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  • Once (dating platform)

    Once (dating platform)

    Once is an online dating platform founded in 2015. The platform offers users one selected match per day for more meaningful connections. == History == Once was established in 2015, the founders included dating industry entrepreneur Jean Meyer, who became a CEO of the company, as well as Guillaume Sempe and Guilhem Duche. It focused on providing a single daily match to its users. On its early stages Once secured a $3.5 million seed round from Partech Ventures and some private investors. The same year, it opened offices in Paris, and London. By 2016, it reached 1 million users. In 2020, the company was acquired by Dating Group for $18 million. Following the acquisition, Once underwent rebranding. Alexandra Beaumont took over leadership of the brand in 2021, driving growth, rebranding, and innovation. == Overview == Once provides an online dating service with a focus on thoughtful connections. Users receive one selected match per day, which encourages meaningful interactions. The platform operates primarily in the United States, the United Kingdom, Canada, France, and Spain. The platform is supported by Android, iOS, and Apple Watch OS.

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  • Web Intents

    Web Intents

    Web Intents was an experimental framework for web-based inter-application communication and service discovery. Web Intents consists of a discovery mechanism and a very light-weight RPC system between web applications, modelled after the Intents system in Android. In the context of the framework an Intent equals an action to be performed by a provider. Web Intents allow two web applications to communicate with each other, without either of them having to actually know what the other one is. == Support == === Client === Google Chrome versions 18 to 23 natively supported Web Intents. This support was disabled in version 24, citing the existence of a "number of areas for development in both the API and specific user experience in Chrome". There is a JavaScript shim with support for IE 8, IE 9, Opera, Safari, Firefox 3+ and Chrome 3+. === Server === There are some Web Intents proxy pages that make available some real services that don't yet support intents. AddThis supports Web Intents by their sharing tools regardless of browser support. == History == Paul Kinlan of Google announced the Web Intents project in December 2010. He soon released a prototype API to GitHub. In August 2011 Google announced that Chrome would support Web Intents. Google and Mozilla have started co-operating to unify Web Intents and Mozilla's Web Activities (which tries to solve the same problem) into one proposal. In November 2012, Greg Billock of Google announced that experimental support of Web Intents had been removed from Chrome.

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  • List of publications in data science

