{"title":"为反编译代码建议有意义的变量名:一种机器翻译方法","authors":"A. Jaffe","doi":"10.1145/3106237.3121274","DOIUrl":null,"url":null,"abstract":"Decompiled code lacks meaningful variable names. We used statistical machine translation to suggest variable names that are natural given the context. This technique has previously been successfully applied to obfuscated JavaScript code, but decompiled C code poses unique challenges in constructing an aligned corpus and selecting the best translation from among several candidates.","PeriodicalId":313494,"journal":{"name":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Suggesting meaningful variable names for decompiled code: a machine translation approach\",\"authors\":\"A. Jaffe\",\"doi\":\"10.1145/3106237.3121274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decompiled code lacks meaningful variable names. We used statistical machine translation to suggest variable names that are natural given the context. This technique has previously been successfully applied to obfuscated JavaScript code, but decompiled C code poses unique challenges in constructing an aligned corpus and selecting the best translation from among several candidates.\",\"PeriodicalId\":313494,\"journal\":{\"name\":\"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3106237.3121274\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3106237.3121274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Suggesting meaningful variable names for decompiled code: a machine translation approach
Decompiled code lacks meaningful variable names. We used statistical machine translation to suggest variable names that are natural given the context. This technique has previously been successfully applied to obfuscated JavaScript code, but decompiled C code poses unique challenges in constructing an aligned corpus and selecting the best translation from among several candidates.