Prefix Free offers features such as efficient processing of stylesheets along with the processing of elements with a style attribute. It supports users in the use of the JQuery method for setting unprefixed properties by way of a plugin. It provides high-quality browser support for all the major browsers like IE9+, Opera 10+, Firefox 3.5+ and Chrome. It is available for Android, Mobile Safari, Opera Mobile and Chrome on mobile as well.
23,819
websites using Prefix-Free
Create a technology report →Export the list of all websites using Prefix-Free with their listed metadata
Websites using Prefix-Free by countrymarket share · top 8 countries
🇺🇸United States
🇩🇪Germany
🇬🇧United Kingdom
🇨🇳China
🇷🇺Russian Federation
🇰🇷Korea, Republic of
🇫🇷France
🇮🇹Italy
0%2%4%6%8%
Websites using Prefix-Free by industrydetected industries
Construction24%
Technology & Computing20%
Education17%
Shopping15%
Manufacturing & Industrial12%
Marketing & Advertising12%
Websites using Prefix-Free
showing 25 of 23,819| Website | Country | Industry | Size | Founded | |
|---|---|---|---|---|---|
| 🇸🇪SE | Technology & Computing | 1-10 | - | ||
| 🇺🇸US | Software Development | 51-200 | 2014 | ||
| 🇷🇺RU | Construction | 51-200 | 2015 | ||
| 🇨🇳CN | - | 1-10 | - | ||
| 🇨🇦CA | Science | 1-10 | 2017 | ||
| 🇺🇸US | Hardware & Electronics | 1-10 | - | ||
| 🇺🇸US | Technology & Computing | 11-50 | 2012 | ||
| 🇵🇪PE | Law & Government | 201-500 | 1996 | ||
| 🇲🇽MX | - | 1-10 | - | ||
| 🇨🇳CN | Home & Garden | 1001-5000 | 1996 | ||
| 🇮🇳IN | Education | 51-200 | 2018 | ||
| 🇯🇵JP | Marketing & Advertising | 201-500 | - | ||
| 🇧🇬BG | Entertainment | 11-50 | 1997 | ||
| 🇺🇸US | Technology & Computing | 11-50 | 2006 | ||
| 🇲🇽MX | Automotive | 1001-5000 | 1988 | ||
| 🇬🇧GB | Technology & Computing | 11-50 | 2015 | ||
| 🇩🇪DE | Events & Attractions | 51-200 | 1924 | ||
| 🇮🇷IR | Software Development | 1-10 | 2007 | ||
| 🇧🇷BR | Telecommunications | 1-10 | - | ||
| 🇺🇸US | Software Development | 11-50 | - | ||
| 🇷🇺RU | Shopping | 1001-5000 | 1995 | ||
| 🇨🇳CN | Wholesale & Distribution | 1-10 | - | ||
| 🇧🇬BG | Technology & Computing | 1-10 | 1999 | ||
| 🇫🇷FR | Software Development | 1-10 | - | ||
| 🇬🇧GB | Manufacturing & Industrial | 11-50 | 1977 |
Showing 25 of 23,819 websitesGet the full list →
Frequently asked
What is a Prefix-Free code?›
A Prefix-Free code, also known as a prefix code or non-singular code, is a type of encoding where no code in the set can be a prefix of another. This property ensures that the encoded data can be uniquely and unambiguously decoded without any need for delimiters or other markers.
What are some common applications of Prefix-Free codes?›
Prefix-Free codes are used in many fields including communications, data compression, and computer science. Examples of Prefix-Free codes include Huffman coding, which is used in data compression algorithms like DEFLATE (used by ZIP files and HTTP compression), and variable-length codes in transmission systems to optimize the transmission rate.
How is Prefix-Free coding related to entropy in information theory?›
In information theory, entropy represents the minimum average number of bits required to represent a source of information. Prefix-Free codes aim to approach this entropy by using shorter codes for more frequently occurring symbols and longer codes for less frequent ones. This ensures efficient encoding and optimal data compression.
What is the difference between Prefix-Free codes and fixed-length codes?›
In a fixed-length code, every symbol has an equal number of bits assigned to its representation, regardless of frequency. Prefix-Free codes, on the other hand, use variable-length encoding, meaning more frequent symbols have shorter codes while less frequent symbols have longer codes. Prefix-Free coding is usually more efficient and achieves better compression results than fixed-length coding.
Can a Prefix-Free code be constructed for any given set of data?›
Yes, it is possible to create a Prefix-Free code for any given data set or source. It involves analyzing the frequency of occurrence of symbols in the data and assigning codes accordingly. Various algorithms, like Huffman coding or Shannon-Fano coding, can be employed to generate an optimal Prefix-Free code for a given probability distribution of symbols.