Web testing

Web testing

Web testing is software testing that focuses on web applications. Complete testing of a web-based system before going live can help address issues before the system is revealed to the public. Issues may include the security of the web application, the basic functionality of the site, its accessibility to disabled and fully able users, its ability to adapt to the multitude of desktops, devices, and operating systems, as well as readiness for expected traffic and number of users and the ability to survive a massive spike in user traffic, both of which are related to load testing. == Web application performance tool == A web application performance tool (WAPT) is used to test web applications and web related interfaces. These tools are used for performance, load and stress testing of web applications, web sites, web API, web servers and other web interfaces. WAPT tends to simulate virtual users which will repeat either recorded URLs or specified URL and allows the users to specify number of times or iterations that the virtual users will have to repeat the recorded URLs. By doing so, the tool is useful to check for bottleneck and performance leakage in the website or web application being tested. A WAPT faces various challenges during testing and should be able to conduct tests for: Browser compatibility Operating System compatibility Windows application compatibility where required WAPT allows a user to specify how virtual users are involved in the testing environment.ie either increasing users or constant users or periodic users load. Increasing user load, step by step is called RAMP where virtual users are increased from 0 to hundreds. Constant user load maintains specified user load at all time. Periodic user load tends to increase and decrease the user load from time to time. == Web security testing == Web security testing tells us whether Web-based applications requirements are met when they are subjected to malicious input data. There is a web application security testing plug-in collection for Fire Fox == Web API testing == An application programming interface API exposes services to other software components, which can query the API. The API implementation is in charge of computing the service and returning the result to the component that send the query. A part of web testing focuses on testing these web API implementations. GraphQL is a specific query and API language. It is the focus of tailored testing techniques. Search-based test generation yields good results to generate test cases for GraphQL APIs.

Right to explanation

In the regulation of algorithms, particularly artificial intelligence and its subfield of machine learning, a right to [an] explanation is a right to be given an explanation for an output of the algorithm. Such rights primarily refer to individual rights to be given an explanation for decisions that significantly affect an individual, particularly legally or financially. For example, a person who applies for a loan and is denied may ask for an explanation, which could be "Credit bureau X reports that you declared bankruptcy last year; this is the main factor in considering you too likely to default, and thus we will not give you the loan you applied for." Some such legal rights already exist, while the scope of a general "right to explanation" is a matter of ongoing debate. There have been arguments made that a "social right to explanation" is a crucial foundation for an information society, particularly as the institutions of that society will need to use digital technologies, artificial intelligence, machine learning. In other words, that the related automated decision making systems that use explainability would be more trustworthy and transparent. Without this right, which could be constituted both legally and through professional standards, the public will be left without much recourse to challenge the decisions of automated systems. == Examples == === Credit scoring in the United States === Under the Equal Credit Opportunity Act (Regulation B of the Code of Federal Regulations), Title 12, Chapter X, Part 1002, §1002.9, creditors are required to notify applicants who are denied credit with specific reasons for the detail. As detailed in §1002.9(b)(2): (2) Statement of specific reasons. The statement of reasons for adverse action required by paragraph (a)(2)(i) of this section must be specific and indicate the principal reason(s) for the adverse action. Statements that the adverse action was based on the creditor's internal standards or policies or that the applicant, joint applicant, or similar party failed to achieve a qualifying score on the creditor's credit scoring system are insufficient. The official interpretation of this section details what types of statements are acceptable. Creditors comply with this regulation by providing a list of reasons (generally