17582

Automated Testing of Graphics Shader Compilers

Alastair F. Donaldson, Hugues Evrard, Andrei Lascu, Paul Thomson
Imperial College London, UK
ACM Programming Languages, OOPSLA, Article 93, 29 pages, 2017

@article{metamorphic:oopsla17,

   author={Alastair F. Donaldson and Hugues Evrard and Andrei Lascu and Paul Thomson},

   title={Automated Testing of Graphics Shader Compilers},

   journal={Proceedings of the ACM Programming Languages},

   volume={1},

   number={undefined},

   year={2017}

}

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We present an automated technique for finding defects in compilers for graphics shading languages. A key challenge in compiler testing is the lack of an oracle that classifies an output as correct or incorrect; this is particularly pertinent in graphics shader compilers where the output is a rendered image that is typically under-specified. Our method builds on recent successful techniques for compiler validation based on metamorphic testing, and leverages existing high-value graphics shaders to create sets of transformed shaders that should be semantically equivalent. Rendering mismatches are then indicative of shader compilation bugs. Deviant shaders are automatically minimized to identify, in each case, a minimal change to an original high-value shader that induces a shader compiler bug. We have implemented the approach as a tool, GLFuzz, targeting the OpenGL shading language, GLSL. Our experiments over a set of 17 GPU and driver configurations, spanning the main 7 GPU designers, have led to us finding and reporting more than 60 distinct bugs, covering all tested configurations. As well as defective rendering, these issues identify security-critical vulnerabilities that affect WebGL, including a significant remote information leak security bug where a malicious web page can capture the contents of other browser tabs, and a bug whereby visiting a malicious web page can lead to a "blue screen of death" under Windows 10. Our findings show that shader compiler defects are prevalent, and that metamorphic testing provides an effective means for detecting them automatically.
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