为反编译代码建议有意义的变量名:一种机器翻译方法

A. Jaffe
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引用次数: 3

摘要

反编译代码缺少有意义的变量名。我们使用统计机器翻译来建议给定上下文的自然变量名称。这种技术以前已经成功地应用于混淆的JavaScript代码,但是反编译的C代码在构建对齐的语料库和从几个候选中选择最佳翻译时提出了独特的挑战。
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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.
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