the free tier. == History == The website was founded in May 2017, releasing late that month with a very basic version of the app. There were less than 100 apps available for download at this time. On Jan 19, 2018, a new version dubbed AppValley 2.0 was released bringing dark mode, more categories, a search, and a much faster interface. On February 14, 2019, a Chinese partner "Jason Wu" allegedly took control of the main Twitter account and domain, causing the original AppValley developers to migrate to the domain app-valley.vip and the Twitter account handle @App_Valley_vip. As of September 2024, the app-valley.vip domain now redirects to appvalley.signulous.com. Today, AppValley continues to offer an alternative to Apple's App Store where app developers can publish their applications. == Features == AppValley is a mobile app installer which can also support iOS version that can be installed and downloaded on the mobile or the devices of the people who wish to get access to many different applications available. AppValley also contains apps that have been modified or tweaked for user preferences, and allows the user to by pass national restrictions on the use of apps, without having to resort to jailbreaking. As of June 2, 2020, there are over 1300 apps available for download.
Association for Computational Linguistics
The Association for Computational Linguistics (ACL) is a scientific and professional organization for people working on natural language processing. Its namesake conference is one of the primary high impact conferences for natural language processing research, along with EMNLP. The conference is held each summer in locations where significant computational linguistics research is carried out. It was founded in 1962, originally named the Association for Machine Translation and Computational Linguistics (AMTCL). It became the ACL in 1968. The ACL has a European (EACL), a North American (NAACL), and an Asian (AACL) chapter. == History == The ACL was founded in 1962 as the Association for Machine Translation and Computational Linguistics (AMTCL). The initial membership was about 100. In 1965, the AMTCL took over the journal Mechanical Translation and Computational Linguistics. This journal was succeeded by many other journals: the American Journal of Computational Linguistics (1974–1978, 1980–1983), and then Computational Linguistics (1984–present). Since 1988, the journal has been published for the ACL by MIT Press. The annual meeting was first held in 1963 in conjunction with the Association for Computing Machinery National Conference. The annual meeting was, for a long time, relatively informal and did not publish anything longer than abstracts. By 1968, the society took on its current name, the Association for Computational Linguistics (ACL). The publication of the annual meeting's Proceedings of the ACL began in 1979 and gradually matured into its modern form. Many of the meetings were held in conjunction with the Linguistic Society of America, and a few with the American Society for Information Science and the Cognitive Science Society. The United States government sponsored much research from 1989 to 1994, characterized by an increase in author retention rates and an increase in research in some key topics, such as speech recognition, in ACL. By the 21st century, it was able to maintain authors at a high rate who coalesced in a more stable arrangement around individual research topics. In 1991, the group published a prototype for a text generator based on the universal grammar theory of Noam Chomsky. The system, nicknamed Parrot, relied on a finite set of syntactic transformations and a hand-curated lexicon. Despite some initial success, including experimentation with morpheme syntactics, funding halted after the research team encountered intractable difficulties with inflection and abstract locutions. == Annual Meeting of the ACL == Every year, the ACL holds the Annual Meeting of the ACL. The location lies in Europe in years zero modulo three, North America in years one modulo three, and Asia–Australia in years two modulo three. In 2020, the Annual Meeting received for the first time more submissions from China than the United States. == Activities == The ACL organizes several of the top conferences and workshops in the field of computational linguistics and natural language processing. These include: Annual Meeting of the Association for Computational Linguistics (ACL), the flagship conference of the organization Empirical Methods in Natural Language Processing (EMNLP) International Joint Conference on Natural Language Processing (IJCNLP), held jointly one of the other conferences on a rotating basis Conference on Computational Natural Language Learning (CoNLL) Lexical and Computational Semantics and Semantic Evaluation (SemEval) Joint Conference on Lexical and Computational Semantics (SEM) Workshop on Statistical Machine Translation (WMT) Besides conferences, the ACL also sponsors the journals Computational Linguistics and Transactions of the Association for Computational Linguistics (TACL). Papers and other presentations at ACL and ACL-affiliated venues are archived online in the open-access ACL Anthology. == Special Interest Groups == ACL has a large number of Special Interest Groups (SIGs), focusing on specific areas of natural language processing. Some current SIGs within ACL are: == Presidents == Each year, the ACL elects a distinguished computational linguist who becomes vice-president of the organization in the next calendar year and president one year later. Recent ACL presidents are:
