Generating Test Suites for GPU Instruction Sets through Mutation and Equivalence Checking

Shoham Shitrit, Sreepathi Pai
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Abstract

—Formal semantics for instruction sets can be used to validate implementations through formal verification. However, testing is often the only feasible method when checking an artifact such as a hardware processor, a simulator, or a compiler. In this work, we construct a pipeline that can be used to automatically generate a test suite for an instruction set from its executable semantics. Our method mutates the formal semantics, expressed as a C program, to introduce bugs in the semantics. Using a bounded model checker, we then check the mutated semantics to the original for equivalence. Since the mutated and original semantics are usually not equivalent, this yields counterexamples which can be used to construct a test suite. By combining a mutation testing engine with a bounded model checker, we obtain a fully automatic method for constructing test suites for a given formal semantics. We intend to instantiate this on a formal semantics of a portion of NVIDIA’s PTX instruction set for GPUs that we have developed. We will compare to our existing method of testing that uses stratified random sampling and evaluate effectiveness, cost, and feasibility.
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通过变异和等价检验生成GPU指令集测试套件
-指令集的形式语义可用于通过形式验证来验证实现。然而,在检查诸如硬件处理器、模拟器或编译器之类的工件时,测试通常是唯一可行的方法。在这项工作中,我们构建了一个管道,该管道可用于从指令集的可执行语义自动生成测试套件。我们的方法改变了表示为C程序的形式语义,从而在语义中引入了错误。然后,使用有界模型检查器,我们检查突变语义与原始语义的等价性。由于变异的和原始的语义通常是不相等的,这就产生了可以用来构建测试套件的反例。通过将突变测试引擎与有界模型检查器相结合,我们获得了为给定形式语义构建测试套件的全自动方法。我们打算在我们开发的gpu的NVIDIA的PTX指令集的一部分的正式语义上实例化这一点。我们将比较我们现有的使用分层随机抽样的测试方法,并评估有效性、成本和可行性。
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First, Fuzz the Mutants Generating Test Suites for GPU Instruction Sets through Mutation and Equivalence Checking
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