{"title":"基于LZ的PE文件压缩基准测试","authors":"Zsombor Paroczi","doi":"10.14232/ACTACYB.24.1.2019.9","DOIUrl":null,"url":null,"abstract":"The key element in runtime compression is the compression algorithm itself, that is used during processing. It has to be small in enough in decompression bytecode size to fit in the final executable, yet have to provide the best possible compression ratio. In our work we benchmark the top LZ based compression methods on Windows PE (both exe and dll) files, and present the results including the decompression overhead and the compression rates.","PeriodicalId":187125,"journal":{"name":"Acta Cybern.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"LZ based Compression Benchmark on PE Files\",\"authors\":\"Zsombor Paroczi\",\"doi\":\"10.14232/ACTACYB.24.1.2019.9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The key element in runtime compression is the compression algorithm itself, that is used during processing. It has to be small in enough in decompression bytecode size to fit in the final executable, yet have to provide the best possible compression ratio. In our work we benchmark the top LZ based compression methods on Windows PE (both exe and dll) files, and present the results including the decompression overhead and the compression rates.\",\"PeriodicalId\":187125,\"journal\":{\"name\":\"Acta Cybern.\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Cybern.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14232/ACTACYB.24.1.2019.9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Cybern.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14232/ACTACYB.24.1.2019.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
运行时压缩的关键元素是压缩算法本身,它在处理过程中使用。它必须足够小的解压缩字节码大小,以适应最终的可执行文件,但必须提供最佳的压缩比。在我们的工作中,我们对基于Windows PE (exe和dll)文件的顶级LZ压缩方法进行了基准测试,并给出了包括解压开销和压缩率在内的结果。
The key element in runtime compression is the compression algorithm itself, that is used during processing. It has to be small in enough in decompression bytecode size to fit in the final executable, yet have to provide the best possible compression ratio. In our work we benchmark the top LZ based compression methods on Windows PE (both exe and dll) files, and present the results including the decompression overhead and the compression rates.