at most 4, per interpretation of regulations), consisting of a numeric reason code (as identifier) and an associated explanation, identifying the main factors affecting a credit score. An example might be: 32: Balances on bankcard or revolving accounts too high compared to credit limits === European Union === The European Union General Data Protection Regulation (GDPR, enacted 2016, taking effect 2018) extends the automated decision-making rights in the 1995 Data Protection Directive to provide a legally disputed form of a right to an explanation, stated as such in Recital 71: "[the data subject should have] the right ... to obtain an explanation of the decision reached". In full: The data subject should have the right not to be subject to a decision, which may include a measure, evaluating personal aspects relating to him or her which is based solely on automated processing and which produces legal effects concerning him or her or similarly significantly affects him or her, such as automatic refusal of an online credit application or e-recruiting practices without any human intervention. ... In any case, such processing should be subject to suitable safeguards, which should include specific information to the data subject and the right to obtain human intervention, to express his or her point of view, to obtain an explanation of the decision reached after such assessment and to challenge the decision. However, the extent to which the regulations themselves provide a "right to explanation" is heavily debated. There are two main strands of criticism. There are significant legal issues with the right as found in Article 22 — as recitals are not binding, and the right to an explanation is not mentioned in the binding articles of the text, having been removed during the legislative process. In addition, there are significant restrictions on the types of automated decisions that are covered — which must be both "solely" based on automated processing, and have legal or similarly significant effects — which significantly limits the range of automated systems and decisions to which the right would apply. In particular, the right is unlikely to apply in many of the cases of algorithmic controversy that have been picked up in the media. The UK has also recently amended its implementation of Article 22. A second potential source of such a right has been pointed to in Article 15, the "right of access by the data subject". This restates a similar provision from the 1995 Data Protection Directive, allowing the data subject access to "meaningful information about the logic involved" in the same significant, solely automated decision-making, found in Article 22. Yet this too suffers from alleged challenges that relate to the timing of when this right can be drawn upon, as well as practical challenges that mean it may not be binding in many cases of public concern. Other EU legislative instruments contain explanation rights. The European Union's Artificial Intelligence Act provides in Article 86 a "[r]ight to explanation of individual decision-making" of certain high risk systems which produce significant, adverse effects to an individual's health, safety or fundamental rights. The right provides for "clear and meaningful explanations of the role of the AI system in the decision-making procedure and the main elements of the decision taken", although only applies to the extent other law does not provide such a right. The Digital Services Act in Article 27, and the Platform to Business Regulation in Article 5, both contain rights to have the main parameters of certain recommender systems to be made clear, although these provisions have been criticised as not matching the way that such systems work. The Platform Work Directive, which provides for regulation of automation in gig economy work as an extension of data protection law, further contains explanation provisions in Article 11, using the specific language of "explanation" in a binding article rather than a recital as is the case in the GDPR. Scholars note that remains uncertainty as to whether these provisions imply sufficiently tailored explanation in practice which will need to be resolved by courts. === France === In France the 2016 Loi pour une République numérique (Digital Republic Act or loi numérique) amends the country's administrative code to introduce a new provision for the explanation of decisions made by public sector bodies about individuals. It notes that where there is "a decision taken on the basis of an algorithmic treatment", the rules that define that treatment and its "principal characteristics" must be communicated to the citizen upon request, where there is not an exclusion (e.g. for national security or defence). These should include the following: the degree and the mode of contribution of the algorithmic processing to the decision- making; the data processed