Understanding and Detecting Performance Bugs in Markdown Compilers
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.
Tue 16 NovDisplayed time zone: Hobart change
23:00 - 00:00 | Artefacts Plenary (Any Day Band 2)Artifact Evaluation at Kangaroo Chair(s): Aldeida Aleti Monash University, Tim Menzies North Carolina State University | ||
23:00 5mDay opening | Opening Artifact Evaluation | ||
23:05 7mKeynote | Keynote Artifact Evaluation Dirk Beyer LMU Munich, Germany | ||
23:12 3mTalk | CiFi: Versatile Analysis of Class and Field Immutability Artifact Evaluation Tobias Roth Technische Universität Darmstadt, Dominik Helm Technische Universität Darmstadt, Michael Reif Technische Universität Darmstadt, Mira Mezini Technische Universität Darmstadt | ||
23:15 3mTalk | Testing Your Question Answering Software via Asking Recursively Artifact Evaluation Songqiang Chen School of Computer Science, Wuhan University, Shuo Jin School of Computer Science, Wuhan University, Xiaoyuan Xie School of Computer Science, Wuhan University, China | ||
23:18 3mTalk | Restoring the Executability of Jupyter Notebooks by Automatic Upgrade of Deprecated APIs Artifact Evaluation Chenguang Zhu University of Texas at Austin, Ripon Saha Fujitsu Laboratories of America, Inc., Mukul Prasad Fujitsu Research of America, Sarfraz Khurshid The University of Texas at Austin | ||
23:21 3mTalk | Context Debloating for Object-Sensitive Pointer Analysis Artifact Evaluation | ||
23:24 3mTalk | Understanding and Detecting Performance Bugs in Markdown Compilers Artifact Evaluation Penghui Li The Chinese University of Hong Kong, Yinxi Liu The Chinese University of Hong Kong, Wei Meng Chinese University of Hong Kong | ||
23:27 5mProduct release | Reuse graphs Artifact Evaluation | ||
23:32 10mTalk | Most reused artefacts Artifact Evaluation | ||
23:42 18mLive Q&A | Discussion Artifact Evaluation |