    List of publications in data science

    This is a list of publications in data science, generally organized by order of use in a data analysis workflow. See the list of publications in statistics for more research-based and fundamental publications; while this list is more applied, business oriented, and cross-disciplinary. General article inclusion criteria are: Papers from notable practitioners or notable professors, either with a Wikipedia page or reference to their notability Common knowledge all data professionals should know, with references validating this claim Highly cited applied statistics and machine learning publications Discussion-facilitating papers on the field of data science as a whole (for example, the Attention Is All You Need paper is arguably a landmark paper that can be added here, but it is specific to generative artificial intelligence, not for all practitioners of data) Some reasons why a particular publication might be regarded as important: Topic creator – A publication that created a new topic Breakthrough – A publication that changed scientific knowledge significantly Influence – A publication which has significantly influenced the world or has had a massive impact on the teaching of data science. When possible, a reference is used to validate the inclusion of the publication in this list. == History == Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) Author: Leo Breiman Publication data: Online version: https://projecteuclid.org/journals/statistical-science/volume-16/issue-3/Statistical-Modeling--The-Two-Cultures-with-comments-and-a/10.1214/ss/1009213726.pdf Description: Describes two cultures of statistics, one using a parsimonious and generative stochastic model, while the other is an algorithmic model with no known mechanism for how the data is generated. Breiman argues that while statistics has traditionally favored using the stochastic model, there is value in expanding the methods that statisticians can use to study phenomenon. Importance: Influence on the philosophies of statisticians right before the increased use of machine learning and deep learning methods. In a 20-year retrospective on this article, "Breiman's words are perhaps more relevant than ever". Notable statisticians at the time wrote opinion pieces about the publication. Although overall critical of the publication, David Cox writes that the publication "contains enough truth and exposes enough weaknesses to be thought-provoking." Bradley Efron commented that this publication is a "stimulating paper". Emanuel Parzen also comments about this publication that "Breiman alerts us to systematic blunders (leading to wrong conclusions) that have been committed applying current statistical practice of data modeling". Data Scientist: The Sexiest Job of the 21st Century Author: Thomas H. Davenport and DJ Patil Publication data: Online version: hbr.org/2022/07/is-data-scientist-still-the-sexiest-job-of-the-21st-century Description: Describes the new role at companies that is coined "Data scientist", what they do, how an organization might recruit one to their organization, and how to work with one effectively. Importance: This publication has been an influence on the data community as mentioned near the time it was published in 2012 by institutions like IEEE Spectrum, but also mentioned nearly a decade later asking the same question the title poses. In a retrospective response to their own publication 10 years earlier, authors Davenport and Patil have reflected that the role of a data scientist has "become better institutionalized, the scope of the job has been redefined, the technology it relies on has made huge strides, and the importance of non-technical expertise, such as ethics and change management, has grown". 50 Years of Data Science Author: David Donoho Publication data: Online version: https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734 Description: Retrospective discussion paper on the history and origins of data science, with a number of commentary from notable statisticians. Importance: This has been described as "the first in the field to present such a comprehensive and in-depth survey and overview", and helps to define the field that has many definitions. The Composable Data Management System Manifesto Author: Pedro Pedreira, Orri Erling, Konstantinos Karanasos, Scott Schneider, Wes McKinney, Satya R Valluri, Mohamed Zait, Jacques Nadeau Publication data: Online version: https://www.vldb.org/pvldb/vol16/p2679-pedreira.pdf Description: The vision paper advocating for a paradigm shift in how data management systems are designed using standard, composable, interoperable tools rather than siloed software tools. Importance: A paradigm shifting view on how future data science software tools should be designed for more efficient workflows, the principles of which "will be especially crucial for addressing fragmentation, improving interoperability, and promoting user-centricity as data ecosystems grow increasingly complex". == Data collection and organization == Tidy Data Author: Hadley Wickham Publication data: Online version: https://www.jstatsoft.org/article/view/v059i10/ https://vita.had.co.nz/papers/tidy-data.pdf Description: Describes a framework for data cleaning that is summarized in the quote, "each variable is a column, each observation is a row, and each type of observational unit is a table". This allows a standard data structure for which data analysis tools can be consistently built around. Importance: Cited over 1,500 times, this effort for tidy data has been described by David Donoho as having "more impact on today's practice of data analysis than many highly regarded theoretical statistics articles". In the context of data visualization, this publication is said to support "efficient exploration and prototyping because variables can be assigned different roles in the plot without modifying anything about the original dataset". Data Organization in Spreadsheets Author: Karl W. Broman and Kara H. Woo Publication data: Online version: https://www.tandfonline.com/doi/full/10.1080/00031305.2017.1375989 Description: This article offers practical recommendations for organizing data in spreadsheets, like Microsoft Excel and Google Sheets, to reduce errors and lower the barrier for later analyses due to limitations in spreadsheets or quirks in the software. Importance: Influences teaching both data and non-data practitioners to create more analysis-friendly spreadsheets, and has been described to outline "spreadsheet best practices". == Data visualizations == Quantitative Graphics in Statistics: A Brief History Author: James R. Beniger and Dorothy L. Robyn Publication data: Online version: https://www.jstor.org/stable/2683467 Description: Outlines history and evolution of quantitative graphics in statistics, going through spatial organization (17th and 18th centuries), discrete comparison (18th and 19th centuries), continuous distribution (19th century), and multivariate distribution and correlation (late 19th and 20th centuries). Importance: Helps put into perspective for learning data practitioners the recency of graphics that are used. A later publication "Graphical Methods in Statistics" by Stephen Fienberg in 1979 writes that his publication "owes much to the work of Beniger and Robyn". == Practice == Data Science for Business Author: Foster Provost and Tom Fawcett Publication data: Online version: N/A Description: Broadly outlines principles of data science and data-analytic thinking for businesses. Importance: Cited over 3,000 times, it is "highly recommended for students" but also it is also recommended due to its "relevance to senior management leaders who want to build and lead a team of data scientists and implement data science in solving complex business problems". == Tooling == Hidden Technical Debt in Machine Learning Systems Author: D. Sculley, Gary Holy, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison Publication data: Online version: https://proceedings.neurips.cc/paper_files/paper/2015/file/86df7dcfd896fcaf2674f757a2463eba-Paper.pdf Description: This paper argues that it is "dangerous to think of [complex machine learning] quick wins as coming for free" and overviews risk factors to account for when implementing a machine learning system. Importance: All authors worked for Google, article is cited over 2,000 times, and helped practitioners thinking about quickly implementing a machine learning tool without understanding the long-term maintenance of the tool. A few useful things to know about machine learning Author: Pedro Domingos Publication data: Online version: https://dl.acm.org/doi/10.1145/2347736.2347755 https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf Description: The purpose of this paper is to distill inaccessible "folk knowledge" to effectively implement machine learning projects because "machin