and its source; the treatment parameters, and where appropriate, their weighting, applied to the situation of the person concerned; the operations carried out by the treatment. Scholars have noted that this right, while limited to administrative decisions, goes beyond the GDPR right to explicitly apply to decision support rather than decisions "solely" based on automated processing, as well as provides a framework for explaining specific decisions. Indeed, the GDPR automated decision-making rights in the European Union, one of the places a "right to an explanation" has been sought within, find their origins in French law in the late 1970s. == Criticism == Some argue that a "right to explanation" is at best unnecessary, at worst harmful, and threatens to stifle innovation. Specific criticisms include: favoring human decisions over machine decisions, being redundant with existing laws, and focusing on process over outcome. Authors of study "Slave to the Algorithm? Why a 'Right to an Explanation' Is Probably Not the Remedy You Are Looking For" Lilian Edwards and Michael Veale argue that a right to explanation is not the solution to harms caused to stakeholders by algorithmic decisions. They also state that the right of explanation in the GDPR is narrowly defined, and is not compatible with how modern machine learning technologies are being developed. With these limitations, defining transparency within the context of algorithmic accountability remains a problem. For example, providing the source code of algorithms may not be sufficient and may create other problems in terms of privacy disclosures and the gaming of technical systems. To mitigate this issue, Edwards and Veale argue that an auditing system could be more effective, to allow auditors to loo

PureWow

PureWow is an American digital media company that publishes women's lifestyle content. Acquired by Gary Vaynerchuk in 2017 as part of Gallery Media Group, PureWow tailors lifestyle topics for Millennials and Generation X, including fashion, beauty, home decor, recipes, entertainment, travel, technology, literature, wellness and money. == History == PureWow was founded by Ryan Harwood in September 2010, along with Bob Pittman's Pilot Group and the women of wowOwow Joni Evans, Mary Wells Lawrence, Whoopi Goldberg, Liz Smith, Candice Bergen, and Lesley Stahl, among others. In January 2013, PureWow hired former Real Simple editor Mary Kate McGrath as its first editor-in-chief. In August 2014, PureWow was listed as no. 352 on Inc. Magazine's 2014 list of the top 500 fastest-growing privately owned companies. In May 2015, PureWow raised $2.5 million. In 2017, serial entrepreneur Gary Vaynerchuk and Miami Dolphins' owner Stephen Ross' venture firm, RSE Ventures, acquired PureWow to form Gallery Media Group as a creative agency and media firm. PureWow's CEO, Ryan Harwood serves as the chief executive of Gallery Media Group. == Editions == PureWow publishes national content as well as local content for New York City, Los Angeles, Chicago, San Francisco, Dallas, and the Hamptons. The company publishes content across fashion, beauty, homecare topics, technology, entertainment, books, wellness and finances. PureWow articles are distributed via its website PureWow.com, email, and over social media channels.

Infone

Infone was a service launched by Metro One Telecommunications in 2003. The service was discontinued effective December 14, 2005. == How it worked == Infone included directory assistance and other services via a toll-free phone number. A user could call 888-411-1111 to request directory assistance, directions, traffic information, movie times, call completion, dinner reservation assistance and other services. Infone provided a number of innovative 411 'concierge'-like services, including movie listings from a live operator, and offered a feature where they could provide information from a linked Microsoft Outlook calendar when set up in advance. For a period of time they advertised heavily on U.S. television, featuring ads with then Governor of Minnesota Jesse Ventura, emphasizing their use of all U.S. based operators. The price offered was $0.89 per call up to 15 minutes (for use when the operator connects you to the requested number, as well as for additional information requests afterwards), with $0.05 for each additional minute, making Infone also a competitively priced long-distance service. New users received 5–10 free calls. Infone identified a registered user (along with billing information; the service was only payable by credit card) by caller ID (numbers were registered on signing up) and by an advanced voiceprint recognition system (VPRS) from SpeechWorks that identified the user when the user called from an unregistered telephone number (or no caller ID) through the use of a personal phrase spoken by the user (e.g., "Hello Infone!") after the welcome tone.

