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Practical Floating-Point Tests with Integer Code

机译:用整数代码进行实际浮点测试

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摘要

Testing integer software with symbolic execution is wellestablished but floating-point remains a specialty feature. Modern symbolic floating-point tactics include concretization, lexical analysis, floating-point solvers, and intricate theories, but mostly ignore the default integer-only capabilities. If a symbolic executor is already highperformance, then software-emulation, common to integer-only machines, becomes a compelling choice for symbolic floating-point. We propose a software floating-point emulation extension for symbolic execution of binary programs. First, supporting a soft floating-point library requires little effort, so multiple models are cheap; our executor has five distinct open source soft floating-point code bases. For integrity, test cases from symbolic execution of library code itself are hardware validated; mismatches with hardware appear in every tested library, a justin- time compiler, a machine decoder, and several floating-point solvers. In practice, the executor finds program faults involving floating-point in hundreds of Linux binaries.
机译:使用符号执行测试整数软件是合法的,但浮点仍然是一个专业功能。现代符号浮点策略包括具体化,词汇分析,浮点求解器和错综复杂的理论,但主要忽略默认的整数功能。如果符号执行器已经高性能,则软件仿真(仅限Integer Machines)将成为符号浮点的引人注目的选择。我们提出了一种用于符号执行二进制程序的软件浮点仿真扩展。首先,支持软浮点库需要很少的努力,所以多种型号便宜;我们的执行程序有五个不同的开源软浮点代码。对于完整性,符号执行库代码本身的测试用例是验证的硬件;每个测试的库中都出现了硬件的不匹配,一次性编译器,机器解码器和几个浮点求解器。在实践中,执行程序发现涉及数百个Linux二进制文件中的浮点的程序故障。

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