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  • Clean Email

    Clean Email

    Clean Email is an automated software as a service email management application which identifies and clears junk mail from inboxes. The service uses a subscription business model with a free trial for the first 1,000 emails. and is available on macOS, iOS, Android, and on the web. == History == Clean Email is a self-funded company headquartered in Los Angeles, California. Initially developed by the founder for personal use, the service was designed to address the growing issue of inbox clutter and privacy concerns. In 2017, John Gruber recognized Clean Email as a trustworthy alternative to Unroll.me after the latter was found to be selling user data. == Features == Clean Email uses algorithms to identify and categorize emails, enabling users to group, remove, label, and archive email messages in bulk. Its Unsubscriber tool consolidates all subscriptions and newsletters into a single view for quick management, allowing users to bulk unsubscribe or temporarily pause mail. Its Screener feature transforms the inbox into an "opt-in" system, enabling users to pre-approve mail from new senders. Cleaning Suggestions identifies frequently cleaned mail, recommending actions accordingly. Additional functionalities include automatic deletion of aging emails, delivery of messages to specified folders, and options to mute or block senders.

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  • Automation

    Automation

    Automation describes a wide range of technologies that reduce human intervention in processes, mainly by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques. The benefits of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision. Automation includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networks, steering, stabilization of ships, aircraft and other applications and vehicles with reduced human intervention. Examples range from a household thermostat controlling a boiler to a large industrial control system with tens of thousands of input measurements and output control signals. In the simplest type of an automatic control loop, a controller compares a measured value of a process with a desired set value and processes the resulting error signal to change some input to the process, in such a way that the process stays at its set point despite disturbances. This closed-loop control is an application of negative feedback to a system. The mathematical basis of control theory began in the 18th century and advanced rapidly in the 20th. The term automation, inspired by the earlier word automatic (coming from automaton), was not widely used before 1947, when Ford established an automation department. It was during this time that the industry was rapidly adopting feedback controllers, Technological advancements introduced in the 1930s revolutionized various industries significantly. The World Bank's World Development Report of 2019 shows evidence that the new industries and jobs in the technology sector outweigh the economic effects of workers being displaced by automation. Job losses and downward mobility blamed on automation have been cited as one of many factors in the resurgence of nationalist, protectionist and populist politics in the US, UK and France, among other countries since the 2010s. == History == === Early history === It was a preoccupation of the Greeks and Arabs (in the period between about 300 BC and about 1200 AD) to keep an accurate track of time. In Ptolemaic Egypt, about 270 BC, Ctesibius described a float regulator for a water clock, a device not unlike the ball and cock in a modern flush toilet. This was the earliest feedback-controlled mechanism. The appearance of the mechanical clock in the 14th century made the water clock and its feedback control system obsolete. The Persian Banū Mūsā brothers, in their Book of Ingenious Devices (850 AD), described a number of automatic controls. Two-step level controls for fluids, a form of discontinuous variable structure controls, were developed by the Banu Musa brothers. They also described a feedback controller. The design of feedback control systems up through the Industrial Revolution was by trial-and-error, together with a great deal of engineering intuition. It was not until the mid-19th century that the stability of feedback control systems was analyzed using mathematics, the formal language of automatic control theory. The centrifugal governor was invented by Christiaan Huygens in the seventeenth century, and used to adjust the gap between millstones. === Industrial Revolution in Western Europe === The introduction of prime movers, or self-driven machines advanced grain mills, furnaces, boilers, and the steam engine created a new requirement for automatic control systems including temperature regulators (invented in 1624; see Cornelius Drebbel), pressure regulators (1681), float regulators (1700) and speed