List of UPnP AV media servers and clients

This is a list of UPnP AV media servers and client application or hard appliances. == UPnP AV media servers == === Software === === Cross-platform === Allonis myServer, a multi-faceted media player/organizer with a DLNA/UPnP server, controller, and renderer, including conversion. Runs on Microsoft Windows. Supports most all HTML5 devices as remote controls. Asset UPnP (DLNA compatible) from Illustrate. An audio specific UPnP/DLNA server for Windows, QNAP, macOS and Linux. Features audio WAVE/LPCM transcoding from a range of audio codecs, ReplayGain and playlists. FreeMi UPnP Media Server, very simple server, historically used to stream to the STB Freebox, based on .net/mono. Home Media Server, a free media server/player/controller for Windows, Linux, macOS, individual device settings, transcoding, external and internal subtitles, restricted device access to folders, uploading files, Internet-Radio, Internet-Television, Digital Video Broadcasting (DVB), DMR-control and "Play To", Music (Visualization), Photo (Slideshow), support for 3D-subtitles, support for BitTorrent files, Web-navigation with HTML5 player, Digital Media Renderer (DMR) emulation for AirPlay and Google Cast devices. Jellyfin, a free and open-source suite of multimedia applications designed to organize, manage, and share digital media files to networked devices. JRiver Media Center, a multi-faceted media player/organizer with a DLNA/UPnP server, controller, and renderer, including conversion. Supports Microsoft Windows, macOS and Linux. Kodi (previously XBMC), a cross platform open source software media-player/media center for Android, Apple TV, Linux, macOS and Windows. LimboMedia, a free cross platform home- and UPnP/DLNA mediaserver with android app and WebM transcoding for browser playback (build with java and FFmpeg). MinimServer, a Java-based highly configurable uPnP/DNLA music server with additional consideration given to Classical Music, supports transcoding with MinimStreamer, supports Microsoft Windows, macOS, Linux, and various NAS devices. Neutron Music Player, acts as a cross platform UPnP/DLNA Media Renderer server available for Android, iOS, BlackBerry 10 & PlayBook platforms. Supports gapless playback and has possibility to output rendered audio further to the high-resolution internal DAC or external USB DAC or another UPnP/DLNA Media Renderer with all supported DSP effects applied. Plex, a cross-platform and closed source software media player and entertainment hub for digital media, available for macOS, Microsoft Windows, Linux, as well as mobile clients for iOS (including Apple TV (2nd generation) onwards), Android, Windows Phone, and many devices such as Xbox. Supports on-the-fly transcoding of video and music. PonoMusic World. Based on the JRiver Media Center software, includes similar features along with a store for purchasing HD audio tracks. PS3 Media Server, a free cross platform Java based UPnP DLNA server especially good for AVC and other current HD media codecs with on-the-fly transcoding. Serviio, is available with a free and a pro license. It can stream media files (music, video or images) to renderer devices (e.g. a TV set, Blu-ray player, games console or mobile phone) on a local area network. TVMOBiLi, a cross platform, high performance UPnP/DLNA Media Server for Windows, macOS and Linux. TwonkyMedia server, a cross-platform multimedia server and entertainment hub for digital media, available for Android, Apple TV, iOS, Linux, macOS, Microsoft Windows, Windows Phone, and Xbox 360. Universal Media Server, a free (open source) DLNA-compliant UPnP Media Server for Windows, macOS and Linux (originally based on the PS3 Media Server). It is able to stream videos, audio and images to any DLNA-capable device. It contains more features than most paid UPnP/DLNA Media Servers. It streams to many devices including TVs (Samsung, Sony, Panasonic, LG, Philips and more.), PS3, Xbox(One/360), smartphones, Blu-ray players and more. vGet Cast, a simple, cross platform (Chrome App) DLNA server and controller for single, local video files. Vuze, an open-source Java-based BitTorrent client which contains MediaServer plugin. Wild Media Server, a media server/player/controller for Windows, Linux, macOS, individual device settings, transcoding, external and internal subtitles, restricted device access to folders, uploading files, Internet-Radio, Internet-Television, Digital Video Broadcasting (DVB), DMR-control and "Play To", Music (Visualization), Photo (Slideshow), support for 3D-subtitles, support for BitTorrent files, Web-navigation with HTML5 player, Digital Media Renderer (DMR) emulation