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2. Smallpdf.com - Wikipedia

   en.wikipedia.org/wiki/Smallpdf.com

   Smallpdf is a Swiss online web-based PDF software, founded in 2013. [2] It offers free version with limited features to compress, convert and edit PDF documents. [3] And its paid version offers advanced features like OCR, compress, and more. [4]

3. List of archive formats - Wikipedia

   en.wikipedia.org/wiki/List_of_archive_formats

   An open source, patent- and royalty-free compression format. The compression algorithm is a Burrows–Wheeler transform followed by a move-to-front transform and finally Huffman coding. .F, .?XF [e] Freeze/melt [3] QNX4, Unix-like and DOS: Old compressor for QNX4 OS. The compression algorithm is a modified LZSS, with an adaptive Huffman coding ...

4. bzip2 - Wikipedia

   en.wikipedia.org/wiki/Bzip2

   bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm.It only compresses single files and is not a file archiver.It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting.

5. PDF - Wikipedia

   en.wikipedia.org/wiki/PDF

   Many PDF viewers are provided free of charge from a variety of sources. Programs to manipulate and edit PDF files are available, usually for purchase. There are many software options for creating PDFs, including the PDF printing capabilities built into macOS, iOS, [72] and most Linux distributions.

6. Executable compression - Wikipedia

   en.wikipedia.org/wiki/Executable_compression

   Executable compression used to be more popular when computers were limited to the storage capacity of floppy disks, which were both slow and low capacity media, and small hard drives; it allowed the computer to store more software in the same amount of space, without the inconvenience of having to manually unpack an archive file every time the ...

7. Lossless compression - Wikipedia

   en.wikipedia.org/wiki/Lossless_compression

   Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (i.e. frequently encountered) data will produce shorter output than "improbable" data.