Huroof
Huroof (Arabic: حروف, lit. 'letters') is an Android kids application produced by the Islamic State, specifically the Islamic States' Al-Himmah Library, which is targeted towards kids in order to teach kids the Arabic alphabet, and to also get kids to support the Islamic State and its practices. == Application == Huroof uses child-like appearances on the main menu, and throughout multiple of Huroof's in-game games for learning the alphabet, a lot of the games reference jihadist concepts, including imagery of weapons (such as missile, tank, cannon, sword,...), 'violent' images, as well as Islamic State imagery, including the flag of the Islamic State, Huroof uses nasheeds from Ajnad Media Foundation for audio production in the app. Reportedly, Huroof was released via Telegram channels of the Islamic State, as well as other file sharing websites. It is not the first moblie app released by Islamic State, but it is the first time they released a moblie application targeting children. === Nasheed game === In the Huroof app, there's a game where you listen to a radio, with the Al-Bayan logo on it, and learn the Arabic alphabet while the nasheed plays. === Writing game === In Huroof, there's a game where you can write out letters of the Arabic alphabet, as well as numbers while a small child tells you what they are. === Letter choosing game === In the app, there's a game they shows you images, and you choose which letter that image/item starts with.
Predictive text
Predictive text is an input technology used where one key or button represents many letters, such as on the physical numeric keypads of mobile phones and in accessibility technologies. Each key press results in a prediction rather than repeatedly sequencing through the same group of "letters" it represents, in the same, invariable order. Predictive text could allow for an entire word to be input by a single keypress. Predictive text makes efficient use of fewer device keys to input writing into a text message, an e-mail, an address book, a calendar, and the like. The most widely used, general, predictive text systems are T9, iTap, eZiText, and LetterWise/WordWise. There are many ways to build a device that predicts text, but all predictive text systems have initial linguistic settings that offer predictions that are re-prioritized to adapt to each user. This learning adapts, by way of the device memory, to a user's disambiguating feedback that results in corrective key presses, such as pressing a "next" key to get to the intention. Most predictive text systems have a user database to facilitate this process. Theoretically the number of keystrokes required per desired character in the finished writing is, on average, comparable to using a keyboard. This is approximately true provided that all words used are in its database, punctuation is ignored, and no input mistakes are made when typing or spelling. The theoretical keystrokes per character, KSPC, of a keyboard is KSPC=1.00, and of multi-tap is KSPC=2.03. Eatoni's LetterWise is a predictive multi-tap hybrid, which when operating on a standard telephone keypad achieves KSPC=1.15 for English. The choice of which predictive text system is the best to use involves matching the user's preferred interface style, the user's level of learned ability to operate predictive text software, and the user's efficiency goal. There are various levels of risk in predictive text systems, versus multi-tap systems, because the predicted text that is automatically written provides the speed and mechanical efficiency benefit, which, if the user is not careful to review, results in transmitting misinformation. Predictive text systems take time to learn to use well, and so generally, a device's system has user options to set up the choice of multi-tap or any one of several schools of predictive text methods. == Background == Short message service (SMS) permits a mobile phone user to send text messages (also called messages, SMSes, texts, and txts) as a short message. The most common system of SMS text input is referred to as "multi-tap". Using multi-tap, a key is pressed multiple times to access the list of letters on that key. For instance, pressing the "2" key once displays an "a", twice displays a "b" and three times displays a "c". To enter two successive letters that are on the same key, the user must either pause or hit a "next" button. A user can type by pressing an alphanumeric keypad without looking at the electronic equipment display. Thus, multi-tap is easy to understand and can be used without any visual feedback. However, multi-tap is not very efficient, requiring potentially many keystrokes to enter a single letter. In ideal predictive text entry, all words used are in the dictionary, punctuation is ignored, no spelling mistakes are made, and no typing mistakes are made. The ideal dictionary would include all slang, proper nouns, abbreviations, URLs, foreign-language words and other user-unique words. This ideal circumstance gives predictive text software a reduction in the number of key strokes a user is required to enter