for AirPlay and Google Cast devices. === Android === BubbleUPnP Android UPnP/DLNA server, player, controller and renderer CastLab Android UPnP/DLNA server. Pixel Media Server, Android UPnP/DLNA Media Server. Supports all popular Video and Audio files. It also support external subtitle file (SRT) Plato is an Android UPnP client app that can play videos and audio. Toaster Cast Android UPnP/DLNA server, controller and renderer vGet, Android App that can play videos embedded in websites on DLNA renderers. Media Cast UPnP, Android UPnP client app that can play videos/Audio. Media Server Pro is a DLNA server that allows individual file selections for sharing. Slick UPnP A minimal and intuitive open-source Android UPnP client app that can play video/audio. (It is not DMS) YAACC Open source UPnP controller, renderer and server app === Linux === === Microsoft Windows === Sundtek Streamingserver a native Windows TV Server providing DVB, ATSC and ISDB-T via UPnP/DLNA, it also supports streaming media files (it only supports TV devices from Sundtek). Stream What You Hear, a Windows application that streams the sound of your computer (i.e.: “what you hear”) to UPnP/DLNA device such as TVs, amps, network receivers, game consoles, etc... TVersity Media Server, a Windows application that streams multimedia content from a personal computer to UPnP, DLNA and mobile devices (Chromecast is also supported). It was the first media server to offer real-time transcoding (back in 2005). TVersity Screen Server, a Windows application that mirrors the screen of a personal computer to UPnP, DLNA and mobile devices. DVBViewer, a Windows application, mainly for TV/Radio recording/playback, but with the ability to stream live TV/radio as well as multimedia files via UPnP/DLNA. DivX, a Windows application, mainly for video encoding into DivX format, but has the ability to stream multimedia files via DLNA. foobar2000, a freeware audio player for Windows. Highly customizable, audio only. Download of dlna-extension from the developers' webpage necessary. Home Media Center, a free and open source media server compatible with DLNA. Includes web interface for streaming content to web browser (Android, iOS, ...), subtitles integration and Windows desktop streaming. This server is easy to use. KooRaRoo Media, a commercial DLNA media server and organizer for Windows. Includes on-the-fly transcoding, per-file and per-folder parental controls, powerful organizing features with dynamic playlists, Internet radio streaming, "Play To" functionality and remote device control, burned-in and external subtitles, extensive format support including RAW photo formats. Streams all files to all devices. Media Go, media player and tagger MediaMonkey, a free media player/tagger/editor with an UPnP/DLNA client and server for Microsoft Windows MusicBee, an audio player, supports UPnP via a plugin. Mezzmo, a commercial software package. Mezzmo streams music, movies, photos and subtitles to the UPnP and DLNA-enabled devices. It automatically finds and organizes music, movies and photos, imports multimedia files from iPad, iPhone, iPod, Audio CDs, iTunes, Windows Media Player and WinAmp. DLNA server supports all popular media file formats with real time transcoding to meet the device specifications. PlayOn, a commercial UPnP/DLNA media server for Windows, includes a transcoder for streaming web video. TVble, a cloud connected (Rotten tomatoes/TMDB etc.), Torrent streaming, DLNA enabled media server. Allows single file or playlist downloads. Windows Media Connect from Microsoft, a free UPnP AV MediaServer and control point (server and client) for Microsoft Windows WMC version 2.0 can be installed for usage with Windows Media Player 10 for Windows XP WMC version 3.0 can be installed for usage with Windows Media Player 11 for Windows XP WMC version 4.0 comes pre-installed on Windows Vista with its Windows Media Player 11 WMC can also refer to Windows Media Center. From the Windows Media Center entry in Wikipedia: In May 2015, Microsoft announced that Windows Media Center would be discontinued on Windows 10, and that it would be uninstalled when upgrading; but stated that those upgrading from a version of Windows that included the Media Center application would receive the paid Windows DVD Player app to maintain DVD playback functio

Production (computer science)

