Understanding and Detecting Performance Bugs in Markdown Compilers

Penghui Li, Yinxi Liu, Wei Meng

Abstract: Markdown compilers are widely used for translating plain Markdown text into formatted text, yet they suffer from performance bugs that cause performance degradation and resource exhaustion. Currently, there is little knowledge and understanding about these performance bugs in the wild. In this work, we first conduct a comprehensive study of known performance bugs in Markdown compilers. We identify that the ways Markdown compilers handle the language’s context-sensitive features are the dominant root cause of performance bugs. To detect unknown performance bugs, we develop MdPerfFuzz, a fuzzing framework with a syntax-tree based mutation strategy to efficiently generate test cases to manifest such bugs. It equips an execution trace similarity algorithm to de-duplicate the bug reports. With MdPerfFuzz, we successfully identified 216 new performance bugs in real-world Markdown compilers and applications. Our work demonstrates that the performance bugs are a common, severe, yet previously overlooked security problem.