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  2. Jenkins hash function - Wikipedia

    en.wikipedia.org/wiki/Jenkins_hash_function

    The lookup3 function consumes input in 12 byte (96 bit) chunks. [9] It may be appropriate when speed is more important than simplicity. Note, though, that any speed improvement from the use of this hash is only likely to be useful for large keys, and that the increased complexity may also have speed consequences such as preventing an optimizing compiler from inlining the hash function.

  3. Whirlpool (hash function) - Wikipedia

    en.wikipedia.org/wiki/Whirlpool_(hash_function)

    Jacksum on SourceForge, a Java implementation of all three revisions of Whirlpool; whirlpool on GitHub – An open source Go implementation of the latest revision of Whirlpool; A Matlab Implementation of the Whirlpool Hashing Function; RHash, an open source command-line tool, which can calculate and verify Whirlpool hash. Perl Whirlpool module ...

  4. SipHash - Wikipedia

    en.wikipedia.org/wiki/SipHash

    SipHash computes a 64-bit message authentication code from a variable-length message and 128-bit secret key. It was designed to be efficient even for short inputs, with performance comparable to non-cryptographic hash functions, such as CityHash; [4]: 496 [2] this can be used to prevent denial-of-service attacks against hash tables ("hash flooding"), [5] or to authenticate network packets.

  5. Java code coverage tools - Wikipedia

    en.wikipedia.org/wiki/Java_Code_Coverage_Tools

    The runtime overhead of added instrumentation is small (5–20%) and the bytecode instrumentor itself is very fast (mostly limited by file I/O speed). Memory overhead is a few hundred bytes per Java class. EMMA is 100% pure Java, has no external library dependencies, and works in any Java 2 JVM (even 1.2.x).

  6. LZ4 (compression algorithm) - Wikipedia

    en.wikipedia.org/wiki/LZ4_(compression_algorithm)

    Each sequence begins with a one-byte token that is broken into two 4-bit fields. The first field represents the number of literal bytes that are to be copied to the output. The second field represents the number of bytes to copy from the already decoded output buffer (with 0 representing the minimum match length of 4 bytes).

  7. Java bytecode - Wikipedia

    en.wikipedia.org/wiki/Java_bytecode

    Java bytecode is used at runtime either interpreted by a JVM or compiled to machine code via just-in-time (JIT) compilation and run as a native application. As Java bytecode is designed for a cross-platform compatibility and security, a Java bytecode application tends to run consistently across various hardware and software configurations. [3]

  8. Adler-32 - Wikipedia

    en.wikipedia.org/wiki/Adler-32

    An Adler-32 checksum is obtained by calculating two 16-bit checksums A and B and concatenating their bits into a 32-bit integer. A is the sum of all bytes in the stream plus one, and B is the sum of the individual values of A from each step. At the beginning of an Adler-32 run, A is initialized to 1, B to 0.

  9. Fletcher's checksum - Wikipedia

    en.wikipedia.org/wiki/Fletcher's_checksum

    When the data word is divided into 8-bit blocks, as in the example above, two 8-bit sums result and are combined into a 16-bit Fletcher checksum. Usually, the second sum will be multiplied by 256 and added to the simple checksum, effectively stacking the sums side-by-side in a 16-bit word with the simple checksum at the least significant end.