While the Java Virtual Machine (JVM) plays a vital role in ensuring correct executions of Java applications, testing JVMs via generating and running class files on them can be rather challenging. The existing techniques, e.g., ClassFuzz and Classming, attempt to leverage the power of fuzzing and differential testing to cope with JVM intricacies by exposing discrepant execution results among different JVMs, i.e., inter-JVM discrepancies, for testing analytics. However, their adopted fuzzers are insufficiently guided since they include no well-designed seed and mutator scheduling mechanisms, leading to inefficient differential testing. To address such issues, in this paper, we propose SJFuzz, the first JVM fuzzing framework with seed and mutator scheduling mechanisms for automated JVM differential testing. Overall, SJFuzz aims to mutate class files via control flow mutators to facilitate the exposure of inter-JVM discrepancies. To this end, SJFuzz schedules seeds (class files) for mutations based on the discrepancy and diversity guidance. SJFuzz also schedules mutators for diversifying class file generation. To evaluate SJFuzz, we conduct an extensive study on multiple representative real-world JVMs, and the experimental results show that SJFuzz significantly outperforms the state-of-the-art mutation-based and generation-based JVM fuzzers in terms of the inter-JVM discrepancy exposure and the class file diversity. Moreover, SJFuzz successfully reported 46 potential JVM issues, and 20 of them have been confirmed as bugs and 16 have been fixed by the JVM developers.
Wed 6 DecDisplayed time zone: Pacific Time (US & Canada) change
16:00 - 18:00 | FuzzingResearch Papers at Golden Gate C1 Chair(s): Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University | ||
16:00 15mTalk | Enhancing Coverage-guided Fuzzing via Phantom Program Research Papers Mingyuan Wu Southern University of Science and Technology and the University of Hong Kong, Kunqiu Chen Southern University of Science and Technology, Qi Luo Southern University of Science and Technology, Jiahong Xiang Southern University of Science and Technology, Ji Qi The University of Hong Kong, Junjie Chen Tianjin University, Heming Cui University of Hong Kong, Yuqun Zhang Southern University of Science and Technology Media Attached | ||
16:15 15mTalk | Co-Dependence Aware Fuzzing for Dataflow-based Big Data Analytics Research Papers Ahmad Humayun Virginia Tech, Miryung Kim University of California at Los Angeles, USA, Muhammad Ali Gulzar Virginia Tech Pre-print Media Attached | ||
16:30 15mTalk | SJFuzz: Seed & Mutator Scheduling for JVM Fuzzing Research Papers Mingyuan Wu Southern University of Science and Technology and the University of Hong Kong, Yicheng Ouyang University of Illinois at Urbana-Champaign, Minghai Lu Southern University of Science and Technology, Junjie Chen Tianjin University, Yingquan Zhao Tianjin University, Heming Cui University of Hong Kong, Guowei Yang University of Queensland, Yuqun Zhang Southern University of Science and Technology Media Attached | ||
16:45 15mTalk | Metamong: Detecting Render-update Bugs in Web Browsers through Fuzzing Research Papers Suhwan Song Seoul National University, South Korea, Byoungyoung Lee Seoul National University, South Korea Media Attached | ||
17:00 15mTalk | Property-based Fuzzing for Finding Data Manipulation Errors in Android Apps Research Papers Jingling Sun East China Normal University, Ting Su East China Normal University, Jiayi Jiang East China Normal University, Jue Wang Nanjing University, Geguang Pu East China Normal University, Zhendong Su ETH Zurich Media Attached | ||
17:15 15mTalk | Leveraging Hardware Probes and Optimizations for Accelerating Fuzz Testing of Heterogeneous Applications Research Papers Jiyuan Wang University of California at Los Angeles, Qian Zhang University of California, Riverside, Hongbo Rong Intel Labs, Guoqing Harry Xu University of California at Los Angeles, Miryung Kim University of California at Los Angeles, USA Pre-print Media Attached | ||
17:30 15mTalk | NaNofuzz: A Usable Tool for Automatic Test Generation Research Papers Matthew C. Davis Carnegie Mellon University, Sangheon Choi Rose-Hulman Institute of Technology, Sam Estep Carnegie Mellon University, Brad A. Myers Carnegie Mellon University, Joshua Sunshine Carnegie Mellon University Link to publication DOI Media Attached | ||
17:45 15mTalk | [Remote] A Generative and Mutational Approach for Synthesizing Bug-exposing Test Cases to Guide Compiler Fuzzing Research Papers Guixin Ye Northwest University, Tianmin Hu Northwest University, Zhanyong Tang Northwest University, Zhenye Fan Northwest University, Shin Hwei Tan Concordia University, Bo Zhang Tencent Security Platform Department, Wenxiang Qian Tencent Security Platform Department, Zheng Wang University of Leeds, UK Media Attached | ||