losssless

Lossless compression refers to data compression methods that allow the original data to be perfectly reconstructed from the compressed form. The term "losssless" appears to be a misspelling of lossless and is not standard in technical literature.

Lossless algorithms achieve this by removing redundancy without discarding information. They are contrasted with lossy compression, which sacrifices some data to gain higher compression ratios. Common techniques include entropy coding and dictionary-based methods such as Huffman coding, Lempel-Ziv variants (LZ77 and LZ78), and their combinations such as the Deflate algorithm, which blends LZ77 with Huffman coding.

Applications include archival storage, software distribution, and file formats that require exact reproduction, such as text, source code, and medical or scientific data. Image formats like PNG and some audio formats like FLAC use lossless compression, while general-purpose formats such as ZIP and gzip provide versatile lossless compression for various data types.

History and theory: Lossless compression is grounded in information theory, notably Shannon's work on entropy. Practical LZ and Huffman-based methods emerged in the mid to late 20th century, culminating in standards such as DEFLATE (RFC 1951) used by gzip and PNG. Reference implementations include zlib and libdeflate, which provide widely used lossless compression functionality across software systems.