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Author Sekar, R. ♦ Hasabnis, Niranjan
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract Translating low-level machine instructions into higher-level intermediate language (IL) is one of the central steps in many binary analysis and instrumentation systems. Existing systems build such translators manually. As a result, it takes a great deal of effort to support new architectures. Even for widely deployed architectures, full instruction sets may not be modeled, e.g., mature systems such as Valgrind still lack support for AVX, FMA4 and SSE4.1 for x86 processors. To overcome these difficulties, we propose a novel approach that leverages knowledge about instruction set semantics that is already embedded into modern compilers such as GCC. In particular, we present a learning-based approach for automating the translation of assembly instructions to a compiler's architecture-neutral IL. We present an experimental evaluation that demonstrates the ability of our approach to easily support many architectures (x86, ARM and AVR), including their advanced instruction sets. Our implementation is available as open-source software.
Description Affiliation: Stony Brook University, Stony Brook, NY, USA (Sekar, R.) || Intel, Santa Clara, CA, USA (Hasabnis, Niranjan)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1981-04-01
Publisher Place New York
Journal ACM SIGARCH Computer Architecture News (CARN)
Volume Number 44
Issue Number 2
Page Count 14
Starting Page 311
Ending Page 324


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Source: ACM Digital Library