{"title":"不可思议的缩小语境......就在您身边的解码器中","authors":"Sifis Lagouvardos, Yannis Bollanos, Neville Grech, Yannis Smaragdakis","doi":"arxiv-2409.11157","DOIUrl":null,"url":null,"abstract":"Decompilation of binary code has arisen as a highly-important application in\nthe space of Ethereum VM (EVM) smart contracts. Major new decompilers appear\nnearly every year and attain popularity, for a multitude of reverse-engineering\nor tool-building purposes. Technically, the problem is fundamental: it consists\nof recovering high-level control flow from a highly-optimized\ncontinuation-passing-style (CPS) representation. Architecturally, decompilers\ncan be built using either static analysis or symbolic execution techniques. We present Shrknr, a static-analysis-based decompiler succeeding the\nstate-of-the-art Elipmoc decompiler. Shrknr manages to achieve drastic\nimprovements relative to the state of the art, in all significant dimensions:\nscalability, completeness, precision. Chief among the techniques employed is a\nnew variant of static analysis context: shrinking context sensitivity.\nShrinking context sensitivity performs deep cuts in the static analysis\ncontext, eagerly \"forgetting\" control-flow history, in order to leave room for\nfurther precise reasoning. We compare Shrnkr to state-of-the-art decompilers, both static-analysis- and\nsymbolic-execution-based. In a standard benchmark set, Shrnkr scales to over\n99.5% of contracts (compared to ~95%), covers (i.e., reaches and manages to\ndecompile) 67% more code, and reduces key imprecision metrics by over 65%.","PeriodicalId":501197,"journal":{"name":"arXiv - CS - Programming Languages","volume":"10 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Incredible Shrinking Context... in a decompiler near you\",\"authors\":\"Sifis Lagouvardos, Yannis Bollanos, Neville Grech, Yannis Smaragdakis\",\"doi\":\"arxiv-2409.11157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decompilation of binary code has arisen as a highly-important application in\\nthe space of Ethereum VM (EVM) smart contracts. Major new decompilers appear\\nnearly every year and attain popularity, for a multitude of reverse-engineering\\nor tool-building purposes. Technically, the problem is fundamental: it consists\\nof recovering high-level control flow from a highly-optimized\\ncontinuation-passing-style (CPS) representation. Architecturally, decompilers\\ncan be built using either static analysis or symbolic execution techniques. We present Shrknr, a static-analysis-based decompiler succeeding the\\nstate-of-the-art Elipmoc decompiler. Shrknr manages to achieve drastic\\nimprovements relative to the state of the art, in all significant dimensions:\\nscalability, completeness, precision. Chief among the techniques employed is a\\nnew variant of static analysis context: shrinking context sensitivity.\\nShrinking context sensitivity performs deep cuts in the static analysis\\ncontext, eagerly \\\"forgetting\\\" control-flow history, in order to leave room for\\nfurther precise reasoning. We compare Shrnkr to state-of-the-art decompilers, both static-analysis- and\\nsymbolic-execution-based. In a standard benchmark set, Shrnkr scales to over\\n99.5% of contracts (compared to ~95%), covers (i.e., reaches and manages to\\ndecompile) 67% more code, and reduces key imprecision metrics by over 65%.\",\"PeriodicalId\":501197,\"journal\":{\"name\":\"arXiv - CS - Programming Languages\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Programming Languages\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.11157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Programming Languages","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Incredible Shrinking Context... in a decompiler near you
Decompilation of binary code has arisen as a highly-important application in
the space of Ethereum VM (EVM) smart contracts. Major new decompilers appear
nearly every year and attain popularity, for a multitude of reverse-engineering
or tool-building purposes. Technically, the problem is fundamental: it consists
of recovering high-level control flow from a highly-optimized
continuation-passing-style (CPS) representation. Architecturally, decompilers
can be built using either static analysis or symbolic execution techniques. We present Shrknr, a static-analysis-based decompiler succeeding the
state-of-the-art Elipmoc decompiler. Shrknr manages to achieve drastic
improvements relative to the state of the art, in all significant dimensions:
scalability, completeness, precision. Chief among the techniques employed is a
new variant of static analysis context: shrinking context sensitivity.
Shrinking context sensitivity performs deep cuts in the static analysis
context, eagerly "forgetting" control-flow history, in order to leave room for
further precise reasoning. We compare Shrnkr to state-of-the-art decompilers, both static-analysis- and
symbolic-execution-based. In a standard benchmark set, Shrnkr scales to over
99.5% of contracts (compared to ~95%), covers (i.e., reaches and manages to
decompile) 67% more code, and reduces key imprecision metrics by over 65%.