Another package into debian experimental thanks to @vagrantc of @reproducible_builds . 🎉🙏

lcrq provides Forward Error Correction via raptorq fountain codes.

@dentangle @librecast @vagrantc @reproducible_builds wow, that’s awesome news! We might finally have an avenue to optimize the FEC code in Freenet! (ideal would be 200% redundancy, not 100%,¹ but the patents on raptor codes prevented that and I did not notice the waiver)


@ArneBab @librecast @vagrantc @reproducible_builds See the "IPR declarations" section on the RFC.

RaptorQ will recover the data with a very high degree of probability with just a couple of overhead symbols.


@ArneBab @librecast @vagrantc @reproducible_builds You can generate a a more or less limitless set of unique encoding symbols (UINT32_MAX, so ~4 billion), distribute them how you wish, and the recover the data from *any* K' symbols.

@ArneBab @librecast @vagrantc @reproducible_builds there's a pair of programs in examples/ (scatter + gather) that will take a file, encode it and write random symbols to disk, then reassemble the file from those.

@ArneBab @librecast @vagrantc @reproducible_builds just bear in mind for large files it will be slow, so generally best to split it yourself into more managable chunks before encoding. Block sizes make a huge difference to performance.

@ArneBab @librecast @vagrantc @reproducible_builds Java? Haven't noticed, but also haven't looked. There are competent ones in Rust and so on. I'll probably port LCRQ to webassembly so it's useable from js, but I don't do Java.


@dentangle @librecast @vagrantc @reproducible_builds Since Freenet is written in Java, we need libs in Java — any step to native code creates lots of maintenance nightmares (been there …).

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