control devices. Another control mechanism was used to tent the sails of windmills. It was patented by Edmund Lee in 1745. Also in 1745, Jacques de Vaucanson invented the first automated loom. Around 1800, Joseph Marie Jacquard created a punch-card system to program looms. In 1771 Richard Arkwright invented the first fully automated spinning mill driven by water power, known at the time as the water frame. An automatic flour mill was developed by Oliver Evans in 1785, making it the first completely automated industrial process. A centrifugal governor was used by Mr. Bunce of England in 1784 as part of a model steam crane. The centrifugal governor was adopted by James Watt for use on a steam engine in 1788 after Watt's partner Boulton saw one at a flour mill Boulton & Watt were building. The governor could not actually hold a set speed; the engine would assume a new constant speed in response to load changes. The governor was able to handle smaller variations such as those caused by fluctuating heat load to the boiler. Also, there was a tendency for oscillation whenever there was a speed change. As a consequence, engines equipped with this governor were not suitable for operations requiring constant speed, such as cotton spinning. Several improvements to the governor, plus improvements to valve cut-off timing on the steam engine, made the engine suitable for most industrial uses before the end of the 19th century. Advances in the steam engine stayed well ahead of science, both thermodynamics and control theory. The governor received relatively little scientific attention until James Clerk Maxwell published a paper that established the beginning of a theoretical basis for understanding control theory. === 20th century === Relay logic was introduced with factory electrification, which underwent rapid adaptation from 1900 through the 1920s. Central electric power stations were also undergoing rapid growth and the operation of new high-pressure boilers, steam turbines and electrical substations created a great demand for instruments and controls. Central control rooms became common in the 1920s, but as late as the early 1930s, most process controls were on-off. Operators typically monitored charts drawn by recorders that plotted data from instruments. To make corrections, operators manually opened or closed valves or turned switches on or off. Control rooms also used color-coded lights to send signals to workers in the plant to manually make certain changes. The development of the electronic amplifier during the 1920s, which was important for long-distance telephony, required a higher signal-to-noise ratio, which was solved by negative feedback noise cancellation. This and other telephony applications contributed to the control theory. In the 1940s and 1950s, German mathematician Irmgard Flügge-Lotz developed the theory of discontinuous automatic controls, which found military applications during the Second World War to fire control systems and aircraft navigation systems. Controllers, which were able to make calculated changes in response to deviations from a set point rather than on-off control, began being introduced in the 1930s. Controllers allowed manufacturing to continue showing productivity gains to offset the declining influence of factory electrification. Factory productivity was greatly increased by electrification in the 1920s. U.S. manufacturing productivity growth fell from 5.2%/yr 1919–29 to 2.76%/yr 1929–41. Alexander Field notes that spending on non-medical instruments increased significantly from 1929 to 1933 and remained strong thereafter. The First and Second World Wars saw major advancements in the field of mass communication and signal processing. Other key advances in automatic controls include differential equations, stability theory and system theory (1938), frequency domain analysis (1940), ship control (1950), and stochastic analysis (1941). Starting in 1958, various systems based on solid-state digital logic modules for hard-wired programmed logic controllers (the predecessors of programmable logic controllers [PLC]) emerged to replace electro-mechanical relay logic in industrial control systems for process control and automation, including early Telefunken/AEG Logistat, Siemens Simatic, Philips/Mullard/Valvo Norbit, BBC Sigmatronic, ACEC Logacec, Akkord Estacord, Krone Mibakron, Bistat, Datapac, Norlog, SSR, or Procontic systems. In 1959 Texaco's Port Arthur Refinery became the first chemical plant to use digital control. Conversion of factories to digital control began to spread rapidly in the 1970s as the price of computer hardware fell. === Significant applications === The automatic telephone switchboard was introduced in 1892 along with dial telephones. By 1929, 31.9% of the Bell system was automatic. Automatic telephone switching originally used vacuum tube amplifiers and electro-mechanical switches, which consumed a large amount of electricity. Call volume eve