In computer science, a production or production rule is a rewrite rule that replaces some symbols with other symbols. A finite set of productions P {\displaystyle P} is the main component in the specification of a formal grammar (specifically a generative grammar). In such grammars, a set of productions is a special case of relation on the set of strings V ∗ {\displaystyle V^{}} (where ∗ {\displaystyle {}^{}} is the Kleene star operator) over a finite set of symbols V {\displaystyle V} called a vocabulary that defines which non-empty strings can be substituted with others. The set of productions is thus a special kind subset P ⊂ V ∗ × V ∗ {\displaystyle P\subset V^{}\times V^{}} and productions are then written in the form u → v {\displaystyle u\to v} to mean that ( u , v ) ∈ P {\displaystyle (u,v)\in P} (not to be confused with → {\displaystyle \to } being used as function notation, since there may be multiple rules for the same u {\displaystyle u} ). Given two subsets A , B ⊂ V ∗ {\displaystyle A,B\subset V^{}} , productions can be restricted to satisfy P ⊂ A × B {\displaystyle P\subset A\times B} , in which case productions are said "to be of the form A → B {\displaystyle A\to B} . Different choices and constructions of A , B {\displaystyle A,B} lead to different types of grammars. In general, any production of the form u → ϵ , {\displaystyle u\to \epsilon ,} where ϵ {\displaystyle \epsilon } is the empty string (sometimes also denoted λ {\displaystyle \lambda } ), is called an erasing rule, while productions that would produce strings out of nowhere, namely of the form ϵ → v , {\displaystyle \epsilon \to v,} are never allowed. In order to allow the production rules to create meaningful sentences, the vocabulary is partitioned into (disjoint) sets Σ {\displaystyle \Sigma } and N {\displaystyle N} providing two different roles: Σ {\displaystyle \Sigma } denotes the terminal symbols known as an alphabet containing the symbols allowed in a sentence; N {\displaystyle N} denotes nonterminal symbols, containing a distinguished start symbol S ∈ N {\displaystyle S\in N} , that are needed together with the production rules to define how to build the sentences. In the most general case of an unrestricted grammar, a production u → v {\displaystyle u\to v} , is allowed to map arbitrary strings u {\displaystyle u} and v {\displaystyle v} in V {\displaystyle V} (terminals and nonterminals), as long as u {\displaystyle u} is not empty. So unrestricted grammars have productions of the form V ∗ ∖ { ϵ } → V ∗ {\displaystyle V^{}\setminus \{\epsilon \}\to V^{}} or if we want to disallow changing finished sentences V ∗ N V ∗ = ( V ∗ ∖ Σ ∗ ) → V ∗ {\displaystyle V^{}NV^{}=(V^{}\setminus \Sigma ^{})\to V^{}} , where V ∗ N V ∗ {\displaystyle V^{}NV^{}} indicates concatenation and forces a non-terminal symbol to always be present on the left-hand side of the productions, and ∖ {\displaystyle \setminus } denotes set minus or set difference. If we do not allow the start symbol to occur in v {\displaystyle v} (the word on the right side), we have to replace V ∗ {\displaystyle V^{}} with ( V ∖ { S } ) ∗ {\displaystyle (V\setminus \{S\})^{}} on the right-hand side. The other types of formal grammar in the Chomsky hierarchy impose additional restrictions on what constitutes a production. Notably in a context-free grammar, the left-hand side of a production must be a single nonterminal symbol. So productions are of the form: N → V ∗ {\displaystyle N\to V^{}} == Grammar generation == To generate a string in the language, one begins with a string consisting of only a single start symbol, and then successively applies the rules (any number of times, in any order) to rewrite this string. This stops when a string containing only terminals is obtained. The language consists of all the strings that can be generated in this manner. Any particular sequence of legal choices taken during this rewriting process yields one particular string in the language. If there are multiple different ways of generating this single string, then the grammar is said to be ambiguous. For example, assume the alphabet consists of a {\displaystyle a} and b {\displaystyle b} , with the start symbol S {\displaystyle S} , and we have the following rules: 1. S → a S b {\displaystyle S\rightarrow aSb} 2. S → b a {\displaystyle S\rightarrow ba} then we start with S {\displaystyle S} , and can choose a rule to apply to it. If we choose rule 1, we replace S {\displaystyle S} with a S b {\displaystyle aSb} and obtain the string a S b {\displaystyle aSb} . If we choose rule 1 again, we replace S {\displaystyle S} with a S b {\displaystyle aSb} and obtain the string a a S b b {\displaystyle aaSbb} . This process is repeated until we only have symbols from the alphabet (i.e., a {\displaystyle a} and b {\displaystyle b} ). If we now choose rule 2, we replace S {\displaystyle S} with b a {\displaystyle ba} and obtain the string a a b a b b {\displaystyle aababb} , and are done. We can write this series of choices more briefly, using symbols: S ⇒ a S b ⇒ a a S b b ⇒ a a b a b b {\displaystyle S\Rightarrow aSb\Rightarrow aaSbb\Rightarrow aababb} . The language of the grammar is the set of all the strings that can be generated using this process: { b a , a b a b , a a b a b b , a a a b a b b b , … } {\displaystyle \{ba,abab,aababb,aaababbb,\dotsc \}} .

