The paper describe the automatically generated compression algorithm for dataset of real numbers. Authors describes 48 basic operation on datasets of the real numbers. Described operations work on the byte or word levels. Therefore, we do not see Huffman or arithmetic coding as one of them. Then they use they framework CRUSHER to try every possible combination of the operations of the given length (4 operations) and evaluate the resulting compression on the datasets. The best algorithm is called SPDP and the paper reports its compression ratio on several datasets. The achieved compression ration is between 1-2 for the most cases but the absolute best dataset achieves compression ration 34.
Operations used by the compression algorithms are sufficiently described and I believe it should be possible to replicate the work. The paper do not describe the CRUSHER framework but reference several additional paper which both use CRUSHER or should describe it.
Authors mentioned the possibility of the use of CRUSHER to generate compression algorithm for specific dataset but the did not provide any time measurement of the generation process.
It would be beneficial to read more papers about CRUSHER and possibly try the described approach on my data.
Link: https://pdfs.semanticscholar.org/204a/f81b89d7b586d7b20025fd3b7f1120446e6b.pdf
Operations used by the compression algorithms are sufficiently described and I believe it should be possible to replicate the work. The paper do not describe the CRUSHER framework but reference several additional paper which both use CRUSHER or should describe it.
Authors mentioned the possibility of the use of CRUSHER to generate compression algorithm for specific dataset but the did not provide any time measurement of the generation process.
It would be beneficial to read more papers about CRUSHER and possibly try the described approach on my data.
Link: https://pdfs.semanticscholar.org/204a/f81b89d7b586d7b20025fd3b7f1120446e6b.pdf
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