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  • Teechart

    Teechart

    TeeChart is a charting library for programmers, developed and managed by Steema Software of Girona, Catalonia, Spain. It is available as commercial and non-commercial software. TeeChart has been included in most Delphi and C++Builder products since 1997, and TeeChart Standard currently is part of Embarcadero RAD Studio 13 Florence. TeeChart Pro version is a commercial product that offers shareware releases for all of its formats. The TeeChart Charting Library offers charts, maps and gauges in versions for Delphi VCL/FMX, ActiveX, C# for Microsoft Visual Studio .NET. Full source code has always been available for all versions except the ActiveX version. TeeChart's user interface is translated into 38 languages. == History == The first version of TeeChart was authored in 1995 by David Berneda, co-founder of Steema, using the Borland Delphi Visual Component Library programming environment and TeeChart was first released as a shareware version and made available via Compuserve in the same year. It was written in the first version of Delphi VCL, as a 16-bit Charting Library named TeeChart version 1. The next version of TeeChart was released as a 32-bit library (Delphi 2 supported 32-bit compilation) but was badged as TeeChart VCL v3 to coincide with Borland's naming convention for inclusion on the toolbox palette of Borland Delphi v3 in 1997 and with C++ Builder v3 in 1998. It has been on the Delphi/C++ Builder toolbox palette ever since. The current version is Embarcadero RAD Studio 13 Florence. TeeChart's first ActiveX version named "version 3" too, to match the VCL version's nomenclature, was released in 1998. The version was optimised to work with Microsoft's Visual Studio v97 and v6.0 developer suites that include Visual Basic and Microsoft Visual C++ programming languages. Support for new programming environments followed with TeeChart's first native C# version for Microsoft Visual Studio .NET released in 2002 and TeeChart.Lite for .NET, a free charting component, released for Visual Studio.NET in 2003 and supporting too, Mono (programming). Steema Software released the first native TeeChart Java (programming language) version in 2006 and TeeChart's first native PHP version was released in 2009 and published as open-source in June 2010. Mobile versions of TeeChart, for Android (operating system) devices and Windows Phone 7 devices were released during the first half of 2011. In 2012 TeeChart extended functionality to iPhone/iPad and BlackBerry OS devices and a new JavaScript version was released in the same year to support HTML5 Canvas. In 2013 Steema launched TeeChart for .NET Chart for Windows Store applications and included support for Microsoft's Windows Phone 8 mobile platform. TeeChart for Xamarin.Forms written with 100% C# code and cross-platform support for .NET desktops, Windows Phone, iOS and Android was released in 2014. Also since 2014 Webforms charts now offers HTML5 interactivity. Steema launched TeeChart for Avalonia (software framework) in 2022 and in 2023 .NET_MAUI support was added to the TeeChart for .NET. == Usage == TeeChart is a general purpose charting component designed for use in differing ambits, offering a wide range of aesthetics to chart data. Generally TeeCharts published in the field, in areas where large amounts of data must be interpreted regularly, remain by designer choice in their simplest form to maximize the "data-ink ratio". Sloan Digital Sky Survey, SDSS Web Services' use for charting "Scientific .. plotting of online data" at The Virtual Observatory Spectrum Services reflects that approach. The SDSS chart authors choose to represent data using TeeChart's standard 2D line display. Speed is also a factor when choosing how to most effectively plot data. Realtime data, at frequencies of up to tens or hundreds of data points or more per second, require the most processor economic approach to charting. Computer processing time dedicated to the plotting of data needs to be as lightweight as possible, freeing-up computer tasks "to achieve real-time data acquisition, display and analysis". A critical and stated aspect of many data visualisation applications is the ability to offer interactivity to the user; NASA's document, the Orbital Debris Engineering Model Model ORDEM 3.0 - User's Guide, 2014, states that "The user may manipulate the graphs to zoom, pan, and copy to the clipboard and export to various file types" and Computer and Computing Technologies in Agriculture II, Volume 1, Daoliang, Li; Chunjiang, Zhao (2009), also using TeeChart, states "the properties at any point in the chart can be viewed moving the mouse over it". Writing about control education, Juha Lindfors states "The desired charting functionality (such as zooming and scaling) is achieved..". Charting applications have become increasingly 'onlined', made available either to a wider public or to a territorially remote userbase via networked applications. The World Wide Web (the Web) has become "by far, the most popular Internet protocol" to disseminate online applications. Most major IDEs now offer environments for web application developede aimed at browser hosted applications. Charting components, TeeChart among them, have adapted to provide models that work within a browser environment, often using static images and scripted layering techniques such as Ajax (programming) to offer a level of interactivity, improve response times and hide apparent delay from the user. Options to enrich client, browser-side processing flexibility are exploited by TeeChart libraries via modules that offer 'micro-environments' within the browser, such as the long established ActiveX technology, Adobe Flash, Microsoft Silverlight or Java Applets. Serverside environments offer too, a means to interact with browser based script to dynamically respond to charting requests. Joomla and CodeIgniter are host environments for TeeChart PHP and an example of an Embarcadero IntraWeb VCL designed application using TeeChart, is documented here. == Programmer reference == The Code Project includes a demo that uses TeeChart.Lite, called 'Self-Organizing Feature Maps (Kohonen maps)' written by Bashir Magomedovl and SourceForge includes a Database Stress and Monitor that also uses TeeChart.Lite. Books and information sources that include substantial sections about working with the Delphi version of TeeChart include "Mastering Delphi 6" by Marco Cantù, "C++ Builder 5 developer's guide", a video Delphi Tutorial on charting JPEG compression and support forums and reference pages at TeeChart Support Forums. Non-English language document sources include, in Czech "Myslíme v jazyku Delphi 7: knihovna zkušeného programátora" by Marco Cantù, and Chinese, Delphi 6, Delphi, and Delphi 5.

