2012ACM SIGPLAN NoticesRequires access

Automated synthesis of symbolic instruction encodings from I/O samples

Patrice Godefroid, Ankur Taly

Open publisher page 11 citations

Abstract

Symbolic execution is a key component of precise binary program analysis tools. We discuss how to automatically boot-strap the construction of a symbolic execution engine for a processor instruction set such as x86, x64 or ARM. We show how to automatically synthesize symbolic representations of individual processor instructions from input/output examples and express them as bit-vector constraints. We present and compare various synthesis algorithms and instruction sampling strategies. We introduce a new synthesis algorithm based on smart sampling which we show is one to two orders of magnitude faster than previous synthesis algorithms in our context. With this new algorithm, we can automatically synthesize bit-vector circuits for over 500 x86 instructions (8/16/32-bits, outputs, EFLAGS) using only 6 synthesis templates and in less than two hours using the Z3 SMT solver on a regular machine. During this work, we also discovered several inconsistencies across x86 processors, errors in the x86 Intel spec, and several bugs in previous manually-written x86 instruction handlers.

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What this paper is about

Symbolic execution is a key component of precise binary program analysis tools. We discuss how to automatically boot-strap the construction of a symbolic execution engine for a processor instruction set such as x86, x64 or ARM. We show how to automatically synthesize symbolic representations of individual processor instructions from input/output examples and express them as bit-vector constraints. We present and compare various synthesis algorithms and instruction sampling strategies. We introduce a new synthesis algorithm based on smart sampling which we show is one to two orders of magnitude faster than previous synthesis algorithms in our context. With this new algorithm, we can automatically synthesize bit-vector circuits for over 500 x86 instructions (8/16/32-bits, outputs, EFLAGS) using only 6 synthesis templates and in less than two hours using the Z3 SMT solver on a regular machine. During this work, we also discovered several inconsistencies across x86 processors, errors in the x86 Intel spec, and several bugs in previous manually-written x86 instruction handlers.

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OpenAlex reports 11 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Symbolic execution is a key component of precise binary program analysis tools. We discuss how to automatically boot-strap the construction of a symbolic execution engine for a processor instruction set such as x86, x64 or ARM. We show how to automatically synthesize symbolic representations of individual processor instructions from input/output examples and express them as bit-vector constraints. We present and compare various synthesis algorithms and instruction sampling strategies. We introduce a new synthesis algorithm based on smart sampling which we show is one to two orders of magnitude faster than previous synthesis algorithms in our context. With this new algorithm, we can automatically synthesize bit-vector circuits for over 500 x86 instructions (8/16/32-bits, outputs, EFLAGS) using only 6 synthesis templates and in less than two hours using the Z3 SMT solver on a regular machine. During this work, we also discovered several inconsistencies across x86 processors, errors in the x86 Intel spec, and several bugs in previous manually-written x86 instruction handlers.

Key concepts: x86, Computer science, Symbolic execution, Parallel computing, Instruction set, Binary translation, Programming language, Set (abstract data type)

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