a word. The user presses the number corresponding to each letter. As long as the word exists in the predictive text dictionary or is correctly disambiguated by non-dictionary systems, it will appear. For instance, pressing "4663" will typically be interpreted as the word good, provided that a linguistic database in English is currently in use, though alternatives such as home, hood and hoof are also valid interpretations of the sequence of key strokes. The most widely used systems of predictive text are Tegic's T9, Motorola's iTap, and the Eatoni Ergonomics' LetterWise and WordWise. T9 and iTap use dictionaries, but Eatoni Ergonomics' products use a disambiguation process, a set of statistical rules to recreate words from keystroke sequences. All predictive text systems require a linguistic database for every supported input language. == Dictionary vs. non-dictionary systems == Traditional disambiguation works by referencing a dictionary of commonly used words, though Eatoni offers a dictionaryless disambiguation system. In dictionary-based systems, as the user presses the number buttons, an algorithm searches the dictionary for a list of possible words that match the keypress combination and offers up the most probable choice. The user can then confirm the selection and move on, or use a key to cycle through the possible combinations. A non-dictionary system constructs words and other sequences of letters from the statistics of word parts. To attempt predictions of the intended result of keystrokes not yet entered, disambiguation may be combined with a word completion facility. Either system (disambiguation or predictive) may include a user database, which can be further classified as a "learning" system when words or phrases are entered into the user database without direct user intervention. The user database is for storing words or phrases that are not well disambiguated by the pre-supplied database. Some disambiguation systems further attempt to correct spelling, format text or perform other automatic rewrites, with the risky effect of either enhancing or frustrating user efforts to enter text. == History == The predictive text and autocomplete technology was invented out of necessities by Chinese scientists and linguists in the 1950s to solve the input inefficiency of the Chinese typewriter, as the typing process involved finding and selecting thousands of logographic characters on a tray, drastically slowing down the word processing speed. The actuating keys of the Chinese typewriter created by Lin Yutang in the 1940s included suggestions for the characters following the one selected. In 1951, the Chinese typesetter Zhang Jiying arranged Chinese characters in associative clusters, a precursor of modern predictive text entry, and broke speed records by doing so. Predictive entry of text from a telephone keypad has been known at least since the 1970s (Smith and Goodwin, 1971). Predictive text was mainly used to look up names in directories over the phone until mobile phone text messaging came into widespread use. == Example == On a typical phone keypad, if users wished to type the in a "multi-tap" keypad entry system, they would need to: Press 8 (tuv) once to select t. Press 4 (ghi) twice to select h. Press 3 (def) twice to select e. Meanwhile, in a phone with predictive text, they need only: Press 8 once to select the (tuv) group for the first character. Press 4 once to select the (ghi) group for the second character. Press 3 once to select the (def) group for the third character. The system updates the display as each keypress is entered, to show the most probable entry. In this example, prediction reduced the number of button presses from five to three. The effect is even greater with longer words and those composed of letters later in each key's sequence. A dictionary-based predictive system is based on the hope that the desired word is in the dictionary. That hope may be misplaced if the word differs in any way from common usage—in particular, if the word is not spelled or typed correctly, is slang, or is a proper noun. In these cases, some other mechanism must be used to enter the word. Furthermore, the simple dictionary approach fails with agglutinative languages, where a single word does not necessarily represent a single semantic entity. == Companies and products == Predictive text is developed and marketed in a variety of competing products, such as Nuance Communications's T9. Other products include Motorola's iTap; Eatoni Ergonomic's LetterWise (character, rather than word-based prediction); WordWise (word-based prediction without a dictionary); EQ3 (a QWERTY-like layout compatible with regular telephone keypads); Prevalent Devices's Phraze-It; Xrgomics' TenGO (a six-key reduced QWERTY keyboard system); Adaptxt (considers language, context, grammar and semantics); Lightkey (a predictive typing software for Windows); Clevertexting (statistical nature of the language, dictionaryless, dynamic key allocation); and Oizea Type (temporal ambiguity); Intelab's Tauto; WordLogic's Intelligent Input Platform™ (patented, layer-based advanced text prediction, includes multi-language dictionary, spell-check, built-in Web search); Google's Gboard. == Textonyms == Words produced by the same combination of keypresses have been called "textonyms"; also "txtonyms"; or "T9o