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  • OpenIO

    OpenIO

    OpenIO offered object storage for a wide range of high-performance applications. OpenIO was founded in 2015 by Laurent Denel (CEO), Jean-François Smigielski (CTO) and five other co-founders; it leveraged open source software, developed since 2006, based on a grid technology that enabled dynamic behaviour and supported heterogenous hardware. In October 2017 OpenIO was completed a $5 million funding rounds. In July 2020 OpenIO had been acquired by OVH and withdrawn from the market to become the core technology of OVHcloud object storage offering. == Software == OpenIO is a software-defined object store that supports S3 and can be deployed on-premises, cloud-hosted or at the edge, on any hardware mix. It has been designed from the beginning for performance and cost-efficiency at any scale, and it has been optimized for Big Data, HPC and AI. OpenIO stores objects within a flat structure within a massively distributed directory with indirections, which allows the data query path to be independent of the number of nodes and the performance not to be affected by the growth of capacity. Servers are organized as a grid of nodes massively distributed, where each node takes part in directory and storage services, which ensures that there is no single point of failure and that new nodes are automatically discovered and immediately available without the need to rebalance data. The software is built on top of a technology that ensures optimal data placement based on real-time metrics and allows the addition or removal of storage devices with automatic performance and load impact optimization. For data protection OpenIO has synchronous and asynchronous replication with multiple copies, and an erasure coding implementation based on Reed-Solomon that can be deployed in one data center or geo-distributed or stretched clusters. The software has a feature that catches all events that occur in the cluster and can pass them up in the stack or to applications running on OpenIO nodes. This enables event-driven computing directly into the storage infrastructure. The open source code is available on Github and it is licensed under AGPL3 for server code and LGPL3 for client code. == Performance == OpenIO claimed in 2019 to have reached 1.372 Tbit/s write speed (171 GB/s) on a cluster of 350 physical machines. The benchmark scenario, conducted under production conditions with standard hardware (commodity servers with 7200 rpm HDDs), consisted in backing up a 38 PB Hadoop datalake via the DistCp command. This level of performance marked, according to analysts, the arrival of a new generation of object storage technologies oriented toward high performance and hyper-scalability.