Mashup (web application hybrid)

A mashup (computer industry jargon), in web development, is a web page or web application that uses content from more than one source to create a single new service displayed in a single graphical interface. For example, a user could combine the addresses and photographs of their library branches with a Google map to create a map mashup. The term implies easy, fast integration, frequently using open application programming interfaces (open API) and data sources to produce enriched results that were not necessarily the original reason for producing the raw source data. The term mashup originally comes from creating something by combining elements from two or more sources. The main characteristics of a mashup are combination, visualization, and aggregation. It is important to make existing data more useful, for personal and professional use. To be able to permanently access the data of other services, mashups are generally client applications or hosted online. In the past years, more and more Web applications have published APIs that enable software developers to easily integrate data and functions the SOA way, instead of building them by themselves. Mashups can be considered to have an active role in the evolution of social software and Web 2.0. Mashup composition tools are usually simple enough to be used by end-users. They generally do not require programming skills and rather support visual wiring of GUI widgets, services and components together. Therefore, these tools contribute to a new vision of the Web, where users are able to contribute. The term "mashup" is not formally defined by any standard-setting body. == History == The broader context of the history of the Web provides a background for the development of mashups. Under the Web 1.0 model, organizations stored consumer data on portals and updated them regularly. They controlled all the consumer data, and the consumer had to use their products and services to get the information. The advent of Web 2.0 introduced Web standards that were commonly and widely adopted across traditional competitors and which unlocked the consumer data. At the same time, mashups emerged, allowing mixing and matching competitors' APIs to develop new services. The first mashups used mapping services or photo services to combine these services with data of any kind and therefore to produce visualizations of data. In the beginning, most mashups were consumer-based, but recently the mashup is to be seen as an interesting concept useful also to enterprises. Business mashups can combine existing internal data with external services to generate new views on the data. There was also the free Yahoo! Pipes to build mashups for free using the Yahoo! Query Language. == Types of mashup == There are many types of mashup, such as business mashups, consumer mashups, and data mashups. The most common type of mashup is the consumer mashup, aimed at the general public. Business (or enterprise) mashups define applications that combine their own resources, application and data, with other external Web services. They focus data into a single presentation and allow for collaborative action among businesses and developers. This works well for an agile development project, which requires collaboration between the developers and customer (or customer proxy, typically a product manager) for defining and implementing the business requirements. Enterprise mashups are secure, visually rich Web applications that expose actionable information from diverse internal and external information sources. Consumer mashups combine data from multiple public sources in the browser and organize it through a simple browser user interface. (e.g.: Wikipediavision combines Google Map and a Wikipedia API) Data mashups, opposite to the consumer mashups, combine similar types of media and information from multiple sources into a single representation. The combination of all these resources create a new and distinct Web service that was not originally provided by either source. === By API type === Mashups can also be categorized by the basic API type they use but any of these can be combined with each other or embedded into other applications. ==== Data types ==== Indexed data (documents, weblogs, images, videos, shopping articles, jobs ...) used by metasearch engines Cartographic and geographic data: geolocation software, geovisualization Feeds, podcasts: news aggregators ==== Functions ==== Data converters: language translators, speech processing, URL shorteners... Communication: email, instant messaging, notification... Visual data rendering: information visualization, diagrams Security related: electronic payment systems, ID identification... Editors == Mashup enabler == In technology, a mashup enabler is a tool for transforming incompatible IT resources into a form that allows them to be easily combined, in order to create a mashup. Mashup enablers allow powerful techniques and tools (such as mashup platforms) for combining data and services to be applied to new kinds of resources. An example of a mashup enabler is a tool for creating an RSS feed from a spreadsheet (which cannot easily be used to create a mashup). Many mashup editors include mashup enablers, for example, Presto Mashup Connectors, Convertigo Web Integrator or Caspio Bridge. Mashup enablers have also been described as "the service and tool providers, [sic] that make mashups possible". === History === Early mashups were developed manually by enthusiastic programmers. However, as mashups became more popular, companies began creating platforms for building mashups, which allow designers to visually construct mashups by connecting together mashup components. Mashup editors have greatly simplified the creation of mashups, significantly increasing the productivity of mashup developers and even opening mashup development to end-users and non-IT experts. Standard components and connectors enable designers to combine mashup resources in all sorts of complex ways with ease. Mashup platforms, however, have done little to broaden the scope of resources accessible by mashups and have not freed mashups from their reliance on well-structured data and open libraries (RSS feeds and public APIs). Mashup enablers evolved to address this problem, providing the ability to convert other kinds of data and services into mashable resources. === Web resources === Of course, not all valuable data is located within organizations. In fact, the most valuable information for business intelligence and decision support is often external to the organization. With the emergence of rich web applications and online Web portals, a wide range of business-critical processes (such as ordering) are becoming available online. Unfortunately, very few of these data sources syndicate content in RSS format and very few of these services provide publicly accessible APIs. Mashup editors therefore solve this problem by providing enablers or connectors. == Mashups versus portals == Mashups and portals are both content aggregation technologies. Portals are an older technology designed as an extension to traditional dynamic Web applications, in which the process of converting data content into marked-up Web pages is split into two phases: generation of markup "fragments" and aggregation of the fragments into pages. Each markup fragment is generated by a "portlet", and the portal combines them into a single Web page. Portlets may be hosted locally on the portal server or remotely on a separate server. Portal technology defines a complete event model covering reads and updates. A request for an aggregate page on a portal is translated into individual read operations on all the portlets that form the page ("render" operations on local, JSR 168 portlets or "getMarkup" operations on remote, WSRP portlets). If a submit button is pressed on any portlet on a portal page, it is translated into an update operation on that portlet alone (processAction on a local portlet or performBlockingInteraction on a remote, WSRP portlet). The update is then immediately followed by a read on all portlets on the page. Portal technology is about server-side, presentation-tier aggregation. It cannot be used to drive more robust forms of application integration such as two-phase commit. Mashups differ from portals in the following respects: The portal model has been around longer and has had greater investment and product research. Portal technology is therefore more standardized and mature. Over time, increasing maturity and standardization of mashup technology will likely make it more popular than portal technology because it is more closely associated with Web 2.0 and lately Service-oriented Architectures (SOA). New versions of portal products are expected to eventually add mashup support while still supporting legacy portlet applications. Mashup technologies, in contrast, are not expected to provide support for portal standards. == Business mashups