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  • Content Security Policy

    Content Security Policy

    Content Security Policy (CSP) is a computer security standard introduced to prevent cross-site scripting (XSS), clickjacking and other code injection attacks resulting from execution of malicious content in the trusted web page context. It is a Candidate Recommendation of the W3C working group on Web Application Security, widely supported by modern web browsers. CSP provides a standard method for website owners to declare approved origins of content that browsers should be allowed to load on that website—covered types are JavaScript, CSS, HTML frames, web workers, fonts, images, embeddable objects such as Java applets, ActiveX, audio and video files, and other HTML5 features. == Status == The standard, originally named Content Restrictions, was proposed by Robert Hansen in 2004, first implemented in Firefox 4 and quickly picked up by other browsers. Version 1 of the standard was published in 2012 as W3C candidate recommendation and quickly with further versions (Level 2) published in 2014. As of 2023, the draft of Level 3 is being developed with the new features being quickly adopted by the web browsers. The following header names are in use as part of experimental CSP implementations: Content-Security-Policy – standard header name proposed by the W3C document. Google Chrome supports this as of version 25. Firefox supports this as of version 23, released on 6 August 2013. WebKit supports this as of version 528 (nightly build). Chromium-based Microsoft Edge support is similar to Chrome's. X-WebKit-CSP – deprecated, experimental header introduced into Google Chrome, Safari and other WebKit-based web browsers in 2011. X-Content-Security-Policy – deprecated, experimental header introduced in Gecko 2 based browsers (Firefox 4 to Firefox 22, Thunderbird 3.3, SeaMonkey 2.1). A website can declare multiple CSP headers, also mixing enforcement and report-only ones. Each header will be processed separately by the browser. CSP can also be delivered within the HTML code using a meta tag, although in this case its effectiveness will be limited. Internet Explorer 10 and Internet Explorer 11 also support CSP, but only sandbox directive, using the experimental X-Content-Security-Policy header. A number of web application frameworks support CSP, for example AngularJS (natively) and Django (middleware). Instructions for Ruby on Rails have been posted by GitHub. Web framework support is however only required if the CSP contents somehow depend on the web application's state—such as usage of the nonce origin. Otherwise, the CSP is rather static and can be delivered from web application tiers above the application, for example on load balancer or web server. === Bypasses === In December 2015 and December 2016, a few methods of bypassing 'nonce' allowlisting origins were published. In January 2016, another method was published, which leverages server-wide CSP allowlisting to exploit old and vulnerable versions of JavaScript libraries hosted at the same server (frequent case with CDN servers). In May 2017 one more method was published to bypass CSP using web application frameworks code. == Mode of operation == If the Content-Security-Policy header is present in the server response, a compliant client enforces the declarative allowlist policy. One example goal of a policy is a stricter execution mode for JavaScript in order to prevent certain cross-site scripting attacks. In practice this means that a number of features are disabled by default: Inline JavaScript code